Articles from the ROIS’s Science Report web magazine (2017-2019)

Exploring Japan’s
001–006

Scientific Frontier:Connecting Data
007–012for Human Good
Focusing on Arctic,
Genome,and Data Science

013–018

Inter-University Research Institute Corporation
Research Organization of Information and Systems

Science Report 001-018

©2019 by Inter-University Research Institute Corporation
Research Organization of Information and Systems. All rights reserved. Printed in Japan.
ISBN978-4-909638-11-3 C0040
Exploring Japan’s Scientific Frontier: Connecting Data for Human Good
Focusing on: The Arctic, Genomes, Data Science
SCIENCE REPORT 001-018
Author: Inter-University Research Institute Corporation Research Organization of Information and Systems (ROIS)
Editor in Chief:
The Arctic: Hiroyuki Enomoto, Professor of National Institute of Polar Research (NIPR)
Genomes: Asao Fujiyama, Specially-appointed Professor of National Institute of Genetics (NIG)
Data Science: Tomoyuki Higuchi, Director of The Institute of Statistical Mathematics (ISM)
Written by Rue Ikeya
The English version was created by Hiroko Sato, The Pitch Room, LLC (Massachusetts, USA).
Photographs: Yuji Iijima unless noted below,
Kazutaka Tateyama (p.8 left, 14-15, 25 below, 26 below),
NIPR (p.17, 18 below, 19 left, 25 above, 33 below, 37 above),
Jun Uetake/National Institute of Polar Research (p.18 above),
Jun Inoue (p.21, 22 below),
Shigeto Nishino (p29 below),
Rue Ikeya (p.33 above, 38 above, 51 below),
Hironori Yabuki (p.35),
ArCS News (p37 below, 38 below, 39 right),
Ken Kurokawa (p.43 above, p44 middle),
Primate Research Institute, Kyoto University (p.63 above)
Design: Grid Co.,Ltd., Japan
Published by Inter-University Research Institute Corporation
Research Organization of Information and Systems
Hulic Kamiyacho Building 2F, Toranomon 4-3-13, Minato-ku, Tokyo 105-0001
TEL: +81-3-6402-6200 FAX: +81-3-3431-3070
http://www.rois.ac.jp/

Articles from the ROIS’s Science Report web magazine (2017-2019)

Exploring Japan’s
Scientific Frontier:Connecting Data
for Human Good
Focusing on:
The Arctic
Genomes
Data Science

Inter-University Research Institute Corporation
Research Organization of Information and Systems

CONTENTS

14

The Arctic as a Window

		 into Earth’s Future

10 Foreword
		 Ryoichi Fujii
12 About Science Report

16 001		
Getting Ahead of
		 Climate Change
		 Takashi Yamanouchi
20 002

		Does Arctic Warming Bring
		 on Colder Winter for Japan?
		 Jun Inoue
24 003
		 What is happening with		 the Arctic Sea Ice?
		 Kazutaka Tateyama
28 004

		 Will Living Organisms Survive		 the Arctic Climate Change?
		 Shigeto Nishino and Eiji Watanabe
32 005

		 What Is the Arctic?
		 It’s Complicated.
		 Shinichiro Tabata
36 006
		 Team Japan Looks to Connect
		 All the Climate Dots in the Arctic
		 Hiroyuki Enomoto

40

Decoding the Language

66

Changing the World

		 of the Genome

		 with Data Science

42 00768 013

		 What Have Bacterial Genomes
		 Got to Do with Us?

		 Reinventing the Process		 of Making Things

		 Ken Kurokawa

		 Ryo Yoshida and Ichiro Hasuo

46 00874 014

		 The Next Medical Revolution
		 Could Come from Innovation
		 in DNA Sequencing Technology

		
Data Science–		 the Humanities’ New Tool

		 Yutaka Suzuki

		 Naruya Saitou
		 and Asanobu Kitamoto

50 00980 015

		 How Will Genomic Discoveries
		 Change Our World Views?

		 Tracing the Cosmic History
		 Back to the Big Bang		 Yuji Kohara

		 Naoki Yoshida, Shiro Ikeda
		 and Mikio Morii

54 010		 The Making of the Databases of		 Scientists’ Dream
		 Susumu Goto
58 011
		 Mapping Out Plant Genomes		 for Human Survival
		 Satoshi Tabata
62 012

		 What Do Chimps’ Mutant
		 Genes Say About Us?
		 Tetsuro Matsuzawa
		 and Asao Fujiyama

84 016
		 Data Intelligence for Sport:
		 Put Some Smarts in Your Cheers
		 Yoshiyasu Tamura, Fumitake Sakaori
		 and Akinobu Takeuchi
88 017
		 Changing Patients’ Lives with
		 Data Science
		 Shin’ichi Satoh, Yoichi M. Ito		 and Hisashi Noma
94 018

		 What’s on the Horizon in the		 Changing World of Big Data?
		 Masaru Kitsuregawa
		 and Tomoyuki Higuchi

89Foreword

The Research Organization of Information and Systems (ROIS) is oneof the Japanese inter-university research institute corporations. It
empowers the country’s science community to find solutions for complex issues facing modern society.
The ROIS was founded in 2004 by four inter-university institutes—the
National Institute of Polar Research (NIPR), the National Institute ofInformatics (NII), The Institute of Statistical Mathematics (ISM) andthe National Institute of Genetics (NIG)—as a nexus of their research
network that includes all national and private universities in Japan.
Utilizing the network’s expansive scope of expertise, the ROIS promotes
the exploration of matters related to human life, society and the environment as well as planet Earth through the lens of information andsystems. While bolstering the foundation of research in each of therespective fields, the ROIS also pushes for the pioneering of new
research areas and paradigms.
In addition to resource sharing and joint research within its network
institutes, the ROIS promotes industry collaborations and open sciencefor citizens’ involvement. The ROIS and the four founding research
institutes also strive to foster the next generations of data scientists at
Sokendai (The Graduate University for Advanced Studies).
In 2016, the ROIS revamped its structure to further enhance collaborations and communications among the founding institutes and established the Joint Support-Center for Data Science Research(ROIS-DS).
The Center provides support for data sharing and analysis and educational opportunities to cultivate new talents.
As the ROIS continues its effort to advance data-driven science that
holds key to producing innovations in today’s world, we humbly ask foryour support and participation.

10

Ryoichi Fujii
President

Research Organization of Information and Systems

11

12

About Science Report

Science Report is a website maintained by the
Research Organization of Information and Systems(ROIS) and also the name of a monthly article series
that runs on the site. The ROIS, an inter-university
research organization, produces the articles to keep
the public informed about its latest research endeavors as well as research activities taking place at otherresearch institutions, including universities acrossJapan.

The series covers diverse topics and projects, including cross-disciplinary research that employs novel
research methods and concepts, and highlights how
research collaborations that the ROIS works to promote help propel innovations. Offering scientificexplanations in easy-to-understand language, Science
Report also serves as the research community’s medium through which to communicate with citizens andanswer some of the most frequently asked science
questions.
The ROIS periodically puts together multiple articles
that were posted on the site over time in the form of abooklet. This volume, the first to be published in English, contains installments concerning three topics:
Arctic science, genomics and data science.

It is our hope that this booklet will help people enjoy
learning about scientists’ ingenuity and visions that
the ROIS works to advance.
URL https://sr.rois.ac.jp/

13

The Arctic
as a Window
into Earth’s
Future14

16 001		
Getting Ahead of
		 Climate Change
		 Takashi Yamanouchi
20 002

		Does Arctic Warming Bring
		 on Colder Winter for Japan?
		 Jun Inoue
24 003

		 What is happening with		 the Arctic Sea Ice?
		 Kazutaka Tateyama
28 004
		 Will Living Organisms Survive		 the Arctic Climate Change?
		 Shigeto Nishino and Eiji Watanabe
32 005
		 What Is the Arctic?
		 It’s Complicated.
		 Shinichiro Tabata
36 006

		 Team Japan Looks to Connect
		 All the Climate Dots in the Arctic
		 Hiroyuki Enomoto

15

Science Report

001 The Arctic as a Window into Earth’s Future 01

Getting Ahead of
Climate Change

Ask an Expert: Takashi Yamanouchi,
Professor Emeritus of National Instituteof Polar Research (NIPR)
Takashi Yamanouchi, Professor Emeritus at the National Institute ofPolar Research, specializes in atmospheric science and polar climatology. He serves as Editor-in-Chief of “Polar Science”, an international quarterly journal. For the Summary of Outcomes, GRENE Arctic Climate Change Research Project, please go to https://www.nipr.ac.jp/
grene/e/publications.html

The Arctic is becoming dirtier—or, so it may seem to people
who visit Greenland to find mysterious black speckles covering ice sheet, turning the entire landscape gray.
The soot-like substance is a microbe called Cryoconite,which has spread rapidly across ice sheet cover in recent
years. The emergence of Cryoconite is an example of various
ecological phenomena happening in the Arctic–the place
where scientists say global climate change manifests in themost extreme forms before anywhere else in the world.
“That’s what we call Arctic amplification,” said Takashi
Yamanouchi, professor emeritus at the National Institute ofPolar Research who has led Japan’s major Arctic research
initiative, Green Network of Excellence (GRENE) Arctic Climate Change Research Project, since its inception in 2011
through 2016.
“The effects of global warming are far more visible in the
Arctic than in any other place on the planet. In fact, the average Arctic temperatures have risen twice as fast as the global
average,” Yamanouchi said, explaining the importance of theresearch initiative. And the GRENE-Arctic is now giving people a glimpse into the future, including potential uses of the
Arctic Ocean in ways we’ve never dreamed of before.
The GRENE-Arctic is Japan’s ultimate attempt at decoding climate change mechanisms. It brings together 360 scientists from 40 research institutions—including the National
Institute of Polar research and the Japan Agency for MarineEarth Science and Technology—for cross-disciplinary investigations into all aspects of the Arctic climate system fromthe atmosphere to biosphere.
The Arctic region refers to the area north of 66° 33’ N lati-

16

tude, and the Antarctic region south of 66° 33’ S latitude.
During the International Geophysical Year (1957-1958), there
was much discussion and reporting about unusual environmental changes taking place in those regions ahead of therest of the world. This brought polar amplification to scientists’ attention.

Recognizing the importance of the Arctic and Antarctic
regions as the harbingers of global climate change, Japan soonlaunched observation programs in both the Arctic and theAntarctic.
In 2011, Japan established the GRENE Arctic Climate

Change Research Program, calling on the country’s best talents in the science community to join in the effort to understand the process of climate change and help combat its
impact on human lives.

The Cycle That Will Never End
Unlike the Antarctic that sits on land, the Arctic is mostly
comprised of ocean with sea ice floating over it. This explains
why the Arctic experiences the effects of global climatechange faster and more severely than the south, according toProf. Yamanouchi, who has served as the GRENE-Arctic program’s Project Manager.
“Sea ice bounces off most of the sunlight that hits its surface, but as the ice thins out, the water underneath it absorbs
more light, further accelerating the warming of the water.
This so-called ice-albedo feedback is the chief cause of Arctic
amplification,” Yamanouchi said.
Snow and ice over the land areas of the Arctic continue tomelt at a startling speed, as well, impacting the wildlife and

The scientific station of Ny-Ålesund in the Svalbard islands. The Norwegian baseon the Arctic Ocean is home to 11 different countries’ Arctic observation programs.
The Svalbard Treaty signed in the 1920s guarantees Norwegian sovereignty overthe islands while providing its signatories with equal rights for commercial activities there. Photograph: National Institute of Polar Research17Cryoconite-covered ice sheet in Greenland. Photograph: Jun Uetake/National Institute of Polar Research

A port in Greenland. A warm current from the Gulf Stream keeps the Arctic Ocean relatively warm compared to the
Antarctic. This is why some ports in such northern countries as Norway, Russia and Iceland remain open yearroundwithout ever using an icebreaker. Photograph: National Institute of Polar Research

18

Shuhei Takahashi of Okhotsk Sea Ice Museum of Hokkaido
Arctic summer. Snow used to encapsulate the entire landscapes throughout theyear. As the warming trend continues, the ground has become more visible eachsummer. Photograph: National Institute of Polar Research

lives of the local residents.
The visible scars from the Arctic warming include theexplosion of Cryoconite, the black spats found all over thesurface of ice sheet in Greenland. But, Cryoconite doesn’t
just create an unsightly vista. The GRENE-Arctic team has
observed the ice under Cryoconite melts more as it receives
heat from the light-absorbing black microbe.
“We now know such changes to the ecosystem further
speed up the melting of ice and snow,” Yamanouchi said.

Taking Advantage of
Global Warming
In the meantime, the receding Arctic sea ice may be welcome
news for those in the business of international trade.
“It opens up new possibilities for ocean shipping,” Yamanouchi said. “In our estimate, you can drastically shorten thetravel distance between Japan and Europe by going throughthe Arctic Ocean instead of the Suez Canal,” Yamanouchi
said. “But, in order to use the route for commercial purposes,
you would also have to know how much safety and financial
risks there are with bypassing the Arctic Ocean. People in theindustry expect scientists to figure out how to compute allthat.”The GRENE Arctic successfully predicted the Arctic sea
ice distribution for the summer of 2015 with little margin oferror, and used the experience to draft a methodology forselecting the best ocean cargo routes. Russia, which owns oilfields in the Arctic, as well as China, Korea and other countries that have financial stakes in the region are reportedlyinterested in using this type of methodology to identify new
and better routes.

talks about Capt. Eiichi Taketomi’s Arctic voyage during thePolar Science Symposium 2016 held on Dec. 2, 2016 at the
National Institute of Polar Researchagribusiness ministry’s fisheries investigation ship led by
Capt. Eiichi Taketomi, reached the mouth of the Kolyma River in Siberia via the East Siberian Sea, according to Shuhei
Takahashi of Okhotsk Sea Ice Museum, who is knowledgeable about the topic. The ship then set out for a cross-Atlantic
voyage with a year-supply of food on it in 1941 before turning
around halfway through the journey. The ministry even contemplated a round-the-world trip for the ship from the Arctic
to the Antarctic via the Atlantic Ocean until the world conflicts that led to the German invasion of Russia later that year
interrupted the plan.
The Kaihomaru’s crew for its fifth voyage included two
Meteorological Observatory staff members. One of them was
Takahashi’s father. Shogo Takahashi, who later served as the
director of the Abashiri Local Meteorological Observatory.
The daily record of the voyage that Takahashi and fellow
observatory staff member kept aboard the Kaihomaru
became known as the “Shirokuma (white bear) Diary.”

Urgent Call for Scientists
Nearly 80 years after the Kaihomaru’s tours, the Arctic
remains a source of wonder for scientists. Understanding
what is happening at the northern end of Earth seems morecritical today than ever, as urgent efforts to guard against thenegative consequences of global warming continue aroundthe world.
We believe it requires us to pull together all available
resources at our disposal to tackle the threats facing the planet and its inhabitants. As Japanese researchers work together to do their part as Team Japan, we plan to share some ofour key findings in this Science Report series.

The Heroes Who Came Before Us
Moving cargoes through the Arctic Ocean would not be an
entirely new endeavor. In 1937, the Kaihomaru, Japanese

Released on: May 10, 2017 (The Japanese version released on Dec. 12. 2016)

19

Science Report

002 The Arctic as a Window into Earth’s Future 02

Does Arctic Warming Bringon Colder Winter for Japan?

Ask an Expert: Jun Inoue
Associate Professor of
National Institute of Polar Research (NIPR)
Dr. Inoue studies meteorology focusing on the Arctic and Antarctic
atmosphere and oceans to understand how these elements cometogether to form polar climates. He is particularly interested in lowpressure systems that induce heat and moisture transport as well as
the mid-latitude extreme weather that is driven by the decrease of
Arctic sea ice. He takes advantage of observation data as well as cutting-edge techniques for data analysis for his research.

20

Just as global warming continues to speed up, Japan’s winteris becoming colder than ever.
In 2016, Tokyo had the first snow of the season in November—the earliest snowfall recorded in 54 years. On Dec. 10that year, 65 cm (2 ft) of snow fell in the northern city of Sapporo, followed by another 96 cm (3 ft) of snowfall in less than
two weeks. The wicked weather that brought all traffic in
Sapporo to a standstill remains fresh in our memory.
Anyone who gives a quick review of weather reports fromaround the world would realize this extraordinary wintry
winter phenomenon is not unique to Japan. From North
America to Europe, record-breaking temperature plunges
and blizzards have been wreaking havoc across the mid-latitude area in recent years. This leads us to ask the question: Is
this seasonal “cooling” interconnected with global warmingthat has brought on other extreme weather events such as
major droughts and flooding?

While Earth Warms Up,
Japan Faces Deep Freeze in WinterIn February 2015, the East River running along the island of
Manhattan in New York City froze over, shutting down thecommuter ferry service through the usually ice-free tidal
waterway. The mercury dipped to record lows of minus 18
degrees Celsius in New York City, minus 15 degrees Celsius in
the Great Lakes region and 0 degree Celsius in Florida.
“Japan had a similarly harsh winter in 2005-2006 withheavy snowfalls hammering the regions along the Sea ofJapan,” said Jun Inoue, associate professor at the National
Institute of Polar Research. “The data shows powerful stormsystems have repeatedly developed during winter across the
mid-latitude areas of the globe since the late 2000s, often
resulting in heavy damage from freezing temperatures andsnow.”
Common sense would dictate winter gets milder everywhere as global warming escalates. Inoue said he looked atwhat’s happening in the Arctic as a clue to understand the
puzzling reality.
“I noticed that the Arctic sea ice area was the smallest on
record in the summer leading up to the winter of 20052006,” Inoue said. “I decided to look into the potential relationship between the shrinking sea ice area in the Arctic andthe climate in Japan.

Decoding the Teleconnection Mechanism
The ongoing shrinkage of the sea ice area is one of the major
environmental changes happening in the Arctic. The region
has lost sea ice in the size of the Hokkaido prefecture on average every year since 1979 when data gathering via satellite
began. It dwindled to the smallest size on record in 2007
before it shrunk even more in 2012. The summer of 2016 is
the second on record thus far, which preceded the major cold
snaps that hit North America in December that year.
Environmentally speaking, what happens in the Arctic
never stays in the Arctic. Climate around the world alsochanges in response to that of the Arctic, which is known as
teleconnection. Now, Inoue and his team believe they havedecoded the mechanism of teleconnection.
“The Gulf Stream is becoming warmer and shifting northward, and this is keeping the high-latitude areas in Europe

The Sapporo city was already deep into the snow season as of Dec. 20, 2016. Photograph: Jun Inoue

21

A radiosonde released into the air for aerological observation. Helium-filled balloons are used to lift radiosondes
from more than 600 locations around the world twice a day. The small box-shaped device that functions as aweather station contains instruments for measuring atmospheric pressure, temperature, humidity, wind direction
and speed and other parameters and transmits data by radio to a receiving station. “It is an old-fashioned observation tool. But, when used simultaneously at many locations, it helps you understand what is happening in theatmosphere,” Inoue said. Photograph: Jun Inoue

22

Research fellows Takeshi Terui (from left) and Takeshi Sugimu-

ra and Research Associate Professor Hironori Yabuki, all of the
National Institute of Polar Research, are developing the Arctic

Area Data Archive System (ADS) shown on the computer mon-itor in the photo. The ADS processes data in real time to map

out the Arctic sea ice area, simulates the best route through the
Arctic Ocean, provides data on Arctic sea ice concentration andsea surface temperature and other information useful to Japanand the surrounding countries. The system launched in 2012 asa way to bring together the data on all aspects of the Arctic climate and environment as well as the space data compiled by theJapan Aerospace Exploration Agency (JAXA) and offer it to the
public in easy-to-understand visual formats. Boasting one million page views per month, the ADS now serves as the platform

for the ArCS team to share its research results with such inter-national organizations as the Global Earth Observation System
of Systems (GEOSS) and the WMO.

warmer in winter. We found that this also allows the lowpressure system that develops above the North Atlantic tomove farther north toward the North Pole. Southern winds
from this low-pressure system also push sea ice farther
north,” Inoue explained.
Heat pours into the Arctic, accelerating the warming of
the Arctic Ocean. In the meantime, the northward shift of the
low-pressure systems results in the development of highpressure systems above the continent and this leaves there
cooler.
“Japan lies in between high-pressure systems to the west
and low-pressure systems to the east during winter. These
western high-pressure systems above the Asian continentthat give us Old Man Winter” Inoue said.
Inoue continues to investigate this mechanism through an
Arctic region research project, the Arctic Challenge for Sustainability (ArCS).

Understanding of Global Climate Requires Global
and Reliable Data
Comprehensive climate studies require different types ofdata from various points around the globe. Inoue said collecting atmospheric data, such as air temperatures and humidity
levels at up to 30 km above the ground is as critical to weather and climate studies as ground- and satellite-based observation data. Observation stations that can gather such data
are mainly located in the northern hemisphere, however.
There need to be more observation stations in the Arctic andAntarctic regions as well as other underpopulated parts of
the world, Inoue said.
Collected data benefits not only climate researchers but

also ordinary people as weather prediction centers in Japan,
the U.S., Europe and many other countries use it every day.
The World Meteorological Organization (WMO) has a dataexchange network that connects observation centers andweather prediction centers around the world. Observation
stations first send raw data to the WMO, which log and distributes it to the network members. The centralized system
ensures weather prediction centers and climate researchers
have real-time access to trustworthy data from a reliable
source, Inoue said.

More Arctic Data, the Better Forecasting
The speed and accuracy of weather forecasting today has a
lot to do with the use of the real-time observation data coming out of the WMO.
“Real-time data enables you to compare the accuracy ofvarious forecasting models. You can also plug in different
data to see how that affects scenarios. Using real-time data
this way helps improve the accuracy of weather and marine
forecasting greatly. It also helps you understand what otherdata should be gathered to make forecasting even better,”Inoue said.
“Climate researches in Japan have traditionally focusedon the tropical climate, but more researchers are beginningto focus on the Arctic region these days,” Inoue said. “Both2017 and 2018 are slated as the Year of Polar Prediction. I am
sure such a heightened interest in the Arctic climate will help
improve the quantity and quality of data we gather and push
the advancement of weather forecasting techniques.”

Released on: Jun 27, 2017 (The Japanese version released on Jan. 10. 2017)23

Science Report

003 The Arctic as a Window into Earth’s Future 03

What is Happening with
the Arctic Sea Ice?

If you think seawater should taste pretty much the same
everywhere around the world, think again. In the Arctic, thesalt content of the surface seawater has always been below
the global range of 3.1 to 3.8 percent, and it’s becoming evenless salty in recent years.
Experts point to the increasing amount of water flowing
into the Arctic Ocean from the surrounding rivers as the culprit of the reduced salinity. The diluted seawater doesn’t
freeze the way saltier seawater does. That sparks a chain of
events that can exacerbate global warming.

Ask an Expert: Kazutaka Tateyama
Associate Professor of
Kitami Institute of Technology
Dr. Tateyama is one of the few scientists in the world conducting
research on the changes of sea ice volume in the Arctic and Antarctic
oceans and the Sea of Okhotsk. He is working to develop a system thatpulls satellite observation data to estimate the thickness of sea ice,
which is currently impossible to do without getting hands on the ice.
While monitoring climate changes related to sea ice, Dr. Tateyama
helps lead research projects on Arctic and Antarctic developments,
including sea route and coastal oilfield developments in the Arctic
Ocean. He participates in the GRENE Arctic Climate Change Research
Project and the Arctic Challenge for Sustainability (ArCS).

24

From salinity to chemical balance, all data related to the
Arctic water cycle provides clues for understanding the intricate workings of the Arctic and global climate systems.
Now, we would like to invite you to take a closer look at
what’s happening with the Arctic sea ice and how that helps
fuel the climate change with the help of our expert.

Distinguishing Between Sea Ice and Iceberg
In the Arctic, ice comes in all shapes and forms. Sea ice refers
to frozen seawater with thickness ranging from a few tens ofcentimeters to 10 meters. An iceberg, on the other hand, iscompressed snow layers that forms on a glacier or an ice shelfand breaks away from it after repeatedly washed by tides. It
floats into the ocean like the one that crashed into anddestroyed the Titanic. Icebergs are particularly abundant inCentral Greenland where ice mountains of various sizes continuously break away from the shorelines that look up to
2,000- to 3,000-meter-high ice sheets.
“You listen to the sounds of the vessel hitting and crushingthe ice below while moving through the Arctic Ocean, andyou know how old the ice is,” says Dr. Kazutaka Tateyama,
associate professor at Kitami Institute of Technology. “Newice under a year old sounds like shaved ice. Ice that’s gone
through two or more summers makes thumping noises orsqueaks like pieces of Styrofoam rubbing against eachother.”
Sea ice and icebergs look alike from the above because
they are both covered in snow.
“You need to look at the cross-section of ice. Newly formed
ice looks greyish and you can see seawater through it. One- to
two-year-old ice has blueish tones to it, and it turns greener
as it ages.”
Dr. Tateyama studies Arctic sea ice with a focus on ice volume changes. He says local animals often approach theresearch crew during the fieldwork. They include polar bear,
which use sea ice as a foothold to hunt seals. For polar bear,sea ice plays a crucial role in their survival, Dr. Tateyama
says.
“Some years, I run into polar bear every day. Some otheryears, little sea ice would be left, and bear don’t come, either,”
he says.

Celsius (28.4 degrees Fahrenheit). This means brine hardly
ever freezes and only grows more concentrated and heavier,sinking towards the bottom of the ocean to become part of
the “global ocean conveyor belt”—deep seawater that circulates around the globe. Temperature and salinity along withenergy from the wind received by the surface seawater drive
this down-reaching current southward across the Atlantic
Ocean and then eastward to the Pacific Ocean past the northof the Antarctic. Deep seawater then moves up and down the
Pacific and returns to the Atlantic Ocean. The round-theworld journey of deep seawater takes about 1,000 years to

Heavy Brine Makes Seawater toCirculate Around the WorldThe lower the salt content of water is, the faster it freezes.
When new sea ice begins to form, a matrix of freshwater ice
crystals develops. These ice crystals contain pockets of highsalinity sea water known as brine cells in them. The freezing
temperature in the Arctic is approximately minus 2 degrees

Polar bear that showed up while the research crew was gathering data.
Photograph: Kazutaka Tateyama

25Various types of sea ice seen near the shore of the Sea of Okhotsk. Ice that’s been just formed (upper left) is thinand semi-transparent and gradually grows thicker (upper right and lower left). When pieces of new ice collide witheach other, their soft edges curl up and begin to look like lotus leaves (lower right). But, the drifting patterns of sea
ice in the Sea of Okhotsk have largely changed over the past 25 years, and the volume of sea ice is also declining.
Sea ice drives minerals and all the things that enrich the sea water to circulate across the oceans, creating greatfishing grounds. Sea ice, which covers the sea surface like a lid, also helps calm the oceans. However, sea ice
hasn’t been able to perform such functions as effectively in recent years, according to Dr. Tateyama. “Calm oceans
may turn rough in the future,” Dr. Tateyama says. Photograph: Kazutaka Tateyama

26complete.

The deep ocean circulation shows how heat transfer andsalinity balance of snow and ice in the Arctic contribute toclimate events a halfway around the world.

“Over the past two to three decades, which is a short termwhen you are discussing climate, we have been seeing more
and more thin ice and less aged ice in the Arctic. This is adirect result of global warming,” Dr. Tateyama says. “Thin ice
quickly melts in summer heat, leaving a larger section ofocean surface directly exposed to the atmosphere. This
causes more seawater to evaporate, triggering heavier andmore frequent rain and snow. The salinity of the Arctic surface seawater is declining as the volume of water streaming
into the ocean is increasing. This may cause the Arctic toregain some of the lost sea ice area because lower salt content helps water to freeze. Sea ice extent may also grow if alot of snow falls on the ocean and freezes.
Such seemingly “cooling” phenomena may not last too
long, however, as they are symptoms of global warming. The
Syowa Station in Antarctica observed the fast ice at record
thickness recently, and this can also be explained by global
warming.

The Japanese research group conducts various research

projects in the Arctic. Prof. Atsuko Sugimoto of Hokkaido
University has spent the past 20 years monitoring sub-Arc-

tic forests with a focus on the cycles of carbon and waterand their impact on global warming. “Larch is highly adap-

tive in the high-latitude areas of Northeast Eurasia. Thereare even forests solely comprised of one type of larch.

Human activities impacted the climate over the past 100

Decoding the Arctic Climate ThroughOn-site Verification of Aerial Monitoring Data

years or so. When you look at the tree rings, you can tell

Dr. Tateyama and his research team visit the Arctic every
September or October to find out what’s happening at groundzero of climate change. Sea ice is a relatively new area ofstudy led by Japan’s Tateyama team. Experts believe obtaining accurate and detailed information about sea ice canreveal how climate and those which live in it are intertwined.
Such data can also help improve weather forecasting, alongwith other benefits. This is why the global science community is paying close attention to Dr. Tateyama group’s research
projects.
For the monitoring of sea ice, researchers use remotesensing instruments that do not damage the environment,such as electro-magnetic inductive device and microwave
radiometer. Dr. Tateyama is experienced with the technology as he has used it since 2003 when he was a university
student.
“We want to be able to not only remotely detect ice and its
age but also its thickness preferably in 10 cm increments. We
are trying to develop a remote-sensing system for that,” Dr.
Tateyama says. “We also hope our use of numerical models
for the analysis of satellite and field data will help us overcome some challenges, such as dealing with multi-layered,
oddly shaped ice and distinguishing between seawater and apool of water on sea ice.”
Dr. Tateyama is unique in that he combines surface andaerial observation data to improve the data accuracy for to
obtain more accurate and precise data.
“In April 2016, our surface observation team drove dog
sleds along Greenland’s shores to stake flags in the fast ice
there while our aerial team followed the markings by helicopter to gather data.

taiga spreads to the north of the forestland. Tundra where

what has been happening to the environment over those

years,” Sugimoto says. Permafrost open land dotted with
only moss grows can be found farther north near the Arctic
Ocean. “We are researching the ecosystem in the Russiancity of Chokurudakh (70° N) that saddles over taiga and per-mafrost areas. We are keeping an eye on the taiga forests tosee if it expands northward due to global warming,” Sugimoto says. Sugimoto is also monitoring how thawing permafrost may be affecting the water cycle and how muchmethane is being released from the wetland. “Thawed per-mafrost turns into wetland, which releases methane. But,
the forest absorbs methane. We are continuing with theobservation at our station in Chokurudakh (70° N) andYakutsk (62° N), as well, so we can find out what will hap-

pen to an area that has both forests and wetland,” Sugimoto
says.

Dr. Tateyama’s research project is a collaborative one with
the Arctic Challenge for Sustainability (ArCS), and his teamclosely works with the ArCS team led by Arctic glacierexperts.
“We are focusing on the points of contacts between theland and sea. We research the water cycle and mass balanceof glaciers that flow into the ocean and dissolve into the seawater. Much of what we do has never been tried before, andso it’s very exciting. We are hopeful that a lot of useful information will come out of the work,” Dr. Tateyama says.

Released on: July 10, 2017 (The Japanese version released on Jan. 20. 2017)27

Science Report

004 The Arctic as a Window into Earth’s Future 04

Will Living Organisms
Survive the Arctic Climate
Change?

Ask the Experts: Dr. Shigeto Nishino and
Dr. Eiji Watanabe, Japan Agency for
Marine-Earth Science and Technology (JAMSTEC)
Dr. Nishino (left) leads Arctic observational projects aboard the JAMSTEC’s research vessel, the Mirai, for collections of oceanographic
and atmospheric data. He specializes in the study of how global
warming and declining sea ice affect the physical and chemical conditions of the Arctic Ocean and its ecosystem.To the right of Dr. Nishino in the photo is Dr. Eiji Watanabe, a researcher at the Institute of
Arctic Climate and Environment Research (IACE), JAMSTEC.

28

In the kingdom of marine life, the food chain starts with barely visible organisms known as plankton. Small fish devour
them, and larger fish feast on small fish. If plankton vanish,
all the rest higher up in the pecking order would starve todeath.
Some parts of the Arctic now face the danger of losing
plankton as sea ice continues to melt, diluting nutrients inthe seawater to make it inhospitable for plankton. The ice
melt is also accelerating ocean acidification, resulting in aharsher living environment for crustaceans like crabs andshellfishes.
The world’s oceans are a boundless, 3,800-meter-deep
expanse with an intricate ecosystem in which its inhabitants
and their surrounding environments, from temperature tosalinity levels to concentrations and ratios of chemical components, are intertwined with each other. And, in order tounderstand how these oceans may change due to global
warming, we need to first look at the Arctic Ocean as it is oneof the areas where most dramatic environmental changes are
occurring in the worlds and its conditions have cascading
effects on the entire planet.
So, what is really happening inside the Arctic Ocean? And,
what will it mean for the world’s oceans that cover 70 percentof the Earth’s surface?
Experts from the Japan Agency for Marine-Earth Scienceand Technology (JAMSTEC) will take you on an Arctic journey for answers.

Heading for the Arctic Aboard Mirai
the 8,706-ton Research Vessel
The Mirai, an 8,706-ton research vessel owned by the JAMSTEC, is one of the world’s largest of its kind. It also serves as
Dr. Nishino’s research base and home for months on end
every year.
The annual voyage that starts and ends in Japan always
takes Dr. Nishino and his colleagues through the North
Pacific toward the northern Bering Sea first.
“The northern Bering Sea is a treasure trove of marine
species, and so we focus on documenting about them asmuch as possible while moving north,” Dr. Nishino says.
Once through the Bering Strait that separates Alaska andSiberia, the vessel would enter the Chukchi Sea, a biodiversity-rich area in the Arctic Ocean. The Mirai would thenhead into the deep Canada Basin.
“This is where some major environmental changes havebeen happening in recent years,” Dr. Nishino says of thebasin. “Sea ice has been melting, and the ocean surface temperatures are rising. We see the seawater becoming more
diluted with freshwater, which lowers the nutrient concentration of the water and accelerates the ocean acidification.
We gather a wide range of data in this area to keep track ofthese changes from a macro viewpoint,” says Dr. Nishino,
who has also served as the chief scientist for the Arctic
research voyage organized as part of the Arctic Challenge for
Sustainability (ArCS) in 2016, as well as the previous Arctic
cruises in 2013 and 2015.
In addition to oceanographic and atmospheric data, thescientists onboard also collect information related to waves

The edges of sea ice near Point Barrow in Alaska (71°25’N, 158°40’W) as seen fromaboard the Mirai. Photograph: Shigeto Nishino29

During the JAMSTEC’s 2016 Arctic voyage, a science team successfully used a prototype of a small autonomous
underwater vehicle (AUV) to gather data, such as water temperature and salinity, and to capture images of theunderside of sea ice as well as the activities of plankton below sea ice. Since the late 1990s, the JAMSTEC has strategically installed measurement devices undersea. These instruments include current meters and water temperature and salinity sensors, all of which are retrieved after a period of time. The agency has also recently begun
mooring biochemical sensors for the measurement of oxygen and phytoplankton in seawater.

30

and droplets, greenhouse gas, marine physics, the ocean’schemical environment, and marine life and benthic organisms ranging from plankton to seabirds.

“Though the Mirai is capable of maneuvering near ice-

edge, there are times when sea ice blocks us from what wewant to see or measure, or when weather conditions makedata-gathering impossible. So, we hold a meeting every day
to create a ‘tomorrow menu’ for the next day,” Dr. Nishinosays. “Our goal is to use the Mirai to capture the changes
occurring in the Arctic Ocean to the best of our ability.”More freshwater for More Acidic Seawaterwith Less Nutrients
The Arctic Ocean has two major sources of water: The Pacific Ocean, from which seawater flows in through the Bering
Strait, and the Atlantic Ocean. The Pacific water, which isrich in nutrients and plankton, helps enrich the Arctic marine
ecosystem.
In recent years, sea ice is melting dramatically in the Arctic Ocean. This means a large amount of freshwater in the
Arctic is turning from solid to liquid, diluting the seawater inthe surface layer. The nutrient concentration in the surface
layer declines (oligotrophication), and the Arctic Ocean’salkalescent seawater becomes more acidic. These changes all
could negatively impact the Arctic marine ecosystem.
But, the domino effect of melting ice doesn’t stop there.
Once sea ice is gone, it directly exposes the seawater to theatmosphere. That accelerates the absorption of carbon dioxide in the air into the ocean, which, in turn, exacerbates theacidification of the seawater.
“The Arctic Ocean acidification is advancing at a much
faster rate than other oceans are,” Dr. Nishino says.

Changing Oceans as Carbon Dioxide Eater
Oceans absorbs carbon dioxide like a sponge. In fact, onethirds of anthropogenic carbon dioxide emitted into theatmosphere disappears into the oceans.
When carbon dioxide enters the seawater, phytoplankton
that floats near the ocean surface takes in some of them inthe process of photosynthesis. Zooplankton eat phytoplankton, which feces and bodies sink to the seafloor to become
sediments. This carbon sequestration system known as the“biological pump” effectively removes carbon dioxide fromthe ocean’s surface and stores it at the bottom.
The problem is, Dr. Nishino says, phytoplankton that plays
a crucial role in the biological pump, cannot thrive without
nutrients in seawater.
“As the Arctic seawater gets more freshwater mixed in, thenutrients in the surface water become diluted. Plankton populations in the Arctic decline as a result, making it harder forthe biological pump to function effectively,” Dr. Nishino says.
Acidification of the seawater might also make the Arctic
uninhabitable for organisms that have calcium carbonate
shells, including plankton, crabs and shellfishes, as theirshells could melt away. In science, calcium carbonate satura-

Dr. Eiji Watanabe is responsible for creating high-resolu-

tion oceanography simulations based on the data collectedby Dr. Nishino and his colleagues. He uses the JAMSTEC’s

supercomputer named Earth Simulator and runs two existing models on it: COCO, which allows simulation of ice

melting and current movements, and NEMURO for simulation of the marine food chain that includes nutrients, phy-

toplankton and zooplankton. COCO was developed by theCenter for Climate System Research, The University ofTokyo (currently the Atmosphere and Ocean ResearchInstitute, The University of Tokyo), and NEMURO by themembers of The North Pacific Marine Science Organiza-tion (PICES). “We now have better technologies to allow forinterdisciplinary simulations that takes physical, chemicaland biological processes into consideration. Also thanks to

the improvements in computer performance and simulation models, we can visualize anything from a 10-kilometer-radius eddy in the ocean to the entire Arctic ocean cir-

culation with a horizontal resolution of 5 kilometers. Thiswas unimaginable just 10 years ago. We can use these simulation models to analyze how nutrients and plankton
move through the ocean and conduct research on algaethat grows under sea ice,” Dr. Watanabe says. JAMSTEC

researchers are also working with their global counterparts

to improve 4D simulation models of the Arctic marine foodchain and have so far made great strides in the project.

tion state is expressed with the symbol of Ω. Anything lower
than Ω=1 is “undersaturated,” meaning calcium carbonate inshells and bones of living organisms can seep out into theseawater.
“We began to see Ω values for the Arctic surface water dip
below 1 in the early 2000s. But, it doesn’t mean shells ofplankton, shellfish, crabs and things like that will melt rightaway. It requires more research to understand how themarine life may adapt to their changing environments,”
Dr.Nishino says.

Released on: Aug. 10, 2017 (The Japanese version released on Feb. 10, 2017)31

Science Report

005 The Arctic as a Window into Earth’s Future 05

What Is the Arctic?
It’s Complicated.

Ask an Expert: Shinichiro Tabata
Professor of Hokkaido University
Prof. Tabata is a renowned economist with expertise in statistical andcomparative analysis of Russia’s economic growth. His research topics include the Russian gas and oil industry’s impact on the country’s
gross domestic product (GDP). He has served as the director of the
Slavic-Eurasian Research Center at Hokkaido University through January 2017, and has supported the center’s research projects on interregional comparative studies, border research and indigenous studies as well as the ArCS’ interdisciplinary research on the Arctic region.
He currently serves as a professor at the Slavic-Eurasian ResearchCenter and the university’s Arctic Research Center.

How do you define the Arctic?
The answer to the question depends on whom you ask.
Russia might describe it as the country’s new frontier foroil and gas. Norwegians would see it as a destination for tourists wanting to marvel at the aurora-lit skies. In the case of
the indigenous people like the Inuit and the Yupik, the Arctic
is also ground-zero for their survival against the effects of climate change.
The truth is, the Arctic is all the above and more. The
region that falls inside the Arctic Circle–an imaginary circle
around the North Pole located at about 66° 33’ North–comprises the high seas as well as land and seas belonging toeight different countries, ranging from the U.S. to Canada to
Russia to Scandinavian nations. The culturally diverse grouphas worked together on common causes, but their competing
economic interests also have brought some of them to anegotiation table from time to time.
The political landscapes surrounding the region will likely
grow even more complex as an increasing number of nonArctic nations are eager to become an Arctic partner in thedevelopments of a new sea route and natural resources aswell as for the protection of the environment.
So, what does the Arctic really mean to these stakeholders? And, how do those living in the Arctic Circle feel about it?
Prof. Shinichiro Tabata of Hokkaido University will sharehis outlook for the Arctic’s future from the social sciences
standpoint.
One of the positive consequences of the end of the Cold
War may be the collaborative relationships forged amongst
the Arctic nations that share common goals. In 1996, the Arc-32

tic Council was established with eight countries that havejurisdiction over land and/or seas located within the Arctic
Circle as its members. The members are Canada, the Kingdom of Denmark, Finland, Iceland, Norway, the Russian Federation, Sweden and the United States of America. The Council acts as the intergovernmental forum to promote “cooperation, collaboration and interaction among the Arctic states,
Arctic indigenous communities and other Arctic inhabitantson common Arctic issues,” particularly sustainable development and environmental protection of the Arctic, according
to the Council. Six organizations representing the indigenous
peoples of the Arctic also hold “permanent participants”
status.
“Among all the members, Russia by far has the most say,”Prof. Tabata says. “Russia accounts for 60 percent of the economic activities in the region. The existing Arctic sea routealso lies to the north of Russia. I bet Russians think the Arctic
Ocean belongs to their country.”“Hungary, Romania, Estonia, and Central Asian countries
and Caucasus are typical examples. Our center’s studies now
include Mongolia and Greenland, as well.”
Hokkaido University is known for its cultural and anthropology research, which includes studies of Siberia and indigenous people, such as the Ainu. Prof. Tabata says humanities
and social sciences studies through the Arctic lens can offer
interesting insights.
“The Sami people in Scandinavia and the Ainu have thingsin common culturally, which I think stems from them having
had to adjust to the cold climate,” Prof. Tabata says. “But, thetraditional area study framework doesn’t allow us to bunchthem together as the people of the Arctic. So, I take a differ-

Humanities and Social Sciences
Through Arctic Lens
The Slavic-Eurasian Research Center at Hokkaido University, where Prof. Tabata works, has conducted research on
Russian and Eastern European people and societies for morethan 60 years. In 2014, the center added “Eurasia” to its original name of The Slavic Research Center to reflect the range
of geography and ethnicity encompassed in its research.
“Most people think ‘Slav’ means Russian descent. In reality, though, there are many nationalities or ethnic groups informer Soviet Union and Eastern Europe,” Prof. Tabata says.

Tromso, an island located at 69 degrees north latitude and 350 kilometers (217
miles) north of the Arctic Circle, is a popular destination for tourists looking toexperience Arctic natural phenomena, such as midnight sun and the aurora.

33

The room dedicated to the Arctic Research Center’s exhibit at The Hokkaido University Museum is open to the public for free and draws many visitors year around. (For the museum’s website, please go to https://www.museum.
hokudai.ac.jp/english/.)34

ent approach to research, which is to look at all areas within
the Arctic Circle, from Canada to the U.S. to Russia to the

Scandinavian countries, as one region. Speaking of which, I

believe sustainability is the biggest issue facing the Arctic
region as a whole from the economic and social standpoint,”
Prof. Tabata says.

Russia’s New Frontier for Oil and Gas
The world is growing keenly aware of how much natural
resources the Arctic region has to offer. Fish are just as abundant off the coast of Northern Norway and in the Icelandic
coast as in the Bering Sea. Northern Alaska accommodates
crude oil fields. Russia and Norway have often negotiatedtheir rights over the enormous undersea oil and gas reserves
spanning both countries’ territories.
The region’s oil and gas reserves are particularly drawing
the world’s attention as Russia tries to further tap into them.
“Russia ranks the number one or two in the world in termsof oil and gas production and exportation as well as theirreserve amounts. And so, the petroleum industry is extremely important to the country’s economy,” Prof. Tabata says. “In
fact, it was the petroleum resources in Baku on the CaspianSea that propelled Imperial Russia’s industrialization in thelate 19th Century. Then, Volga-Ural emerged as the “second
Baku” in the 1940s and became the hub of the Russian oil andgas production before Western Siberia took over the spot.
Production is plateauing at both locations now, which is why
the industry is migrating farther north and east for exploration and drilling. Given the industry’s significance to thecountry’s economy, the Arctic development isn’t just important; it’s a necessity for Russia.”

Putting Yamal on the World Economic Map
Among all the areas being developed for potential productionof oil and gas, Russia is particularly invested in the Yamal
Peninsula. Yamal means “the end of the world” in the local
language. Permafrost covers most of the peninsula, whereindigenous people maintain their traditional nomadic lifestyle by herding reindeer.
“Since 2007, the government has been working on the
project to construct a liquefied natural gas production facility here to take advantage of the large oil and gas reserve.
They are constructing a seaport, as well. Once a new Arctic
sea route opens, the port will allow exports to Europe year
around and to Asian countries, such as Japan and China, during summer,” Prof. Tabata says.
But, to get to the point, Russia need to rely on other countries for cutting-edge deep-sea drilling and LNG production
technologies as the country lacks such expertise required forthe development.
“American capital has been involved in Russian oil and gas
exploration since the Baku days. Russia couldn’t develop any
additional oil or gas fields without the technological support
from the U.S., Japan, France and the Netherlands, among
other countries. Russia also needs Asian countries thatimport its petroleum products to show interest in the proj-

Hironori Yabuki, project associate professor at the National

Institute of Polar Research, studies frost of Northeastern
Eurasia. Frost refers to ground soil that stays at or below

the freezing temperature. Permafrost refers to ground soilthat remains in the frost state for 2 or more years. Permafrost spreads out from Siberia and covers 24 percent of the

Earth’s surface. Global warming causes thawing of frost,which in turn helps accelerate global warming. In the upper

left and right photos, Prof. Yabuki and his team install anearth thermometer after boring a 60-meter hole in the

ground in Tiksi in a Tundra on the Arctic shore in 2006.
Data collected is expected to enhance understanding of different stages that permafrost and terrestrial vegetations go

through as they change amid global warming. “Communications with local people is paramount for success of onsite

investigations and monitoring,” Prof. Yabuki says. The low-er left photo shows methane gas coming up from a pondthat was once frost in Yakutsk in Eastern Siberia . The lower right photo shows frost thawing in a town near Yakutsk

in Sakha Republic of Northeastern Russia, which exposes

utility poles (seen in the background) to the danger of falling. (Photographs: Hironori Yabuki)

ect,” Prof. Tabata says.
Japan has served on the Arctic Council as an observer
since 2013 when the Council granted the status at its eighth
ministerial meeting. As of July 31, 2017, there are 13 nonArctic states holding observer status, including such Asian
countries as the People’s Republic of China and the Republicof Korea.
“The Arctic has precious metals and other valuable natural resources that are important to the Japanese economy.
Another and more crucial reason for Japan being involved in
the region is that Japan is on the future Arctic sea route,”
Prof. Tabata says. “Also, given China’s and Korea’s strong
interest in the Arctic, it is imperative for Japan to maintain apresence on the Council.”If all these countries’ attention is any indication, the Arctic
is on its way to becoming a major stage for international politics, business and science.
Released on: Aug. 21, 2017 (The Japanese version released on March 10, 2017)35

Science Report

006 The Arctic as a Window into Earth’s Future 06

Team Japan Looks toConnect All the Climate
Dots in the Arctic

Ask an Expert: Hiroyuki Enomoto
Professor of National Institute ofPolar Research (NIPR)
Dr. Enomoto serves as professor at the NIPR and the director of the
NIPR’s Arctic Environment Research Center (AERC). He holds anundergraduate degree from Hokkaido University and received his PhD
in physical geography from Swiss Federal Institute of Technology(ETH) in Zurich for his study on sea ice and climate. Prof. Enomoto has
participated in various sea ice, glacier and cryosphere observatory
programs in the Arctic and Antarctic and joined the NIPR in 2011 following his tenure at Kitami Institute of Technology in Kitami, Hokkaido.
As sub-project director of the ArCS, which was launched in 2015, Prof.
Enomoto oversees the maintenance of global research and observation sites in the Arctic and assembles a delegate of experts to the Arctic Council related meetings to promote Japan’s “sci-tech diplomacy”
efforts.

36

For many Japanese scientists, the “end of the earth” is becoming a familiar corner of the earth.
Recognizing the urgent need to tackle climate change,
Japan named its first-ever Arctic ambassador in 2013, followed by the Arctic Council’s admittance of Japan as one ofits observer states. By late 2015, the country would develop“Japan’s Arctic Policy,” spelling out its commitment to Arctic
monitoring and research as well as collaborations with theinternational research community. With hundreds of Japanese scientists working together under the framework of the
Arctic Challenge for Sustainability (ArCS)–Japan’s nationalflagship project for Arctic research–the Arctic no longer
seems like a faraway place on the end of the earth. It’s simply
their research base.
Now, global leaders are hoping these Japanese scientists
will help the world make sense of climatic changes in the
Arctic with their data and analysis and address society’s
needs. So, how is Team Japan trying to do just that? An expert
from the National Institute of Polar Research answers to thequestion.

Japan’s Role as Expert Witness for
Arctic Climate Change
Scientists are a hot commodity in global political scenes thesedays. Every stakeholder participating in such events as the
Arctic Council’s meetings wants scientists by their side while
making their points.
“Arctic climate change has global consequences, and people want to know why they are experiencing extreme climat-

ic phenomena and what it means for the future. If you haveample, concrete scientific data to back up your policy proposal, more people will listen to you,” Prof. Enomoto says.
That’s where Japanese scientists come into the picture.
“People want scientists to find ways to use their research
results in meaningful manners for the benefit of the society. I
believe that’s the mission of the 21st Century Arctic research,”
Prof. Enomoto says.
Prof. Enomoto points out, however, that the Arctic climate
is changing so fast that the problems that the scientists aretrying to tackle can be moving targets.
“Nature is moving fast, and it’s like humans are trying tocatch up with it. But, nature continues to beat us to it,” Prof.
Enomoto says.
This may mean that we, as an international research community, need to decide what is the most important thing tomonitor, and develop “observation strategies.”
The Arctic Challenge for Sustainability (ArCS) aims to
decode Arctic climate change by bringing together all theexperts and resources that Japan has to offer on the topic justas its predecessor, the Green Network of Excellence(GRENE) Arctic project, did (See Science Report 001). This“Team Japan” approach is drawing the attention of the global research community, according to Prof. Enomoto, who
serves as part of the ArCS core leadership.
“People look at us as this compact team from a mid-latitude country going all out to advance the Arctic research,”
Prof. Enomoto says. “Just because you are an Arctic country,
that doesn’t necessarily mean you have the best know-howsfor observing the region’s climate. Strategic selections ofJapanese scientists are becoming more visible on the global stage. Some of them,photographed here, participated in the September 2016 general assembly of theProtection of Arctic Marine Environment (PAME), which was held in Portland,
Maine, in the U.S. The PAME is an Arctic Council working group for the conservationof the marine environment and non-emergency pollution prevention. Photograph:
Natsuhiko Otsuka (From ArCS News, ArCS website)

37

Prof. Enomoto talks to the audience in the ArCS public seminar, “The Arctic Research and Japan–What Motivates
Us to Study the Arctic,” held on March 18, 2017, at Seiryo-Kaikan in Chiyoda-ku, Tokyo. The sea ice area in the Arctic shrinks to a minimum size every September. The minimum size from 2012 is the smallest on record thus far,followed by that of 2016. The sea ice area has not grown back at a normal speed since September 2016, however,and the recovery has been particularly slow off the coast of Norway and near Alaska, according to Prof. Enomoto’s
latest findings. “Arctic research is like a mountain. You think you’ve climbed quite a bit and then find out you werestill at its base. This is happening more as the Arctic climate continues to change,” Prof. Enomoto says.

Qaanaaq, a coastal village in northeastern Greenland, is among the communities that host the ArCS’s observation
base. (Right) Photograph: Yoshihiko Ohashi (From ArCS News)
Field observation on the Bowdoin Glacier in July 2016. The site is 20 kilometers from Qaanaaq, and the glacier ischanging rapidly especially on its outer edges. Team Japan has gathered data here since 2013. Photo: Evgeny
Podolskiy (From ArCS News)

38

The ArCS’s public seminar for the residents of Qaanaaq in July 2016. The seminar
was held with the help of an interpreter who speaks English and Greenland’s local
language. In the Greenland which has a population of 56,000, the local language isthe official language. (Photograph: Bungo Nishizawa From ArCS News)

monitoring sites for long-term observations, climate forecasting and sea route planning through simulations, development of data archiving systems, providing information to
the local community and fostering the next generations ofscientists in the field–these are all areas where the Arctic
countries could use fresh eyes to do better, and for TeamJapan, being an outsider helps,” Prof. Enomoto says.
The Team Japan’s goals include setting new, higher standards for data gathering.
“We seek collaborations from the U.S. and Canada forsimultaneous data-gatherings. We propose new observation
methods to improve upon forecasting accuracy. All of thisenables us to collect more and better data,” Prof. Enomoto
says.
Among all parts of the Arctic, Greenland is seeing the fastest climate change, according to Prof. Enomono. Greenlandis the world’s largest island with 80 percent of the area covered with ice sheet. In other words, Greenland comprises oneof the two ice sheets that exist on earth with the other one
being Antarctica. The ice thickness ranges from 1,500 metersnear the shorelines to 3,000 meters inland. Ice slowly moves
from its center to the shore and becomes an iceberg when it
falls into the sea. (See Science Report 003)
“Greenland is a forerunner of climate change. Changes
occurring there gives us an idea of what may also happen in
Antarctica down the road,” Prof. Enomoto says. “On the
ground, compressed layers of snow become an ice sheet.
Lakes that dot the Scandinavian region and Canada are theremnants of an ice sheet from the glacial period that melted.
The weight of the ice pushed up the ground to form hills.
Greenland’s ice sheet is melting fast right now, which could
eventually yield a series of lakes when the ice is all gone. At
the COP 21, the Conference of the Parties that took place inParis in 2015, participating countries set the goal of limiting
the global temperature increase to a minimum of 1.5 degrees
Celsius and a maximum of 2 degrees Celsius above preindustry levels. Some predict an increase above 1.5 degrees
could cause Greenland to melt away rapidly.”Engagement with the local community is essential to thesuccessful operation of research and observation projects.
(See Science Report 005)
“We want local people to understand why we are here, andjoin us in data-gathering. We want them to help us with theirlocal knowledge and experience and show us how to getaround. We would share our data and analysis to help
improve the quality of the locals’ lives. This is a challenge tocommunicate and build the relationship. We don’t want tocome across as foreigners from a faraway country who invaded a population’s space and set up strange-looking measuring apparatus everywhere,” Prof. Enomoto says. “As a firststep, we have been hold a series of workshops open to the
local residents,” he says.
Team Japan has introduced the Arctic Data archive System (ADS), which brings together all the monitoring data, tothe locals at one such workshops and was surprised by thehugely positive response of the participating residents.
“The conversation we had with the residents made us
realize that we should include more social science data in
addition to science data,” Prof. Enomoto says.
Prof. Enomoto says Team Japan is striving to provide awider array of information to foster connections among theecosystem, industry, global politics and regional security.

Released on: Sept. 11, 2017 (The Japanese version released on April 10, 2017)39

Decoding theLanguageof theGenome40

42 007

		 What Have Bacterial Genomes
		 Got to Do with Us?
		 Ken Kurokawa
46 008
		 The Next Medical Revolution
		 Could Come from Innovation
		 in DNA Sequencing Technology
		 Yutaka Suzuki
50 009

		 How Will Genomic Discoveries
		 Change Our World Views?
		 Yuji Kohara
54 010		 The Making of the Databases of		 Scientists’ Dream
		 Susumu Goto
58 011
		 Mapping Out Plant Genomes		 for Human Survival
		 Satoshi Tabata
62 012

		 What Do Chimps’ Mutant
		 Genes Say About Us?
		 Tetsuro Matsuzawa
		 and Asao Fujiyama

41

Science Report

007 Decoding the Language of the Genome 01

What Have Bacterial
Genomes Got to Do
with Us?

Ask an Expert: Ken Kurokawa
Professor of National Institute of Genetics (NIG)
Dr. Ken Kurokawa is professor at the National Institute of Genetics(NIG) and the director of the NIG’s Advanced Genomics Center. Since
2014, he has serviced as a director of “Hadean Bioscience,” a project
funded by the Grant-in-Aid for Scientific Research on Innovative
Areas . Dr. Kurokawa, who studied geology and tectonics in the undergraduate and master’s programs, holds a bachelor’s degree fromTohoku University and a Ph.D. from Osaka University. He joined the
NIG in 2016 after serving as associate professor at the Nara Instituteof Science and Technology and as professor at the Tokyo Institute ofTechnology. After founding Japan’s first full-scale metagenomic project in 2004, Dr. Kurokawa published the analysis of the human intestinal microbiota from 13 Japanese individuals. Dr. Kurokawa is known
for developing the metagenomic analysis technique he used for the
project to study how microorganisms in the soil and hot spring waterschange in relation to the environment.

42

In 2003 when the world celebrated the completion of humangenome mapping, Craig Venter, an American geneticist who
was instrumental to the project’s success, had already moved
onto his new target: Marine bacterial genomes.
He stunned the public in April 2004 with the announcement that he and his team discovered 1.2 million new genes
following their research voyage around the Sargasso Sea. The
news signaled a new era of metagenomics–genetic analysis of
microorganism samples directly taken from a particularlocation to gain a broad understanding about the environment. Metagenomics differs from the traditional genetic
research in that it puts microbes found in the wild straight
through a sequencing machine instead of using microbes
cultured in laboratories.
Because microbes have direct control over both our bodies
and environments, decoding microbial genomes and theirrelationships to the surroundings can pave the way for somany scientific breakthroughs from the medical to pharmaceutical fields. Some people are already anticipating agricultural, construction and various other applications of theinformation that metagenomics can provide.
With the speed and the scale of genetic analysis increasing
ever more, thanks to the emergence of next-generation
sequence technologies, how can we expect to benefit frommetagenomics? --- A leading expert from the National Institute of Genetics will explain.

What Is A Genome Anyway?

A genome refers to the entire set of an organism’s genetic
information, and consists of deoxyribonucleic acid (DNA).
DNA is comprised of four nitrogenous bases known as AGCT
(adenine, guanine, cytosine and thymine). AGCT are attached
to DNA’s double helix in a sequence unique to each species.
The human genome contains about 3 billion bases. Candidatus Carsonella ruddii, a parasitic microorganism, has thesmallest genome discovered to this day with 159,662 bases,
which is equivalent of the number of letters contained in a
typical Japanese 24-page broadsheet morning newspaper.
A codon, or a genetic code, is a sequence of three bases.
Each codon can attract a specific amino acid, and its basesequence order dictates which one of the 20 amino acids it
can attract. Codon patterns are transcribed from DNA intomessenger RNA (mRNA), which are then translated to createa chain of matching amino acids for the production of protein. This DNA-to-protein flow of genetic information is universal among all species.
“Yes, that’s all species–including us humans,” Prof. Ken
Kurokawa of the National Institute of Genetics says,“Genome is a bridge between data and its physicalmanifestation.”43

ature,” says Prof. Kurokawa. “The analysis can also show you
the pH value (hydrogen-ion exponent) and humidity levels of
the environment, which helps you get a good handle on thesanitary condition of your surroundings. On top of that, if you
take time series data, you will be able to see how the environment has changed over time, as well,” Prof. Kurokawa says.

The Tama River system supplies about 20 percent of Tokyo’s drinking water. Photographed here is a downstream section of the river where Prof. Kurokawa and his
students conducted research. Prof. Kurokawa credits the students for the successful analysis of the riverfront microbe genomes.

The Hakuba Hoppo Hot Spring in Hakuba Village in Nagano Prefecture gushes out
through sepentinite, featuring 50 degrees Celsius (120 degrees Fahrenheit) waterwith high hydrogen and alkali (pH11), content. This hot spring environment isbelieved to run parallel to that of the hadean Earth. A group of scientists is conducting metagenomic research on the microbial community that thrives in theboiling water bubbling 600 meters (1,968.5 feet) underground inside of the sepentinite. The work is beginning to shed light on the primitive metabolic system.

In short, microbial genomes contain a treasure trove of
information useful for gaining insights into the world aroundus. Metagenomics attempts to deliver that information to us
through multidimensional analysis and interpretation ofdata.
But how can microorganisms offer this much data todecipher?
“That’s because microbes always respond to environmental factors–the sole controlling factors in changes to organisms–in the same, specific manners,” says Prof. Kurokawa.
“You can always count on microbes to provide the mostobjective data. Metagenomes just have no room for humanmanipulations.”
For the same reason human microbiota can help determine the condition of digestive systems, microorganisms cancontribute to soil research.
“We conducted research on the waterfront microbial communities along the entire 138-kilometer Tama River from the
Okutama Lake in the western edge of Tokyo through theHaneda Airport on the Tokyo Bay. We then integrated socioenvironmental data into it, such as population distributions
and crime rates of the areas. This provides us a comprehensive picture on the community environment. We are now
working to develop technology that enables us to assess aneighborhood environment simply from taking a look at its
microbial community structure,” Prof. Kurokawa says.
This illustrates how metagenomics can layer countless
individual data sets covering ranging topics to generate multifaceted yet cohesive information, Prof. Kurokawa says.
“By using the genome as an equal gauge for all living matter, you can create linkages among various research fields
and industries,” Prof. Kurokawa says. “And, that’s the crux ofthe premise of metagenomics,” he says.

Human and Microbial Genomes: We Are All inThis Together
Microorganisms as a Dependable Research Tool

The most fascinating aspect of the genome, Prof. Kurokawa
says, is that it lends an objective yardstick to define all species
on equal terms. In genomic studies, all living matter fromhumans to microbes boil down to A, T, G and C.
And in the metagenomics, “those four chemicals can add
infinite layers of meaning to the environmental context thatyou are trying to understand,” Prof. Kurokawa says.
For example, people will know what conditions theirdigestive systems are in by analyzing their human intestinal
metagenome.
“We could tell you what the temperature inside yourstomach is by just looking at the genomic analysis of yourintestinal metagenome without ever taking the body temper-

44

Success of metagenomics depends on the sizes and scopes ofaccessible databases. There are currently 170,000 samples of
microbiome available to the public, and Prof. Kurokawa’s lab
is building a “microbe GPS” that shows the environmental
contexts for the organisms when the data is plugged into it.
“We already have catalogs of microbes from all corners of
the globe. By layering other types of information to the data,
we should be able to figure out to a reasonable degree what
the presence of certain microbes means for the environment,” Prof. Kurokawa says.
He believes the “hologenome” approach that includes
human genomes into the mix for data analysis is also a powerful method for understanding the environment.
“Our human cells and the microbes are all made from thegenomes, and they cohabitate in the same environment. The

The Advanced Genomics Center: The Axis ofInternational Academic Collaborations for
Genomic Analyses
The Advanced Genomics Center is Japan’s central institution for genomic studies. As one of the country’s 19 inter-

university research organizations, the center provides universities and researchers with access to databases containing voluminous genome data compiled with the use ofnext-generation sequencing technologies. The center pro-

motes resource-sharing and joint research among all
genome research institutions and also undertakes large-

scale sequencing and analysis projects in response to
The Hadean Bioscience Project, in which Prof. is involved as the NIG’s representative, has many images and videos that explains origin of life with computer-generated graphics and animations. For “The Whole History of the Earth and Life” series
on YouTube, please go to https://www.youtube.com/channel/UCCToEEPlF7ur1m0
efQTHG4g.

requests by universities. The center opened in October 2011in Mishima City in Shizuoka prefecture and has since conducted various cutting-edge genome research in collaboration with other relevant organizations.

idea of treating all the genomes and environmental data aspart of one big system and decoding the relationships among
them is growing into this new approach,” Prof. Kurokawa
says.

Understanding the Earth Environment t
Understand the Origin of Life

Prof. Kurokawa has always approached genetic studies with asimple mantra: To understand life, one must understand its
environment.
With that same principle, Prof. Kurokawa is now tackling
the origin of life study, envisioning the hadean Earth between
4.6 billion-4 billion years ago.
“The reason life scientists can’t begin to fathom how life
began on Earth is because we don’t know anything about the
Earth environment of that time,” Prof. Kurokawa says.
So, some leading scientists in geology, earth science, life
science and planetary science decided to get together anddiscussed the matter.
“We found out that hadean Earth surface environment
was inhospitable to life. Seawater was highly acidic with a pH
value of zero, and melted rocks were swirling in it, like ironinside a blast furnace. Forget the life-nurturing image that
we have of the oceans today. Even if life was born, it wouldn’t
have survived too long in the harsh environment,” Prof. Kurokawa says. “The scientific evidence collected thus far suggests that life may have emerged amid the process of ferocious chemical reactions triggered by radioactivity inside ageyser-like spring on a continent in the primitive era.”
But, Prof. Kurokawa points out that scientists still have along way to go to decode how life began.
“How the genome became responsible for carrying selfreplicating information remains a mystery,” Prof. Kurokawa
says.

The Advanced Genomics Center
http://genome.nig.ac.jp/

Released on: Nov. 10, 2017 (The Japanese version released on July 10, 2017)45

Science Report

008 Decoding the Language of the Genome 02

The Next Medical
Revolution Could Comefrom Innovation in DNA
Sequencing Technology

Ask an Expert: Yutaka Suzuki
Professor of Department of Computational
Biology and Medical Sciences, University of Tokyo
Dr. Suzuki is a professor at the Graduate School of Frontier Science at
the University of Tokyo. He earned his bachelor’s degree in 1994 andhis doctoral degree in 1999, both from the University of Tokyo. After
working for RIKEN (Rikagaku Kenkyujo)’s Genome Science Center as
research associate in 1999, he moved to the Laboratory of DNA Information Analysis at the Institute of Medical Science at the University ofTokyo in 2000 to serve as assistant professor and became associate
professor in 2004. For the past 25 years, Dr. Suzuki has conducted
research focused on transcriptome collaborated with his mentor,
Prof. Sumio Sugano of the University of Tokyo. His research is aimed
at gaining a systemic understanding of how genomic mutation manifests in the form of cancer, neurologic disorders and other types of
diseases.

46

The genome is a set of nucleotide sequences that makes you
who you are and different from everybody else.
Determining what your sequence looks like used torequire enormous time and money. But, thanks to theimmense advancement of sequencing technology since thefirst successful human genome sequencing nearly 15 years
ago, we can now use so-called next-generation sequencers toanalyze our genomes far more quickly, accurately and costeffectively than ever possible before.
With information on an astronomical number of genomes
stored in databases, the big data is helping further advancegenome science. It is also revolutionizing medicine andenabling improvements in multiple aspects of our lives fromthe environment to land and economic development.
With sequencing technology continuing to progress at a
rapid pace, it promises to transform our ourselves. So, whereis this all headed? Dr. Yutaka Suzuki, a human genome
expert, will explain.

Delivering Cutting-edge Medical Treatment
Anywhere, Including the Middle of a Jungle
A handful companies that developed the next-generation
sequencing technologies control the entire global sequencing market. This means that the base technologies that support the industry all come from these same companies. The
monopoly translates into uniform research procedures,
including how to verify experimental data and conduct follow-up experiments, says Prof. Suzuki.
“Having said that, next-generation sequencers present
tremendous possibilities for further advancement and revo-lutionizing medical practice. We must decide how we want tobenefit from the technology and put the research community on the right path toward that goal,” Prof. Suzuki says.
As a step to do just that, Prof. Suzuki has launched the “onsite genomic diagnosis” project to provide better medical
access to people in undeveloped countries. The project’s goal
is to develop a compact, portable sequencer that can be usedanywhere to quickly identify the best course of treatment forpatients and deliver it on the spot. One scenario would
involve drawing blood from a patient suffering a high fever inthe middle of a jungle and conducting high-speed sequencingof the patient’s genome conducted right on the site. The
result would reveal not only what’s causing the fever, such as
malaria and dengue, but also what strain or type of virus orparasite it is, whether it would respond to medication andwhat other underlying infections the patient may have. One
requirement for the sequencer, in addition to its portability
and sequencing speed, is the ability to withstand tropical heatand elements, and Prof. Suzuki and his team are working todevelop a group of technologies that would enable the use of
sequencers in non-hospital, non-sterilized environments,
including outdoors.
“These technologies have a surprisingly wide range ofapplications, including self-health check through genome
sequencing of your own stool sample taken at home, discovering a new species during field research, verifying the origins of seafood like eel and other food products to prevent
false claims and identifying individuals involved in a crime
through genome sequencing of hair,” Prof. Suzuki says.
“Genomic diagnosis” could particularly be useful for quarantine checks at the airport, he says.

Using Genomic Mutation as Weapons
Against Cancer
When it comes to medical use of genomic information, wholegenome sequencing is only the first step. Many researchers
are now focused on finding out how someone’s DNA molecules are organized as a system in order to use that information to predict the person’s medical risks, or keep a disease
from progressing.

The prototype sequencer for genomic diagnosis is small enough to fit in your palm.
The sequencer that Prof. Suzuki is shown holding here needs to be inserted into thespecimen holder, which allows the user to read the processed data and analysis on
one’s personal computer.

47

Single-cell sequencer that deciphers and provides genomic information of each separate cell.

Each living organism has just one set of DNA information,
but mRNA that transcribes information from DNA for synthesizing protein can alter in response to various factors andcan carry different information in different organs. Prof.
Suzuki, who has studied mRNA transcriptome for many
years, says analyzing gene readouts is useful in cancer diagnosis and treatment.
“Cancer is a disease that causes a transcriptome mutation.
We can find out how a genome mutation affects gene expressions and what happens to it if we try to correct it with medication,” Prof. Suzuki says. “Causes and prognosis largely varyfrom patient to a patient because of the genome. This
explains why there are 500 to 1,000 different types of lungcancers alone. Just because a medication worked for one
patient, that doesn’t mean it will help another patient. Everyone has their own story, and we hope genomic mutation
information will help us deliver individualized treatment.”
The Tama River system supplies about 20 percent ofTokyo’s drinking water. Photographed here is a downstream
section of the river where Prof. Kurokawa and his students
conducted research. Prof. Kurokawa credits the students forthe successful analysis of the riverfront microbe genomes.

Taking Out-of-the-box Approach to
Expedite Drug Development
Prof. Suzuki holds a tray for a single-cell isolator/analysis machine. Trays are
divided into microscopic sections that function as receptacles for separated cells,
allowing the machine to read genomic information of each cell.

48

The Suzuki Lab is also working to develop methods for integrating sequencing results and prognosis obtained throughcomputer simulations in order to make individualizedPlatform for Advanced Genome Science: Support Network for Genome Analysis Research
led by the Inter-University Research Institute“Platform for Advanced Genome Science (PAGS)” is a proj-

ect of KAKENHI, the Ministry of Education, Culture,

Sports, Science and Technology (MEXT)’s Grants-in-Aid for
Scientific Research program. PAGS provides cutting-edge

genome sequencing and analysis technology to KAKENHI
supported projects. The National Institute of Genetics(NIG), which is located in Mishima, Shizuoka Prefecture
and is one of the Inter-University Research Institutes,

serves as the central institution for PAGS in which various
A researcher operates a next-generation sequencer. A genome sample needs to beplaced in the black box on which the researcher has her hands. The user can control the machine via the monitor and get sequencing information.

universities and research organizations participate to forma network. PAGS has helped various research projects generate multidisciplinary research outcomes to promote cutting-edge life science findings, as well as the advancement
new genome technologies.

genomic treatment a reality. Chemotherapy may kill 99 percent of cancerous cells, but the remaining 1 percent that
doesn’t respond to the drugs often triggers a recurrence.
“It’s crucial to identify the 1 percent cell with high accuracy. We then need to perform genomic analysis of that cell anduse the result for simulations,” Prof. Suzuki says.
In the meantime, “immune checkpoint inhibitors,” a new
type of cancer medication that activates the patient’s immune
system to attack cancerous cells, has drawn public attention
in recent years. Prof. Suzuki points out that the ability to distinguish and isolate cells to target is important in this type oftreatment, as well.

Single-cell Technology x Next-generation
Sequencers for Cutting-edge Cancer Treatment
Single-cell technology refers to the technology for isolating
and analyzing a single cell. When trying to analyze a genome
sample with a next-generation sequencer, researchers normally mush cells before putting them through the machine.
In case of cancer, however, they aren’t trying to evaluate thesample as a whole.
“In partnership with Dr. Ryoji Yao, principal investigatorof the Division of Cell Biology, Cancer Institute, The Japanese Foundation for Cancer Research, we are conducting
research on single-cell technology for isolating each cell andanalyzing it with next-generation sequencers. Our initial
focus is colorectal cancer,” Prof. Suzuki says.
The project is part of the “Platform for Advanced Genome
Science” that uses revenues from genome sequencing to augment grants that support researchers. “We have high hopesthat the project will elucidate how colorectal cancer cells are
structured and particularly how would-be cancerous cells
emerge and mutate,” Prof. Suzuki says.

Platform for Advanced Genome Science (PAGS)
https://www.genome-sci.jp/eReleased on: Dec. 11, 2017 (The Japanese version released on July 10, 2017)49

Science Report

009 Decoding the Language of the Genome 03

How Will Genomic
Discoveries Change
Our World Views?

Ask an Expert: Yuji KoharaSpecially-appointed Professor of
National Institute of Genetics (NIG)
Dr. Kohara is a specially appointed professor at the National Instituteof Genetics(NIG) and the director of the ROIS’s Database Center forLife Science(DBCLS). He serves as the principal investigator of “Platform for Advanced Genome Science(PAGS)”, which is one of the Ministry of Education, Culture, Sports, Science and Technology(MEXT)’s
Grants-in-Aid for Scientific Research program. After receiving a PhD’s
degree in science from Nagoya University, he worked as a research
fellow for Medical Research Council’s Laboratory of Molecular Biology
in the United Kingdom. He joined the NIG as professor in 1996 andserved as its director from 2004 through 2012. Amid the fast advancement of molecular biology, Dr. Kohara has worked to decode the connections between the genome and phenotypes. As data gathering andsharing are key to promoting genetic research, Dr. Kohara is also
focusing on the development of integrated databases.

50

Thanks to the advancement of technology, we now sequence
countless genomes every day, including personal samples
and the DNA of living matter around us. All such data
becomes aggregated to form big data, which gives us new
insights into life. For example, we now know what separates
humans from chimpanzees is a 1.23 percent difference innucleotide sequences of the two species’ DNA. Big data also
led to some revelations that resulted in a rewriting of thephylogenetic tree of evolution.
The genome provides scientific evidence useful to prove or
disprove hypotheses. The demand for this versatile researchtool continues to grow in research fields, many of which have
had little to do with the genome until recently.
But what does this really mean for our future? How areresearchers trying to leverage the technology? And how will
our new discoveries change our perspective on life?
Dr. Yuji Kohara of the Database Center for Life Science
will share his view.

One Technological Breakthroughs
After Another
Genomics is a fiercely competitive research field, where not
only scientists but also technologists from around the world
are racing to innovate. To put the speed of evolution in perspective, “a couple of major technological innovations
emerge every five years,” according to Prof. Yuji Kohara of
the National Institute of Genetics, who serves as the directorof the ROIS’s Database Center for Life Science (DBCLS).
The industry-standard genome sequencer also needs to bereplaced with a newer version every so often to keep up withtechnological advancements.
“As soon as a new machine becomes available, we must
adopt it and adjust our procedures and operations accordingly,” Prof. Kohara says.
In other words, research labs would need to review andmodify their entire research process, from what types ofexperiments to carry out to what samples to prepare to how
to conduct analysis. Such reconfiguration requires high levels of expertise each step of the way.
In the meantime, genomic analysis as a research tool continues to make its way into various research fields.
“Researchers who weren’t even thinking about the word,‘genomes,’ yesterday are suddenly talking about sequencing
them today. We are seeing more and more of this,” Prof.
Kohara says. “This trend is particularly noticeable in theenvironmental, medical and agricultural fields. The genomic
analysis of river soils and bacteria, for example, can reveal
interesting facts. Medical researchers are now interested indoing not only genomic diagnosis but also genomic analysis
of intestinal bacteria. Agricultural researchers are looking to
use genomic analysis for potential crop improvements.”
The demand for single-cell genomic analysis is also on arise, Prof. Kohara says.
Individual labs only cannot do so much to catch up with
rapid technological changes by themselves. But, what if there
was a centralized system that pulls together all the expertiseneeded for making other important changes–such as software and hardware upgrade–and makes it accessible to labs?
This idea led to the launching of “Platform for Advanced
Genome Science (PAGS).” PAGS is a project of the Ministry of

Genomic analysis of river soil and bacteria is particularly popular.

51

Education, Culture, Sports, Science and Technology(MEXT)’s Grants-in-Aid for Scientific Research Program
known as the KAKENHI program. PAGS makes cutting-edge
technologies for genome and data analysis available toresearchers when requested in order to help them carry out
their KAKENHI research projects.
In 2000, a core-facility team was formed within a KAKENHI project called Grant-in-Aid for Scientific Research on
Priority Areas. This team was the precursor to PAGS’s
research support team, according to Prof. Kohara. Thisteam’s primary focus changed over time to aiding genomic
research. It also redesigned its structure to facilitate multidisciplinary distribution of resources and technologies tobecome the NIG-led support system that it is today.
PAGS’s research support team coordinates resources andexpertise that university labs request for their KAKENHI
projects. The team assists universities with the alignment
and maintenance of the latest equipment and technologies
and conducts genomic analysis for some of the most advanced
research projects. Prof. Kohara represents the PAGS.
“As PAGS’s support team adopt newer equipment, it is
becoming capable of sequencing genomes faster and moreaccurately than ever. Informatic scientists in PAGS’s support
team have access to more actual data through assisting university labs, which, in turn, is helping them improve theiranalysis skills,” Prof. Kohara says. “PAGS’s support team also
coordinates a one-week on-the-job training program for students to gain necessary skills and better contribute to the
KAKENHI projects for which they work. In other words, our52

team helps put KAKENHI labs and PAGS’ support team on apath for continuous improvements.”

If You Want to Win the Competition,
Build Databases
Genomic data is critical to life science research and becomes
more so as data accumulates.
“In the game of big data analytics for genomic research,
the one with the most amount of data wins,” Prof. Koharasays. “In addition to the U.S., places like China have megaanalytics centers. These are the places that get the largest
amount of data because data naturally goes to analytic service providers. This explains why Japan needs to come up
with a way to attract and compile more data, so Japanese life
scientists have more data with which to work,” Prof. Kohara
says.
But, in order to truly tap into the potential of genomic big
data, one must have not only a substantial amount of data
but also information that puts the data in context.
“For example, in order to use genomic big data for medical
research, you need to link genomic data with epigenetics ormedical records to glean knowledge from it,” Prof. Koharasays. “Although ‘we are all made from genomes’, all thosebacteria and other life matter that live with us help shape us,”Prof. Kohara says.
Hologenome refers to sampling and analyzing of genomes
in the entire environment that surrounds us, including bacteria outside our bodies and those inside our organs, such as

National BioResource Project, the Database for
All Organisms from Prokaryote to Humans
The purpose of National BioResource Project (NBRP) is tocollect, preserve and share samples of 30 different biore-

sources that are regarded as strategically important forJapan’s research projects.
Bio-resource refers to “systems, groups, tissues, cells,
and genetic materials of animals, plants, and microbes andtheir information as research and development materials”
according to the NBRP website.
The Genetic Strains Research Center at the National
Institute of Genetics (NIG) serves as the NBRP’s portal for
information and model species. Dr. Shoko Kawamoto,associate professor at the Genetic Strains Research Center, was recently appointed to lead the NBRP.
“We are trying to build a bio-resource database thatallows for cross-species search,” Dr. Kawamoto says. “Thatmeans the database has to have sequencing data of allmodel species’ genomes as well as analytics on the bulk of
those genomes.”Once common denominators among different species
become clear, it enables replication of a scientific experi-

National BioResource Project (NBRP) Official Website
http://nbrp.jp/
More than 28,000 research papers have used NBRP resources.

the stomach.
As hologenome research continues to advance, the line
between the human and the environment may become more
ambiguous. We may not be just the bodies that are covered
with the skin after all; things around us could also be considered as a part of us.

Dr. Shoko Kawamoto, associate professor at the Genetic Strains
Research Center, was recently appointed to lead the NBRP.

ment with multiple species. For example, when a newly
developed variety of wheat grows well, one might be able
to create a same type of variety of another monocot.
“It might also allow replacing mice and rats with theircounterparts that are structurally much simpler, such aszebrafish and drosophila, for experiments in research on
human diseases. There is a growing expectation that thiswould help speed up research on rare diseases,”Dr. Kawamoto says. “The NBRP could potentially match clinicalresearchers with drosophila researchers,” she says.
In addition, the NBRP serves as a Japanese arm of the
Global Biodiversity Information Facility (GBIF), an “opendata research infrastructure” that gathers and provides
access to information about all kinds of species to better
understand ecosystems around the world. The NBRP has abiodiversity registry through which people can report what
species lives and where.
“Research data on spiders on the island of Yakushima
and swallows nestling in the Kinki region are examples ofwhat we’ve collected through the registry,” Dr. Kawamoto
says.
But having an intelligent database may not help as
much if researchers don’t know how to tap into it, says Dr.
Kawamoto, who has the experience as a genetic
researcher.
“Demand for personalized medical treatments is expected to grow. We are going to keep that in mind to build anopen science type of database system that caters to theneeds of end users like patients,” Dr. Kawamoto says.

“That can also lead to the profound question of what life isand what you consider as an individual.”

Released on: Jan. 25, 2018 (The Japanese version released on Aug. 10, 2017)

53

Science Report

010 Decoding the Language of the Genome 04

The Making of the
Databases of
Scientists’ DreamAsk an Expert: Susumu Goto
Professor of Database Center for Life Science(DBCLS)
Dr. Susumu Goto (right) is a professor for Database Center for Life
Science (DBCLS) at the Research Organization of Information and
Systems’ Joint Support-Center for Data Science Research. Before
joining the DBCLS in 2017, he worked for 23 years at Kyoto University
Institute for Chemical Research, where he helped Prof. Minoru Kanehisa found a bioinformatics database called Kyoto Encyclopedia of
Genes and Genomes (KEGG) and developed his expertise in bioinformatics, an interdisciplinary science field that uses computer to sortand analyze big biological data. Dr. Goto earned his bachelor’s anddoctor’s degrees in computer science in 1989 and 1994 respectively,
both from Kyushu University. Dr. Toshiaki Katayama (left), a Project
Assistant Professor at the DBCLS, has led BioHackathon, the DBCLS’s
international coding camp for life science data standardization, since
its inception 10 years ago.

54

Isaac Newton experienced his epiphany while in a garden
with apple trees, and Archimedes, a bathhouse. In the case ofmodern life scientists, their databases could become their goto place to seek inspiration to find their own eureka moments.
Bioinformatics experts from around the world, including
those in Japan, are making progress on the decades-old initiative to develop ways to blend all sorts of life science dataand create the most comprehensive and cohesive reservoir of
information imaginable to accelerate scientific discoveries.
The ultimate database they envision would not only make anastronomical volume of information available at the user’s
fingertips, but also show how seemingly unrelated data areconnected in the real world. For example, data on a humangene could encompass anything from the explanations about
how the same gene works in other species’ systems to what
diseases are associated with the gene.
With big data growing even bigger and more important inlife science, there is an impetus for the movement to consolidate scattered biological data. Two experts from the Database Center for Life Science (DBCLS) who have been on theforefront of the movement will explain what progress has
been made thus far in Japan and what challenges still lie
ahead.

Database as an Encyclopedia of Biology
Life scientists began dreaming up integrated biological databases during the 1990s as they became flooded with billionsof pieces of genomic data. Among those dreamers were scientists at Kyoto University Institute for Chemical Research,
who envisioned creating a virtual encyclopedia of biology.

They appropriately named their project, Kyoto Encyclopediaof Genes and Genomes (KEGG).
“Back then, all you saw in databases was character data
without context, such as nucleotide acid and amino acidsequences, whereas what’s in textbooks was mostly graphicaldata, explaining how metabolic pathways and signal transduction pathways work,” Prof. Goto, one of KEGG’s founders,said, looking back on the early days. “We thought it would begreat if we could combine both types of information. We figured the web, which was becoming popular at the time,
would work well as media for that.”

relationships among species from the whole new viewpoint of
how one species’ chemical processes influence another’s,”
Prof. Goto said.

Standardizing Data to Make It
Sharable Among All Databases
There are many databases in Japan that are open to the public. These databases come in all sizes and forms, covering a
range of species from microbes to eukaryotic to primates toUnderstanding Human Genes in
Relation to Other Species’ Genes
KEGG is a database that brings together genomic and genetic data with the information about genes’ roles in “pathways,”such as metabolic pathways and signal transduction
pathways.
“Once the genomes of the human and tens of thousands ofother species were sequenced, it became clear what genes
are there. And we can use diagrams to show things like what
each gene does to cause a chain of metabolic reactions.
KEGG calls the flowchart describing this network a ‘pathway
map,’” Prof. Goto said.
Pathway maps make it easier for people to grasp and compare the pathway patterns and the genes involved among various species.
“KEGG also catalogue genes found in ocean and soil samples and compile information about the gene functions. So,
we expect the KEGG database will enable us to look at the55birds. Major databases include Tohoku University’s Tohoku
Medical Megabank that collects human genomic information and Kazusa DNA Research Institute, which, for the mostpart, deals with plant genomes.
The DBCLS wants researchers to be able to simultaneously access many of these databases and effortlessly cross-reference all kinds of data, including chemical compounds andstructures, pathway information and genome data on various
species. This means all data must be standardized for integration, and developing technology for it is the key, Prof.
Goto said.
“We are using semantic web technology to develop a data
integration system that works with a data model called
Resource Description Framework (RDF). RDF allows thesystem to learn the context of data and link data accordingly.
So, you can search a gene by an associated disease and viceversa, for example. You can also look something up by genedisease correlation types,” Prof. Goto said. “With this system,
it’s super easy to locate the information that you are looking
for. The system also helps you analyze and interpret data
more accurately and efficiently.”
While the system is being constantly improved and updated, researchers across Japan can already take advantage of it
to obtain diverse data from multiple databases. It’s made anopen source system so people can use it as it suits them,according to Prof. Goto. “The user might be a bioinformatician interested in using the system’s API to develop a propri-

56

etary application, or could be a data scientist who wants to
extract information from the databases to make a discovery,”Prof. Goto said.

Big Data for Genomic Therapy
For the past 10 years, the DBCLS has organized BioHackathon, an annual international coding camp, to promote
standardization and integration of life science data.
“The organizers are particularly focused on the integration of medical databases in recent years because more people are growing interested in connections between genomic
mutation and the causes of human diseases and that sort ofthing,” said Project Assistant Professor Toshiaki Katayama,
who has led the hackathon since its inception.
For BioHackathon 2017, Project Assistant Professor Katayama said he expects lively discussions on the topic ofgenome graphs, a cutting-edge tool for analyzing individual
genomes.
“There are slight individual differences in humangenomes. Research institutions have traditionally stored
variant data separately as reference data. Genome graphs
bundle an array of variant datasets into an intelligible batchof information” Project Assistant Professor Katayama said.
“This would allow researchers to laser-focus on the genomesof the Japanese, for example. Genome graphs are very usefulthat way.”Here in the photo, Project Assistant Professor Katayama

devoted the past 10 years for the development of basic tech-explains TogoGenome, which is one of the services offered

nology for database integration. We expect our focus will

which usually consists of a one-day symposium and a five-tion in response to the “Global Alliance for Genomics andby the DBCLS. He also described about the BioHackathon,days hackathon. The symposium was expanded into a twoday event for BioHackathon 2017 to mark the event’s

10-year anniversary. “What was new last year was that we

had more participants from medical and pharmaceuticalfields, including researchers from a Japan Agency for Med-

ical Research and Development (AMED) project. We’ve

What’s also key to clinical use of big data is the development of the standardized “pipelines” that automates a stringof tasks from integrating data to connecting genes with diseases to identifying the best medical treatment, Project
Assistant Professor Katayama said.
“The pipeline that we envision would use a single graph tobundle all genomic information, allowing the users to apply
the same pipeline with the cutting-edge genome graph technology to the subgraph sorted by disease or race,” Project
Assistant Professor Katayama said.

now shift to international collaborations for standardizaHealth” and other similar initiatives calling for global data
sharing,” Project Assistant Professor Katayama said. The

Symposium portion of BioHackathon 2017 took place during Sept. 9-10 at JST Science Plaza in Chiyoda-ku, Tokyo,
followed by the hackathon camp during Sept. 11-16 at Hotel
Taikan in Iwate prefecture.

Project Assistant Professor Katayama pointed out that thedevelopment of Common Workflow Language (CWL) used towrite such data processing should also become a theme for
BioHackathon 2017.
“The entire world is working together to move toward
data standardization,” he said.

Released on: January 10, 2019 (The Japanese version released on Sept. 11, 2017)57

Science Report

011 Decoding the Language of the Genome 05

Mapping Out Plant
Genomes for Human
Survival

If you are trying to make sure everyone on earth will haveplenty of quality food to eat, you may care to learn how cyanobacteria’s DNA works. The bacteria commonly known as
blue-green algae are the origin of chloroplast, and its genomic information provides the fundamental understanding of allplants that depend on photosynthesis to survive. Genomic
analysis of such earliest species as well as more recent ones
also sheds light on how plants have evolved to overcome ecological challenges over time. Plant genomics is now increasingly gaining the public’s attention as weather patterns grow

Ask an Expert: Satoshi Tabata
Director of Kazusa DNA Research Institute
Dr. Tabata is an award-winning genome scientist known for his leading role at Kazusa DNA Research Institute in its successful sequencing of cyanobacteria’s complete genome in 1996. He received hisbachelor’s of science in biology from Kobe University in 1977 and his
doctorate of science from Kyoto University in 1983 before serving as a
postdoctoral fellow at the University of California, San Diego in 1982
and as a research assistant at Kyoto University Institute of Chemical
Research in 1982. He joined Kazusa DNA Research Institute in 1994
as a researcher, where he has served as director since 2013. He hasreceived the gold medal at Tokyo Techno Forum 1997, a JapaneseSociety of Plant Physiologists Award and a Kumho Science International Award, both in 2001.

58

more unpredictable and extreme, necessitating us to tap into
the power of life science to find ways to help plants better
adapt to the environment. In 1996, Kazusa DNA ResearchInstitute of Japan successfully sequenced cyanobacteria–
which was only the fourth completely sequenced genome in
the world and the first in Japan. The Institute has sincesequenced the genomes of various crop plants, including
strawberries, tomatoes, sweet potatoes and napa cabbage, bycollaborating with universities, research institutions andcorporations. Dr. Satoshi Tabata, the director of Kazusa DNA
Research Institute, who played the central role in the 1996
sequencing of cyanobacteria, will explain how researchers
could use genomic data of plants for societal common good.

The “Mutants” on Our Dining Table
Plants cannot move like animals do. That explains why plants
have more genes and longer genomes than animals do,
according to Dr. Tabata of Kazusa DNA Research Institute.
“Plants have numerous genes that can come in to play inorder to help adjust to harsh environments, compensating fortheir inability to relocate,” Dr. Tabata said. “Animals, on theother hand, have fewer genes, which become reprogrammed
in response to environmental changes. So, plants and animals have contrasting survival strategies.”
Parts of the nucleotide sequences in the genome function
as genes while the rest are only there to connect the genes
without the protein-producing functionality. Plant genomes
contain more gene parts and less connection parts than animal genomes, according to Dr. Tabata. Plants’ genomes arealso longer.
Many plants also have multiple genomes.
“The human only has one genome comprised of a pair ofchromosomes with one side of the pair representing thematernal heredity and the other side paternal. In contrast,some of wheat have sextets of chromosomes, or three
genomes. The wheat used to make the bread we eat has three
genomes–genomes A, B and D–that are similar to but slightly different from each other,” Dr. Tabata said.
But, why does the genome multiply in plants?
“It probably stems from some sort of mutation that occurs
when cells divide. Genome multiplication would kill animals,
but plants tend to tolerate it,” Dr. Tabata said.
“Heterosis–crossbred species’ superiority in the growthrate and other features–is also prominent among plants. And
we know that genome multiplication causes plants to growlarger. As humans intentionally selected these “mutants” forcultivation, they have become crop plants,” Dr. Tabata said.
These crop plants include sweet potatoes that have a sextet of chromosomes and strawberries that have an octet ofchromosomes. Their genomes are longer and more complex
than animals’ genomes.

Kazusa DNA Research Institute’s campus in the scenic pasture of the Academia
Park in Kisarazu City in Chiba Prefecture.

59

“The genomes of crop plants, in particular, are extremely

difficult to analyze for that reason,” Dr. Tabata said.

From the Lab to the Field

Dr. Tabata talks about the ongoing research projects at Kazusa, which, in addition
to plant genomic research, conducts genome analysis on rare human diseases for
personalized medicine per request. The red stuffed animal behind him is CHIBA+KUN, the official mascot of Chiba Prefecture.

60

Applying the knowledge gained through genomic analysis
inside the lab to crop cultivation is a challenging task.
“In research projects, we’ve traditionally used ‘model
plants’ that are design-bred for lab uses only. Researchers
didn’t know how to take the data from lab experiments conducted in meticulously controlled environments and applythat to the field environment where it would suddenly rain
and snow and have diseases striking plants out of the blue,”
Dr. Tabata said.
Dr. Tabata pointed out that this gave rise to the question:“Whose job is it to research breeding techniques for crop
plants?”“I thought we must take on the challenge and establish thelinkage between genomics and the data from the fields. To dothat, we need to be able to scientifically understand field data
and develop methodologies for it. We would then record how
plants changed under what conditions and evaluate the data.
That’s exactly how we are conducting research on crop plants
at Kazusa DNA Research Institute,” Dr. Tabata said.

The National BioResource Project (NBRP)
contains searchable data on about 250,000
different plant species
The Japan Science and Technology Agency’s CREST (Cre-Arabidopsis thaliana, rice, wheat, barley, chrysanthemum,

nology Innovation) is currently promoting this initiative of
connecting genomics with field data through its program
titled “Creation of fundamental technologies contribute to
the elucidation and application for the robustness in plants
against environmental changes.”
Dr. Tabata believes data and knowledge from plant
genomic research should be leveraged to help solve realworld problems, just as human genome research is helping
the development of effective treatments for diseases.
“We need to remove some hurdles that are in the way ofgetting there. I think it’s Kazusa’s job–and the Japanese science community’s job–to figure out how to do just that,” Dr.
Tabata said. “And this should be a rather immediate goal andnot a distant one. Climate is rapidly changing, and we areseeing different pests and plant diseases migrating fromSoutheast Asia to as far north as the Kyushu Island. We know
we need to quickly develop new varieties that can withstandthe increasingly challenging environment.

to and algae are among the 30 different bioresources thatate Revolutionary Technological Seeds for Science and Tech-morning glory, Lotus japonicus, Glycime max / soja, tomaare registered in the National BioResource Project (NBRP)
as strategically important for Japan’s research projects. The

NBRP collects, preserves and shares samples of these bioresources and enables searches of data on 250,000 differ-ent plant species on its website. Shown here is a screenshotof the rice database.

Plant Genomics for Common GoodDr. Tabata said it’s a testament to the advancement ofgenomic science that people are discussing how to apply theknowledge to cultivation.
“As an undergraduate biology student, I used to wonder
how much longer it would take to get the entire genomic picture of a species,” he said. “Back then, biology meant analyzing individual phenomena or individual genes that we knewof and compiling those understandings to create a big picture. Then genomics emerged, and what came along with it
was this new approach to biology, in which we first list all
substances that are useful to understanding the genomic
innerworkings of a species and gather data according to thelist to develop the whole picture. That’s what we call datadriven science,” Dr. Tabata said.
For example, researchers would gather and analyze
genome-wide data on how different proteins interact witheach other, what substances are produced through the metabolic process and what types of chemical chain-reactions
those substances have. Kazusa DNA Research Institute is
working to expand the databases that allow for such “omics
analysis.”“It’s important, Dr. Tabata says, given that genomic databases are generally intended for multidisciplinary uses. What
researchers need to remember, however, is that multiple factors play into omics analysis; two identical genetic codes inomics data can mean two different things. This is important,
Dr. Tabata says, given that genetic databases generally serveas the platforms for multidisciplinary collaborations. Even if
you integrate all the data and find a common gene among
different kinds of species, it may function differently in eachkind of the species because what caused the gene to be born,“Oryzabase” (rice database)–Core operating organization: The National Institute of Genetics
https://shigen.nig.ac.jp/rice/oryzabase/such as the environmental factors and other genes, vastly
vary in each case,” Dr. Tabata said. “Genomic data provides
the foundation for biological research. How to interpret thedata and how to layer that knowledge on top of the foundation will be the key in further advancing plant genomics.”
Dr. Tabata has made efforts to advance plant genomics tothat end, collaborating for a KAKENHI project called “Platform for Advanced Genome Science (PAGS)” from 2010 to2014. Using plant genomics for societal common good isimportant, Dr. Tabata said. After all, the survival of plantsmeans the survival of humans.

Released on: May 31, 2018 (The Japanese version released on Sept. 11, 2017)

61

Science Report

012 Decoding the Language of the Genome 06

What Do Chimps’ Mutant
Genes Say About Us?

Ask the Experts: Tetsuro Matsuzawa
Distinguished Professor of Kyoto University
Institute for Advanced Study (KUIAS)
Dr. Tetsuro Matsuzawa serves as deputy director-general and distinguished professor at Kyoto University Institute for Advanced Study(KUIAS) with a joint appointment as professor for the university’s Primate Research Institute. In November 1977, three and a half years
after receiving his bachelor’s degree in philosophy from Kyoto University in 1974, Dr. Matsuzawa founded a research project known as Ai
Project to study the mind of the chimpanzee while also conducting
surveys on the life of chimpanzees in the wild. He has used his
research result to better understand human intelligence and behaviors as well as evolution, establishing a new academic field called
comparative cognitive science.

62

Ask the Experts: Asao Fujiyama
Specially-appointed Professor of
National Institute of Genetics (NIG)
Dr. Asao Fujiyama serves as the director of the Joint Support-Center
for Data Science Research (DS) at the Research Organization of Information and Systems (ROIS) and as a specially-appointed professor
for the National Institute of Genetics (NIG). He holds a Ph.D. in sciencefrom Nagoya University. He worked at the Faculty of Medicine at Osaka University, the Institute for Molecular and Cellular Biology at Osaka
University, Cold Spring Harbor Laboratory and the University of Chicago before becoming assistant professor at the NIG in 1989, professor
at the National Institute of Informatics in 2002 and professor at the
NIG in 2008. He joined the DS as its director in 2016. He specializes ingenomic bioscience and is known for comparative analysis of humanand chimpanzee genomes.

© Primate Research Institute, Kyoto University

Ayumu is an 18-year-old chimpanzee living in Japan who,much like his mother, works hard on any task given to him
until he gets it done. He also has handsome looks that camefrom his father. But how do these traits relate to his genetic
makeup? Which genes did Ayumu inherit from his father,and which ones from his mother? And how likely is it that
Ayumu has mutate genes that weren’t present in his ancestors or even in his grandparents?
A group of Japanese scientists now have answers to all thequestions. In a press conference at Kyoto University on Oct.
30, 2017, Dr. Tetsuro Matsuzawa from the Kyoto University
Institute for Advanced Study(KUIAS), Dr. Asao Fujiyama
from the National Institute of Genetics (NIG) and Dr. Yasuhiro Go, associate professor for the Center for Novel Science
Initiatives at the National Institutes of Natural Sciences(NINS), announced that their research team had completed
an “ultra-deep” whole genome sequencing study on Ayumu
and his parents. The chimpanzee trio live at the Primate
Research Institute of Kyoto University in Inuyama City in
Aichi prefecture. The ultra-deep study, which analyzed an
unprecedented number of DNA bases in the primate’s study
history, revealed each offspring of the chimpanzee has estimated 1.48 newly-formed mutations per 100 million bases ofDNA.
Dr. Matsuzawa and Dr. Fujiyama will explain what theresults of the study on the chimpanzee family at Kyoto University’s Primate Research Institute say about chimpanzees’
closest cousin, the human, and the future of genome
studies.

Genomes, the Driver of Behaviors
The Primate Research Institute of Kyoto University, a worldly renowned primate research organization, is home to an
extended chimpanzee family spanning three generations.
Prof. Matsuzawa has been studying “the mind of the chimpanzee” since 1977 when he met Ai, a girl chimpanzee who
had moved to the center earlier that year. Ai was estimated tobe 23 years old when she gave birth to Ayumu on April 24,
2000. In his book, “Okāsan-ni natta Ai” (“Ai who became amom”), Prof. Matsuzawa described the details of the labor,
including how Ayumu’s dangling limbs had researchers concerned about his health at first.

Prof. Tetsuro Matsuzawa (right) and Prof. Asao Fujiyama during an event at Kyoto
University

63

“We have been conducting research on the learning

behaviors of chimpanzees to find out how knowledge andexperience accumulate to make their minds grow andchange,” Prof. Matsuzawa said. “If I can use the iceberg met-aphor, the tip is the behaviors, and the foundation that wecannot see under the sea is the genomes. Once we understand exactly how genes work, then the whole picture of theiceberg will begin to emerge more clearly,” he said. “Forexample, we already know that aggressive behaviors in chimpanzees have to do with a male hormone called Androgen
and which genes function as Androgen receptors. This leads
to our next question about which genes can help suppress
aggressiveness and so on, and we can continue digging down
into the matter this way.”

Going Back 6 Million Years to Fill the Genetic Gaps
Humans and chimpanzees share so much of their DNA. This
made Prof. Fujiyama decide to delve into the chimpanzee’s
genome in the early 2000s while participating in a humangenome project.
“By comparing the human genome to that of the chimpanzee that’s phylogenetically closest to us, we can figure out thegenes that played the crucial roles in separating the two species from the common ancestor. And because most of theviruses that cause infections for chimpanzees also affecthumans and vice versa, researchers are hopeful that studying
chimpanzee genomes will help them develop effective treat-64

ments for human diseases,” Prof. Fujiyama said.

Prof. Fujiyama and fellow researchers have already con-ducted some ground-breaking research in the field, identify-

ing mirroring relationships between the chimpanzee’s 22
chromosomes and the human’s 21 chromosomes and studying their commonalities and differences.
“Following our study in 2004, we concluded the humanand the chimpanzee phylogenetically parted ways about 6
million years ago. We simulated the evolution on the premisethat the generation time is 20 years and computed the rate ofgenetic mutation,” Prof. Fujiyama said.
Prof. Matsuzawa won’t forget the day Prof. Fujiyama visited him in Inuyama City to collaborate on that study in 2004.
“Ninety-nine out of 100 people who visit the Primate
Research Institute look at the chimpanzees here and ask
which one Ai is. Only Prof. Fujiyama asked, ‘Which one isGon?’” Prof. Matsuzawa said, laughing. Gon is a root node of
the Institute’s chimpanzee pedigree tree. “Prof. Fujiyama’squestion showed that back in 2004, he already knew how to
go about the chimpanzee genome study,” Prof. Matsuzawa
said.
And, that’s how the ultra-deep whole genome sequencingof Ai, Ayumu and his father, Akira, began.

Taking the Guesswork out of Genomic Analysis
The whole genome sequencing on Ayumu and his parents
was different from any genome studies conducted in the past
on two fronts. First, the team ran a “personal genomics”
study on the chimpanzee nuclear family, treating the parents-offspring trio as a set. Secondly, the team used the socalled next-generation sequencer to analyze 575, 463, and468 giga bases of DNA–unprecedented numbers of reads for
personal genomic sequencing of any mammalian species–inorder to make the analysis highly accurate. Each chimpanzee
has about 30 giga bases of DNA. The study also considered
the actual generation time instead of an estimate used in the
traditional phylogenetic research.
“From this research, we were able to determine the rate ofgermline newly formed mutations to be 1.48 mutations per
100 million bases,” said Prof. Go. “This is higher than thereported rate of 0.96 to 1.2 mutations per 100 million bases
for humans. We also discovered 75 percent of the newly
formed mutations for the chimpanzee originated with thepaternal side (sperm).”
In other words, the team was able to pinpoint the types,
the extent and frequency of errors in the transmission ofgenetic information from parents to an offspring.
“If we can go beyond the parents-and-son trio to cover
more members of the second generation or even the third
generation in the analysis, we will have a greater understanding of the inner workings of the chimpanzee’s genome,”
Prof. Fujiyama said.

Prof. Matsuzawa believes the lack of research on the mind of the horse has to dowith ‘Clever Hans,’ a horse that became famous for its claimed ability to perform
math around the turn of the 20th Century,” Prof. Matsuzawa said. “A researcher
eventually proved that it was all tricks. Little study has since been conducted tounderstand how the mind of the horse works, even though people have continuously used the ability of horses to take directions for horse races and otherpurposes.”interested in understanding the mind of the horse in connection with the genome at the bottom of the “iceberg.” He plans
to conduct research both in laboratory settings and in thewild just as he’s done for his chimpanzee studies.
“The horse is a beloved animal, yet no one is studying themind of the horse. It’s like a blind spot in our field,” Prof. Matsuzawa said.
He pointed out that studying mammals helps researchersbetter understand the primate and that the genome is the
key to the big picture.
“Following the extinction of dinosaurs 66 million years
ago, mammals adapted to the new environment and rapidly
proliferated. Mammals are believed to have all come from asmall, nocturnal creature resembling a mouse. This explains
why many mammals are terrestrial,” Prof. Matsuzawa said.
“In the meantime, the primate chose to live in the tree. As
they began climbing trees, their four legs became four hands.
Take a look at the four limbs of chimpanzees or Japanesemacaques or whatever, and you will see they are handshaped. But the human is unique in that they decided toreturn to the ground from trees. We got our feet when we
became humans,” he said. “When you think these things, youstart to see the history of evolution. And, the genome isbehind all of it.”

Tracing the Mammals’ Footsteps
For Prof. Matsuzawa, the next step in his research is to target
non-primate mammals as study subjects. He is particularly

Released on: July 10, 2018 (The Japanese version released on Sept. 11, 2017)

65

Changing
the World
with
Data Science66

68 013
		 Reinventing the Process		 of Making Things
		 Ryo Yoshida and Ichiro Hasuo
74 014
		 Data Science–		 the Humanities’ New Tool
		 Naruya Saitou
		 and Asanobu Kitamoto
80 015
		 Tracing the Cosmic History
		 Back to the Big Bang		 Naoki Yoshida, Shiro Ikeda
		 and Mikio Morii
84 016

		 Data Intelligence for Sport:
		 Put Some Smarts in Your Cheers
		 Yoshiyasu Tamura, Fumitake Sakaori
		 and Akinobu Takeuchi
88 017

		 Changing Patients’ Lives with
		 Data Science
		 Shin’ichi Satoh, Yoichi M. Ito		 and Hisashi Noma
94 018
		 What’s on the Horizon in the		 Changing World of Big Data?
		 Masaru Kitsuregawa
		 and Tomoyuki Higuchi

67

Science Report

013 Changing the World with Data Science 01

Reinventing the Processof Making Things

Ask the Experts: Ryo Yoshida
Professor of The Institute of
Statistical Mathematics (ISM)

Ask the Experts: Ichiro Hasuo
Associate Professor of
National Institute of Informatics (NII)

Dr. Ryo Yoshida, professor for Department of Data Science at the Institute of Statistical Mathematics (ISM), has served as the director of theInstitute’s Data Science Center for Creative Design and Manufacturing
since the center’s opening in July 2017. After receiving his doctorate
degree in Statistical Mathematics from the Graduate University for
Advanced Studies in 2004, he worked as a Project Assistant Professor
for the Human Genome Center at Institute of Medical Science, the University of Tokyo–a position he has maintained after joining the ISM in2007. In addition, he serves as a specially appointed researcher for
National Institute for Materials Science. Dr. Yoshida has the experience of using his expertise in data science for research work in bothbiology and materials science. He plays leadership roles in several
cutting-edge research projects, including the Japan Science andTechnology Agency (JST)’s the “Material Research by Information
Integration” initiative.

Dr. Ichiro Hasuo, associate professor for the National Institute of Informatics (NII)’s Information Systems Architecture Science Research
Division, has served as the director of the Institute’s new Global
Research Center for System Design and Mathematics since July 2017.
With his expertise in theoretical computer science, he is particularlyinterested in such research topics as system verification, programming language theory, information processing, and mathematicalstructures in information science. He is a 2002 graduate of the University of Tokyo and received his doctorate in computer science from
Radboud University Nijmegen in the Netherlands. Before joining the
NII in April 2017, he served as associate professor for the Graduate
School of Information Science and Technology at the University ofTokyo as well as visiting associate professor for the Research Institute for Mathematical Science at Kyoto University.

68Decades after “Made in Japan” became synonymous withhigh quality, the country is pushing for scientific breakthroughs that would help industries redefine excellence inmanufacturing. The initiative focuses on leveraging data science and artificial intelligence (AI) for manufacturing, following in the footsteps of the U.S., Germany and many othernations in Europe and Asia, where similar movements havealready been underway. In hopes of galvanizing ongoing
efforts in Japan, the Research Organization of Informationand Systems (ROIS) established two centers last year within
the existing institutes under the ROIS’s umbrella–the Data
Science Center for Creative Design and Manufacturing,launched at the Institute of Statistical Mathematics, and the
Global Research Center for System Design and Mathematics, launched at the National Institute of Informatics. So,
what’s the vision of Japanese leaders in this scientific frontier? And how could they take manufacturing to a whole newheight? The scholars who lead the two new research centerswill spell it out for us as they explain about the projects thatthey lead.

things do or don’t work out in the ways hypothesized, thatwould shed that much more lights on the complex relationships between material chemistry and physics. Researchers
would use the knowledge to conduct additional experiments
and inch toward discovering ground-breaking materials.
This long-standing empirical approach to inventing materials is becoming a thing of the past, now that materials informatics allows researchers to make discoveries without compiling direct evidence to get there, according to Prof. Ryo
Yoshida of the Institute of Statistical Mathematics (ISM).
Materials informatics refers to a field of study that har-Materials Informatics: Trading Test Tubes for AI
One of the study fields that are increasingly attracting theattention of both the academic and manufacturing communities is materials informatics. Public interest in the fieldgrew following the 2011 launching of the Materials Genome
Informatics Initiative by the U.S. government under the leadership of the former president Obama.
Researchers used to go through countless trials and errors
in wet labs to develop new materials for products. WhenThe graph shows newly discovered materials for photovoltaic cells. The squareinside the graph, in which few dots exist, indicates the area where researchers aretargeting.

69

Prof. Yoshida is also interested in designing of spaces conducive to industry-academia collaborations. While working with companies on projects, Prof. Yoshida
helps them build mechanisms for recruiting talented data scientists.

nesses the power of big data and AI to rapidly discover novel
materials that could be created. Before conducting direct
experiments and physically measuring values, researchers
would put existing big data as well as interpolative data
derived from it through algorithms and let AI identify patterns in the data. AI uses the patterns to predict how proposed materials would behave in the real world and/or what
properties a material need to be made of to offer desired
characteristics and features.
This drastically accelerates the speed of material innovations. It also allows researchers to create something that they
never imagined or have considered as far-fetched, said Prof.
Yoshida, who serves as the director of the ISM’s Data Science
Center for Creative Design and Manufacturing.
For example, the Power conversion efficiency of photovoltaic cells is currently limited to 11 percent maximum, Prof.
Yoshida said, as he showed a graph with dots representing theefficiency of cells made of different materials.
“The vertical line in the middle is the maximum efficiency
we can attain with the existing scientific knowledge andmaterials. The area to the right is the ‘uncharted territory.’
Our job is to find materials that fall in this territory,” Prof.
Yoshida said. “We want materials with features and characteristics that enable cells to achieve far more than 11 percent
of efficiency,” he said.
“Over many decades, material science gradually advanced,
pushing the middle line in the graph to the right. Now, wehave the opportunity to expand this dotted region at exponential speeds by taking advantage of the cutting-edge data
science technology. This will definitely be a boon to scientificand industrial advancement.”
Prof. Yoshida pointed out that data-gathering and identification of patterns with the use of machines is the essence ofdata science.

70“In data science, we, the researchers don’t have to come up
with any theories. We just need to have the machines analyze
data to recognize hidden patterns and identify the theory
behind them with inverse problem methods. The computeruses the theory to build a virtual material with the structure
and properties that are necessary to provide desired features,” Prof. Yoshida said.

Getting Mileage out of Data Science
with Extrapolative Data
Prof. Yoshida has particularly been interested in the use of
extrapolated data to enhance the machine’s ability to create avirtual material far, far outside of the current realm of possibility. That’s because the computer needs more data thancurrently available to theorize advanced materials on it.
“You can make only so much prediction from data. To
explore outside the ‘predictable zone,’ you would need additional data. That’s the limitation of data science,” Prof. Yoshida said.
“Data science has never played crucial roles in any Novel
Prize-level, ground-breaking scientific discoveries. Technological advancements have always come from direct experimentations and theories. When I think about what contributed to my research successes thus far, data science accounts
for 5 to 10 percent of it,” Prof. Yoshida said.
He noted that data science has increasingly had artistic
applications in recent years, such as machine production ofvideography and music and designing of anime characters.
However, whatever the field you are in, the availability ofdata or the lack thereof still dictates what you can do withdata science,” Prof. Yoshida said. “Therefore, if we wanted amachine that can make advanced predictions–those that go
far beyond the predictions based on the knowledge and expe-

riences humans currently have, then the machine needs tomissing.”

New Era of Quality Assurance Begins
with Self-Driving Carsan algorithm called SPACIER.

researchers is trailblazing to advance manufacturing is

be capable of extrapolating data to make up for what’sThis idea inspired Prof. Yoshida’s research team to develop

Another area in information science that a group of ROIS“SPACIER sets up a virtual materials research laboratory

called “category theory.” This effort stems from the fact that

inside a computer. It designs experiments and conducts simulations in the virtual lab to extrapolate data,” Prof. Yoshidasaid. “The machine solves inverse problem to enhance its
predictability, so it can find materials beyond the existing‘predictable zone.’ You can repeat this extrapolation process
through the algorithm to gradually push the limit.”
Theoretically, he said, it’s possible to keep using the algorithm to generate more and more data, further expanding
data distributions. It’s also possible to modify SPACIER for
general applications in other fields, including such a purpose
as structural designing of industrial products, Prof. Yoshida
said.

Collaborations and Blending Tools Key
to Reaching the Goal
While combinations of algorithm, AI and extrapolative data
may sound like a magic wand for inventing things, Prof.
Yoshida cautions that there’s still a way to go before practicalapplications become routine. Don’t get too excited aboutmachines like AlphaGo Zero, the robot that gets better atplaying an Asian board game known as Go by learning fromits own actions to outdo itself.
“We’ve only begun making ‘super creative’ machines thatinternally generate data to serve its purpose. There are manytechnological challenges to overcome to perfect the mechanisms,” he said. “At least for now, experiments in virtual labs
alone cannot suffice to meet all industrial design and development needs. It’s important that we create formulae forturning ideas into products by blending physical experiments, theories, computational research and algorithms.”
Prof. Yoshida’s mid-range vision calls for robust machinelearning with the use of data and theories from direct experiments. A machine would feed on existing data and take backwhat’s come out of the algorithm after theories are applied toit. But, how would he convince the manufacturing industry
to adopt the new methodology?
“Show. Don’t tell,” Prof. Yoshida said. “We want to send themessage out that the methodology does work and that data
science can be the most powerful ally in innovating products
under the right partnerships. I intend to bring this message
to those on the front line of industrial development researchover the next few years.”
As part of this initiative, the Data Science Center for Creative Design and Manufacturing plans to collaborate with six
corporations this year for data scientists training. The center
hopes to work with many more companies in the years tocome, Prof. Yoshida said.

most machines today are computerized, necessitating manufacturers to reconsider how to carry out quality assurance,
according to Prof. Ichiro Hasuo of the National Institute ofInformatics (NII)’s Information Systems Architecture Science Research Division.
“Just think about self-driving automobiles,” said Prof.
Hasuo, who also serves as the director of the NII’s Institute’s
new Global Research Center for System Design and Mathematics. “Even the most experienced auto makers’ considerable know-how can’t be of enough help when it comes to performing quality control and assurance in this nascent field of
self-driving automobile technology. Manufacturers areunderstandably unsure about how to navigate these uncharted waters. Academia are equally confused about which discipline’s responsibility it should be to address this issue.”That’s where Japan Science and Technology Agency(JST)’s Exploratory Research for Advanced Technology
Metamathematics for Systems Design Project (ERATOMMSD project) comes in. Directed by Prof. Hasuo, the ERATO MMSD project aims to expand the formal methods–
mathematical methods to structure software systems–with
the use of category theory, so formal methods can be applied
to cyber-physical systems (CPS) as well as physical products.
The project places a particular focus on automobiles.
“It began at the right timing,” Prof. Hasuo said of the ERATO MMSD project, which was launched in October 2016 andis now housed at the Institute’s new Global Research Center
for System Design and Mathematics, for which he serves as
the director.
“Industrial equipment used to be kinetic machines, andtheir stabilization systems were based on the control theory.
But nowadays, nearly every machine has a computerized
control system installed in it,” Prof. Hasuo said. “Generally,71the safety of their products.

“Category theory comes from algebra. It’s a mathematicallanguage used for structural description,” said Prof. Hasuo, acategory theory specialist. “It focuses on the relations among

objects and expresses it in an abstract form. It differs from‘graph theory,’ which also describes the relations among

simpler machines are linear systems, meaning their response
to outside forces is straightforward and predictable. If you
give it twice as much force, the output would also be twice as
much. Computerized control systems for automobiles andother large, complex systems don’t act that way.”
So, how do they act? The ERATO MMSD Project willanswer the question, Prof. Hasuo said.

Category Theory for New QA Methods
The ERATO MMSD project couples logic with category theory to develop a method that manufacturers can use to assure

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objects, in that category theory doesn’t generalize what’spresent; it abstracts the logics behind what’s present. In other words, category theory is a meta language.”
Category theory is an integral part of mathematical structuralism. The theory matured at the same time as structural
anthropology grew out of the study of algebraic structures inFrance during the 1940s. This historical fact may make one
wonder if and how category theory and structural anthropology–which owes its development to Claude Lévi-Strauss–
may be related to one another.
“Claude Lévi-Strauss (French anthropologist whose work
helped the development of structuralism) made many contributions to the academic world, but I understand one of themwas his idea that all kinds of communities–or mass bodies ofthings–have immutable structures supporting them. I
believe the same is true for masses of data. Whether it’s a traditional information system–which is the focus of the data
science–or an information system involving physics data of
industrial machines, they both deal with collections of information. So, they’ve got to share some things in common froman algebraic perspective,” Prof. Hasuo said.

JST ERATO Metamathematics for Systems Design Project is based out of a downtown Tokyo building. A group responsible for expansion of formal methods for general usage and a group responsible for applying the methods for practical purposes converge here daily and have lively discussions.

Mathematic Processes as Guide for Exploring
Unfamiliar Territory
Prof. Hasuo’s is not the first researcher to suggest the use offormal methods as verification techniques for physical information systems. In fact, there have been many attempts
made around the world to do just that. “Those attempts havenot necessarily been unsuccessful because it is not clear how
to make formal methods usable for cyber-physical information systems,” Prof. Hasuo said. He wants to use category theory to create the missing link, and that makes his idea andproject exceptionally cutting-edge.
Formal methods–which are used to verify software does its
job in the way it’s supposed to–are regarded as reliable quality-assurance techniques because they are mathematical, andtherefore, leave little room for ambiguity and error. For manufacturers, minor inaccuracy could mean a disaster. Hairsplitting margins of error have indeed caused problems, suchas rocket launching problems and arithmetic glitches incomputers. Formal methods are useful for ensuring software
products won’t get stuck in an infinite loop nor present any
vulnerability. So, it could change the ways industries operatearound the world if the ERATO MMSD project succeeds.
“Mathematical processes show you the ropes to guide you
through the unknown territory,” Prof. Hasuo said. “We aregoing to use category theory to expand formal methods andcreate templates for defining problems in a mathematic language. We will gradually flesh them out and keep the tem-plates in our ‘tool box,’ if you will, so we can take out suitableone, depending on what problem we need to solve, and workwith manufacturing engineers to provide evidence for whatever they need to verify or prove. The ever-advancing AI andmachine-learning technology can be useful for this process,as well,” he said. “When this is put to use, this will provide
additional support for the current quality-assurance process
centering around engineers’ judgment calls based on theiryears of experience and knowledge. This should drasticallyreduce the time required for verification processes.”Prof. Hasuo and his team want to see five cases of manufacturing applications of this verification method before the
ERATO MMSD project completes in 5 ½ years. The team isalready discussing possible applications with several companies, according to Prof. Hasuo.

Released on: August 10, 2018
(The Japanese version released on January 10, 2018)73

Science Report

014 Changing the World with Data Science 02

Data Science–
the Humanities’ New Tool

Ask the Experts: Naruya Saitou
Professor of
National Institute of Genetics (NIG)
Prof. Saitou serves as professor of genetics for the Graduate School of
Advanced Studies and as professor of biology at the University ofTokyo. He has extensive experience in research on species-specificevolutionarily conserved characteristics based on large-scale genomic data comparisons. His 1987 paper with Dr. Masatoshi Nei, his Ph.D.
supervisor, which proposed the “neighbor-joining method” for reconstructing phylogenetic trees through the use of evolutionary distancedata, has thus far been cited more than 53,000 times. He is the authorof “Introduction to Evolutionary Genomics, Second Edition (2018,
Springer)”, and many other books.

74

Ask the Experts: Asanobu Kitamoto
Director of Center for Open Data in the Humanities(CODH), Research Organization of Information and
Systems(ROIS)
Prof. Kitamoto, the director of the Center for Open Data in the Humanities at the Research Organization of Information and Systems, serves
as associate professor for the Digital Content and Media Sciences
research division of the National Institute of Informatics and as associate professor of informatics at the Graduate School of Advanced
Studies. He has a bachelor’s and doctoral degrees in engineeringfrom the University of Tokyo. His research work centers around image
data analysis and application of data-driven science in various disciplines from the humanities to earth science to disaster reduction. His
project was among Jury’s Selections at the 2007 Japan Media Art
Festival organized by the Agency for Cultural Affairs and the Information Processing Society of Japan’s Yamashita SIG Research Award.
Prof. Kitamoto is interested in transdisciplinary research that helps
promote open science.

History teaches us something new whenever we revisit it, but
researchers are finding out that we can learn so much morefrom our past by bringing data science into historical studies.
From projects that combine genomics and archeology to digitization of cultural heritage, a wide range of experimentsthat merge the humanities and computer science are bearing
fruit, shedding light on previously unknown facts. This isallowing researchers to dig deeper into their subject matterto shed light on previously hidden facts–so much so that historians, for example, are now able to add new pages to history books or even rewrite parts of them. Two data science
experts involved in this growing research approach explain
how this is helping us develop new bodies of knowledge andwhere it’s all headed.

Upside of Drilling into Ancient Artifacts
When and how did the ancestors of the modern Japanesearrive the archipelago from the Asian continent?
It’s a question that fascinates the people of this island
country in Far East. A piece of enlightenment came in 2016
when Prof. Naruya Saitou of the National Institute of Genetics (NIG) and his research team analyzed the genome ofhuman bones that had been excavated from the Sangaji shellmound in Fukushima, Japan, and found that the Jomon people–who lived in the Japanese Archipelago between 14,000
and 900 BC–were genetically very different from Chineseand Southeast Asians. The team made the discovery upon
visiting the University of Tokyo Museum where the bones
were stored and drilling a hole into a back tooth of both amale and female skull to take samples.

Then in 2017, the team concluded that their Japanese
ancestors from the continent arrived in three separate timeframes instead of two, which had been the popular belief.
“As we compared the genome sequences of people who livein various locations of the Japanese Archipelago (Yaponesia),
we found small differences among them.When we looked atwhere these groups were located, we saw a geographical pattern. And that looked different from the pattern of the Jomon
population distribution expected under the two-step migration model,” Prof. Saitou said. “As you can see, humanities
information is critical to advancing the research on human
evolution. We have countless pieces of archeological artifacts
painstakingly unearthed from across the country over many,
many decades. Our job is to mine these materials for data. In
other words, museums are our ‘field’ of research,” Prof.
Saitou said.
He pointed out that such “genomic excavation” is happening more and more across Japan.
“Genomics is finally catching up to the humanities. As wecontinue with the large-scale genomic project that studies
the Jomon people as well as modern-day Japanese frommany different areas of the country, we will be able to gain
more insights into the revolutionary history,” he said.

Data at the Crossroad of the Humanities andScience
Bringing together the humanities and data science–the twoseemingly opposite ends of the academic spectrum–for theadvancement of both is an emerging trend. But, Prof. Saitou
said a 19th Century scientist’s concept of how the universe

75

works to is the most useful for explaining why the new
approach makes perfect sense. What Prof. Saitou is referring
is a Venn diagram that Japanese natural historian and folklorist, Kumagusu Minakata, drew in his letter to a priest. Oneof the two circles in Minakata’s diagram contains a character
that signifies “the mind,” with “matter” encircled in the other. The overlapped area represents “things.”“There is the human mind, or the subjective world, on one
side and physical matters and phenomena, or the objective
world on the other. Both have ‘things’ in common, and that’s
what we obtain through excavation, such as historical data
and archives,” Prof. Saitou said.
“People talk about how far biology has come, but there isso much more that we don’t know,” said Prof. Saitou, whoworks to advance “evolutionary genomics,” a field that studies how the genome has changed over the course ofevolution.
“An interesting thing about genomics is that the ‘matter’and ‘things’ mirror each other. While adenine (A), cytosine(C), guanine (G), and thymine (T) are genetic information, or‘thing,’ each of them also corresponds to a physical, objective‘matter.’ This closeness between matter and things is a wonderful thing,” Prof. Saitou said.
“Our goal is to find out how a natural phenomenon called
evolution transpired over time by first looking at the genomic changes. It’s important for us to use data as the language todescribe what happened in the world that surrounds thehuman and how it changed. This enables us to prove or disprove history, and I believe that’s what data science is allabout,” he said.

Why Data Speaks Against Darwinism
In the research field of biological revolution, Prof. Saitou
said, tracking changes in genomic data has already allowed76

scientists to disprove one of the most widely held ideas: theDarwin theory.
Charles Darwin believed that every species’ survival is dictated by its ability to adapt to the environment throughgenetic mutations. In other words, genes are continuallyreplaced by those that can better handle environmental challenges, allowing species to produce more offspring and carryforward the mutations. Prof. Saitou calls this theory of natural selection an “illusion,” however.
“The idea that all biological organisms are adjusted to theenvironment is a fantasy. If better genes outlive worse ones,
then no species should die off. But in reality, we see species go
extinct all the time. Just this fact itself disproves the natural
selection process,” Prof. Saitou said.
He said a close look at genomic data further provides evidence that the theory of natural selection isn’t factual.
“Even when mutations occur in a species’ DNA to better
handle the environment, the effects eventually wear off, andthose mutated genes will play no more or less part than othergenes in the species’ survival. In the end, maintaining the status quo is all that the genes do. We call it ‘purifying selection’as opposed to ‘natural selection,’” Prof. Saitou said.
In 1968, Japanese biologist Motoo Kimura proposed the“neutral theory of molecular evolution,” stating that the
reproductive rates of organisms remain unchanged, or “neutral,” even if nucleotide sequences become altered as theresult of mutations. This remains the most trusted theory in
the field of evolution studies, Prof. Saitou said.
“Today, we know most genes have gradually evolved fromthe originals as such neutral mutations repeatedly occurred
over long periods of time,” Prof. Saitou said.

Data for Reconstructing the Edo Period
On another front of transdisciplinary data science is the academic community’s effort to pull together all types of historical archives to build big data and analyze it to connect all thedots. The Center for Open Data in the Humanities (CODH) at
the Research Organization of Information and Systems(ROIS) supports this movement by offering datasets, software and other tools to innovate humanities research. In
CODH’s March 2018 seminar, “Historical Big Data - Challenges in Transforming Historical Documents to Structured
Data for the Integrated Analysis of Records in the Past -,” forexample, participants from various disciplines learned how
to integrate and analyze seismologic, climatologic and astronomical data obtained from historical records.
“People didn’t have Twitter in old days. Instead of postingon social media, they wrote down in their documents anddiaries what they saw and heard. Historical manuscripts andold records are a treasure trove of such everyday informationfrom the past,” said CODH Director Asanobu Kitamoto, who
also serves as associate professor for the Digital Content andMedia Sciences research division of the National Institute ofInformatics and as associate professor of informatics at theGraduate School of Advanced Studies.
“For example, we can find weather information in a
300-year-old diary that a family in the western part of Tokyo
has kept. In Nagano, people have maintained official recordsof “Omiwatari” for the past 600 years, which is a religious
celebration of the appearance of an ice ridge formed along a
crack on a frozen Suwa Lake. Shrines in Kyoto have also longrecorded the day cherry flowers blossomed every spring,”
Prof. Kitamoto said.
He said records from the Edo period are particularly abundant, which is the reason he is focusing his research on that
period. Researchers can use such records to reconstruct past

climate conditions, put together historical disaster information and even analyze correlations between natural eventsand social, political or economic events, including market
fluctuations in the modern era, and groundwater management. The CODH works to foster the research community ofdigital humanities by supplying its technological expertiseand research gathering.
“Reconstruction of history through comprehensive analysis of historical records has been a growing movement worldwide. The Venice Time Machine, a project to create digitalarchives of records covering Venice’s 1000-year history toreconstruct the city from the ancient days, is an example,”
Prof. Kitamoto said. “But research teams engaged in these
digital humanities projects are scattered across the globe. We
are hoping to establish a system for bringing together the
research results, digitizing them and making them accessible to all researchers,” Prof. Kitamoto said.

Open Science Through Standardization for Visual
Art Curation
The CODH is also an active participant in the International
Image Interoperability Framework, or IIIF, which is an international initiative to develop standard technology and systems for image delivery. IIIF aims to make digital images–
those that belong to museums, libraries and other institutions and individuals from around the world–accessible toresearchers and the general public everywhere. The Nation-77

al Diet Library of Japan, the British Library, the National
Library of France and “Europeana,” an online repository ofdigitized items, as well as Oxford University and other universities, use IIIF to provide access to more than 350 million
digital images. As part of its effort to help build a IIIF community in Japan, the CODH has developed an application
called “IIIF Curation Viewer,” which allows users to view IIIF
images on a global scale, including the National Institute ofJapanese Literature’s old books on the CODH’s website.
“IIIF Curation Viewer lets you cut out the parts of images
that interest you, such as people’s faces, and curate them justlike making a scrapbook. To do something like this, we used
to visit museums, take photos of the images or photocopy
them and cut and paste the parts we want with scissors andglue. Now that we have this Viewer, we can do the same thing
hundreds or thousands of times faster,” Prof. Kitamoto said.
As curation and analysis of images becomes easier,researchers are tapping more into visual resources to makediscoveries.
“We curated facial images from our collection as an experiment. Comparison of these images revealed that a face
appears in one book is painted very similarly to another facethat appears in a different book. Picture books from the Edo
period are comprised of paintings and calligraphy, and weknow people used to ask art studios that specialize in either
painting or calligraphy to get each part done separately. It is
possible that there were templates that art studios were78

The CODH also offers a publicly assessible collection of the images of charactersfrom 15 old books that belong to the National Institute of Japanese Literature. The
collection contains 403,242 characters representing 3,999 different cursive
characters. “Ruby characters (annotations for pronunciations) are particularly achallenge for AI in recognizing characters,” Prof. Kitamoto said.

using to paint faces–which would be somewhat similar to themethod that today’s manga artists use,” Prof. Kitamoto said.
He noted that everyone in the research community significantly benefits from open access to research data, as it allows
them to review each other’s results and share their interpretations. To make this possible, data needs to be aggregatedfirst, and a part of the research workflow standardized.
“Data science can contribute to digital humanities, but
that’s not enough. Accelerating innovation in digital humanities through data science is our mission,” Prof. Kitamoto
said. He wants to provide scholars’ a tool to share with others
the knowledge and materials that are locked in their brains.
“Anyone can curate images that they find on any IIIF-enabledwebsites–that’s my vision for the participatory citizen sciencethat we are trying to promote,” Prof. Kitamoto said.

Discoveries at the Crossroad of the Humanities
and Computer Science
One of the COHD’s curation series that has drawn the mostpublic participation is the Dataset of Edo Cooking Recipes.
The COHD launched the series in 2017 with a collection ofegg recipes from a cookbook “Manbo Ryori Himitsubako”

Prof. Kitamoto at the National Institute of Informatics (Chiyoda-ku, Tokyo) where
he serves as associate professor

published in 1795. The egg recipes have even made their way
onto a popular online recipe service, Cookpad, to reach thegeneral public across Japan.
This experience was a lesson to learn that, just make data
accessible is not enough to make the full use of it, according
to Prof. Kitamoto.
“What’s interesting about humanities data is that we canstudy connection to the history and culture behind the data. I
hope to use humanities data to not only advance computerscience but also gain new understanding in the humanities,”
Prof. Kitamoto said. “Computer scientists need to go beyond
the research practice of putting someone’s data into a blackbox and get the result. When the same cutting-edge analysis
tools become accessible to non-computer scientists, our fieldcannot grow further. We have to think about better ways toaccess new data, what kind of new knowledge we could gainfrom data, and those sorts of things. In other words, I believethat the future of our field depends on how we try to effectively and creatively handle data,” Prof. Kitamoto said.

Released on: September 26, 2018
(The Japanese version released on February 10, 2018)

79Science Report

015 Changing the World with Data Science 03

Tracing the Cosmic History
Back to the Big Bang

Ask the Experts: Shiro Ikeda
Professor of The Institute of
Statistical Mathematics (ISM)
Dr. Shiro Ikeda is a professor at the Institute of Statistical Mathematics. His research focuses include separation of acoustic signals withthe use of “independent component analysis,” a multivariate statistical analysis technique, as well as the development of processing andanalysis techniques for noisy data. He also works to find out methods
to improve astronomical and physical measurement through sparsemodelling based on the premise that estimated target signals containmany zeros. He received his doctorate degree in engineering from the
University of Tokyo in 1996.

Ask the Experts: Naoki Yoshida
Professor of Department of Physics,
University of Tokyo
Dr. Naoki Yoshida is a cosmologist and astrophysicist working to solve
mysteries surrounding dark matter and black holes. He has served as
specially appointed professor at Kavli Institute for Physics and Mathematics of the Universe at the University of Tokyo and as professor of
astrophysics at the University of Tokyo since 2014 and 2012 respectively. He received his bachelor of science in aerospace engineeringand doctorate degree in science from the University of Munich andhas worked at Harvard University’s Department of Astronomy and at
Nagoya University in Japan.

Ask the Experts: Mikio Morii
Project Assistant Professor of
The Institute of Statistical Mathematics (ISM)
Dr. Mikio Morii serves as project assistant professor at the Institute of
Statistical Mathematics. He specializes in observational astronomy.

80Type Ia supernovae identified through analysis. They are compiled in data basealong with the information on their luminary levels and transformations.

Modern cosmology tells us it’s been 13.8 billion years since
the universe emerged. Following the Big Bang, the hot anddense universe kept cooling down through continuous
expansion. About 380,000 years later, the universe became
transparent to radiation, enabling us to directly observe theuniverse. Approximately 100 million years after the Big
Bang, the first generation of stars were born, and they illuminated the universe. Cosmology, the study of the origin andevolution of the universe, has risen from serendipitous discoveries that people made while gazing into space andabsorbing all the information they could see, said Prof. Naoki
Yoshida of Kavli Institute for the Physics and Mathematics of
the Universe at the University of Tokyo. “Cosmology, from its
beginning, has always been a frontier of data science,” hesaid. Researchers today are trying to build on this cosmology-data science connection by taking advantage of the ability
to collect literally astronomical amounts of observational
data. Will the technology help elucidate how the universe
came into existence? Three experts involved in such transdisciplinary research efforts will answer the question andexplain what is happening on the cutting edge of cosmology
and data science.

Key to Finding Out How the Universe Appeared
Prof. Naoki Yoshida is involved in a 5-year space observation
project to use an advanced camera newly installed in the

Subaru telescope to collect and analyze imaging data, whichis expected to total as much as 1 petabyte in data size.
“A single image typically has several thousand galaxies
captured in it. They may look like a cloud of fog at first, but
the resolution is so high that you can zoom in far enough to
identify individual stars. You can use the camera to capture
what’s happening in a vast area of space,” Prof. Yoshida said.
“People often think the universe is a calm place and looks
pretty much the same at all times. But when you compare animage you just took from the one from the day before, youwill know just how much has changed in 24 hours. In our daily analysis of the data collected with the Subaru telescope, wenormally find evidence for explosions of about 100 stars anight,” he said. “You can, of course, zoom into each supernova and see the details with your own eyes, but there are just
too many of them to check on manually. So, we use the computer to gauge differential values between images to understand the changes occurring in the universe.”
What’s behind Prof. Yoshida’s focus on supernova explosions is Saul Perlmutter, a 2011 Nobel Prize winner work. In
1998, the U.C. Berkeley astrophysicist used his analysis ofType Ia supernovae in the distant universe to prove that theuniverse continues to expand today, and that the rate of
expansion is accelerating. Prof. Yoshida’s research centersaround Type Ia supernovae, which he said make up about ahalf of supernovae observed through the Subaru telescope.
“Artificial intelligence (AI) now has remarkable image

81

data on them, we put it together with the stars’ locations andspeeds to come up with a complete profile on each of them”

Prof. Ikeda said. “After making great strides with accuracy,
we are now able to identify 10 to 20 potential supernovae anight.”The Institute of Statistical Mathematics shares its building in Tachikawa City, Tokyo,
with the National Institute of Polar Research.

Prof. Ikeda’s expertise is statistical science, notcosmology.
“When you have observation data contaminated by noise,
you need to analyze data in order to understand what the
information behind the noise is. Doing that is a statistical scientist’s job,” Prof. Ikeda said. “We call it signal processing
when the data is comprised of physical signals. It often
requires multiple steps using various signal processing methods to understand the original signals. I have studied suchmethods for astronomical data, as well, including opticallight data collected with instruments like the Subaru telescope and data captured with radio telescopes. The field of
signal processing is active and growing, as the advancementof measuring instruments provides us with more opportunities to collect new kinds of data,” Prof. Ikeda said.

Mapping the Distribution of Dark Matter
analysis capabilities and can distinguish Type Ia supernovae
from other types. Prof. Shiro Ikeda of the Institute of Statistical Mathematics has been instrumental in helping us develop
a tool for identifying Type Ia,” Prof. Yoshida said.
The question is how accurately AI can distinguish Type Ia
from others, according to Prof. Shiro Ikeda of the Institute ofMathematical Statistics.
“Getting AI to accurately identify which supernovae aremost likely Type Ia is our challenge,” Prof. Ikeda said.

Pursuing High Accuracy in Identifying Type Ia
Type Ia supernovae are born when white dwarf stars with
about 1.4 solar masses explode, and they are almost equally
luminous, according to Dr. Mikio Morii of the Institute of
Statistical Mathematics (ISM).
“You can estimate Type Ia supernovae’s distances based on
how bright they appear to our sight. You can also calculate
the speeds at which they are moving away based on spectral
observations,” Dr. Morii said. “Based on the distances andspeeds of supernovae, you can estimate how fast the universeis expanding. Accelerating expansion means the distant universe is expanding faster than originally thought.”
Accurately identifying Type Ia supernovae isn’t easy,
however.
“In fact, 99 percent of what appear to be supernovae turnout to be something else,” Prof. Ikeda said. “We compare two
images taken at different times to find supernovae, but sometimes the differences aren’t as clear. We select ‘potential TypeIa’ from an image, and that typically makes up less than 1 percent of the changes we observe from the images. We would
then use a telescope to continuously observe those stars that
we think may be Type Ia. After collecting enough spectral

82

Prof. Yoshida’s 5-year observation project also focuses on
gravitational lens.
“We find a number of galaxies with distorted shapes allaround space. They are not physically distorted but just lookdistorted because of gravity that bends light-rays. The
degrees of shape distortion reveal heavy objects have large
quantities of some sort of invisible matter around them,”
Prof. Yoshida said.
This “some sort of invisible matter” is what is also known
as dark matter. It is believed that the universe is made up of 4
percent chemical elements and 22 percent dark matter, withthe remaining 74 percent being dark energy.
“We are investigating large areas of space to understandthree dimensional distributions of dark matter, which is, inessence, a map of the universe,” Prof. Yoshida said.
Scientists around the world have been studying the largescale structure of the universe since the 1980s. But, “Just figuring out dark matter distributions based on gravitational
calculations can help further theoretical models,” Prof.
Yoshida said. “We want to look at every distorted galaxy,including very subtly distorted ones, and compute thedegrees of distortion. We can then begin to think about thenature of dark matter that makes the galaxy look the way it
does through gravitational lensing. That provides basis fordeveloping new theories and models. But, in order to map
dark matter’s distributions, you need to start with observations and trace them back to causes, which is a very difficult
thing to do. This is another area in which we pull together the
ISM’s resources to support the research,” he said.

The Universe Doesn’t Show You Its True Self
Separately from the 5-year observation project, Prof. Yoshidais also working on computer simulations to show how theuniverse began and how stars and galaxies are formed.

The arcs shown around the bright stars are the examples of “distortion.” Strong
gravity bends straight light-rays to give distant galaxies distorted appearances.

“The universe is not nice enough to show you the true picture of how its components, such as galaxies, are distributed.
So, we do our best to estimate the distribution based on
observations. But you can create an accurate distribution
map of matter through computer simulations,” Prof. Yoshida
said.
“Our goal is to shed light on the evolution of the universe.
We will use whatever it takes to get to the goal, including AI
and super-computers,” he said.
Prof. Yoshida believes that it’s possible to understandwhat’s happening around the universe using the knowledge
and experiences we have on Earth.
“Saying, ‘Space is nothing like here,’ won’t get you anywhere,” he said. “Contrary to what some people might think,verified facts from our experiences on Earth provide thefoundation for understanding the universe. If you mobilize
utilize all the knowledge we have and still don’t understandsomething, then we can identify what’s missing. Once we’ve
exhausted the process and realize there’s a critical piece
missing that we don’t have, that’s when a discovery
happens.”

Prof. Naoki Yosida at his lab at the University of Tokyo’s Hongo campus

Released on: October 10, 2018
(The Japanese version released on March 12, 2018)83

Science Report

016 Changing the World with Data Science 04

Data Intelligence forSport: Put Some Smarts inYour Cheers

Ask the Experts: Yoshiyasu Tamura
Project Professor of
The Institute of Statistical Mathematics (ISM)

Ask the Experts: Fumitake Sakaori
Associate Professor of
Chuo University

Dr. Tamura serves as project professor at the Institute of Statistical
Mathematics. He works to develop statistical methods and studies
various applications of the methods. He is also known for his researchon physical random number generator, a crucial tool for simulations
conducted by the ISM. He received his Ph.D. in science from Tokyo
Institute of Technology. Dr. Tamura was appointed to his current position in 2018 after as associate professor and professor at the institutesince 1986 and 1997 respectively.

Dr. Sakaori serves as associate professor for the Department of Mathematics, Faculty of Science and Engineering, at Chuo University andas visiting associate professor at the Institute of Mathematical Statistics. He specializes in statistical modeling, computational statistics,
statistical science in sports, and statistical education. Dr. Sakaori was
appointed to his current position at Chuo University after working as
assistant professor for College of Sociology at Rikkyo University andas adjunct professor at Chuo University’s Faculty of Science andEngineering.

84

We have seen the scenario come true before: A cash-strapped
professional baseball team rises up to win its league championship, out of left field. Drastic performance improvementsof sport teams are often the results of game strategies developed by utilizing data intelligence. In baseball, “sabermetrics”–statistical analyses of players’ performances and gameactivities–began garnering attention in the 1980s. Inspiredby how the American Major League Baseball teams quickly
adapted sabermetrics as the key component of game-planstrategy, the Japan Statistical Society established the Sport
Data Subcommittee in 2009 to spearhead sport applicationsof data science in the country. Having recently celebrated theseventh anniversary of the group’s ever-growing flagshipannual event, “Sport Data Analytics Competition,” the subcommittee leaders believe data analytics are destined toserve as the fundamental tools in sport teams’ pursuit of victory. Prof. Yoshiyasu Tamura of the Institute of Statistical
Mathematics, Prof. Fumitake Sakaori of Chuo University andProf. Akinobu Takeuchi of Jissen Women’s University–threeof the founding members of the subcommittee and the contest–will share their takes on the future of the application ofdata science in sport and what it means for the talents thatwill be required to help develop successful game strategies.

Prospective Data Scientist Turned Professional
Baseball Player

Ask the Experts: Akinobu Takeuchi
Professor of
Jissen Women’s University
Dr. Takeuchi is professor for the Faculty of Humanities and Social Sciences at Jissen Women’s University and the director of the university’s Information Center. He specializes in statistical science, behavior
metrics, and statistical education, including data science education.
As the chairperson of the Special Committee of Statistical Education,
Dr. Takeuchi has long worked to develop educational methods for fostering statistical thinking.

On March 19, 2018, dozens of data scientists from across thecountry, both professionals and students, descended on the
Research Organization of Information Systems (ROIS)’s theInstitute of Statistical Mathmatics’ headquarters in the suburban Tokyo city of Tachikawa for the 7th annual Sports Data
Analysis Competition award ceremony. The event highlighted the work of a grand prize, first prize and honorable mention winners in the highly competitive contest, which began
in June 2017 with a call for submissions, followed by a September deadline and announcement of the awardees in January. The exponential growth of the contest’s popularity overthe past years speaks for the surging interest in use of data
analytics in sport, said Prof. Yoshiyasu Tamura of the Institute of Mathematical Science, a baseball enthusiast who used
to play the sport for his university as a catcher.
“I love all kinds of sports, and that’s how I became interested in applying statistics to sports,” Prof. Tamura said, looking
back on his college days. “When we began the competition,very few people had heard of the word, ‘data science,’ and we
didn’t even have the Japan Data Scientist Society,” Prof.

85

the research, we would add points for that, too,” said Prof.
Fumitake Sakaori of Chuo University, who has led the com-

petition long with Prof. Tamura since its inception. “In otherwords, we look at whether the analysis is warranted.”
The second most important criteria are whether the teams

used appropriate techniques for analysis as well as their inge-

The results of the 7th annual Sports Data Analysis Competition are available athttps://estat.sci.kagoshima-u.ac.jp/sports/ (in Japanese).

Tamura said. “A lot of people are sports fans like me. It makes
sports an ideal subject for practicing analytics.”
The success of the Sports Data Analysis Competition has
proven him right. The 2017 contest drew submissions from as
many as 61 teams for three sports categories–baseball, soccer
and basketball–each of which is broken down into three subcategories of “Analytics” and “Infographics” for adults and“Secondary Education” for middle and high schoolers.
Entries ran the gamut in subject matter from “Topological
data analysis for the evaluation of the robustness of the
defense system,” submission by a Keio University team, to“Analysis of basketball scores” entered by a Chuo University
team, which won the grand prizes in the analytics and infographics categories respectively.
“When I think about this year’s entries, there was morequality research that was soccer-related than baseball-related,” Prof. Tamura said. “In baseball, you only have pitch-bypitch data. In soccer, on the other hand, you not only havedata on an entire play but also ball tracking and touch-bytouch data, allowing you to synthesize them all for analysis.
The quality of soccer data is really improving,” Prof. Tamura
said.
The competition organizers are trying to offer participants
more sport choices to choose from, as well, which was thereason behind the addition of the rugby category for the 2016
contest.
“Statistics can be difficult to analyze, but sports have themagical power to get people excited about analyzing data,”
Prof. Tamura said. “I know one university student, who participated in the competition twice, went on to become a professional baseball player. I was stoked to find out about that,”he said. “Every professional baseball team nowadays is on thehunt for data analysis talent.”

Climbing the Learning Curb with Sport Data
AnalysisContest judges first screen the submissions based on how
attractive the analysis themes are.
“If there is a surprising result or highly practical use for86

nuity in the ways they conducted their analysis, according toProf. Sakaori. Originality and novelty count, he said.
“Teams that show originality in data analysis and groups
that try novel processing techniques to produce their own
data instead of using the variables given by the competition
organizers can earn extra points, as well,” Prof. Sakaori said.
“The great thing about sports is that those analyzing thedata easily understand what it is that they are trying to get
out of their analysis. Thus, sports data makes for excellent
educational material, especially when one is familiar withwhichever sports in the subject of analysis.” Prof. Sakaori
said.
He explained that the Sport Data Subcommittee’s single
biggest goal in organizing the competition was to encourage
people to make use of data and grow their ability to think interms of mathematical statistics.
“The competition program has been very effective in thatlight,” Prof. Sakaori said. “I can see contestants’ skills are
improved every time they come back for another competition. From the angles they take to their analysis to theirobjectives, everything gets better. I suppose looking at excellent work done by other teams inspires you and helps you
develop statistical thinking.”
In the end, you have to ask yourself for whose benefit you
are analyzing data–whether it’s for the players, for the coaches or for the team owners–or whether you are doing it toenhance the experience of watching games on TV, Prof. Sakaori said.
“Once you answer these questions, it becomes clear how
you should present your analysis,” he said.

Looking Beyond 2020: Data Analysis May Be
Sports’ Future
In the Sports Data Analysis Competition, participants get towork with streamlined datasets provided to them. In real life,
however, it is difficult to find well-organized quality data, andin some sports, you couldn’t find any data at all, according toProf. Sakaori.
“That creates a challenge for people who are trying to tap
into the power of data analysis to contribute to the sports
industry,” Prof. Sakaori said. “Another challenge is how to
produce analytical data from things like video footage ofsports tournaments. You can take data from video of a judo
tournament, for example, but that’s unstructured data andyou wouldn’t necessarily know how to approach it. We must
advance our knowledge in not only statistical science but also
informatics in order to deal with these issues,” he said.
Some countries have all sorts of professional sports
leagues, including basketball leagues, soccer leagues andAmerican football leagues. In these countries, there aremany science magazines focused on sports statistics, and lots

of research being conducted on the topic, as well, according
to Prof. Sakaori.

“In Japan, we are now seeing more sports consulting busi-

nesses being established to work with professional teams andstrategize how to boost the industry for the post 2020 Olym-

pics era,” Prof. Sakaori said. “Since the Japan Sports Analysts
Association (JSAA) has also been established in 2014, a number of conferences have been organized, and they are growing larger every year, offering opportunities for sports analysts to compare notes. If this is any indication, I predict
sports games 10 years from now will look much different
from the ones we see today.”Everyone Needs to Be Able to Talk Data
The 7th annual Sports Data Analysis Competition marked its
fifth year since opening the contest to middle- and highschoolers and drew as many as 65 submissions to the Secondary Education category. Prof. Akinobu Takeuchi of Jissen
Women’s University, who has overseen the category since its
beginning, said he has been impressed by the quality of thestudents’ work.
“People from around the world often look at the Japanese
as being highly skilled in mathematics. But statistics revealthat many other countries, particularly China, the U.S.,
South Korea, New Zealand, England and Australia, provide
much more advanced math education than Japan does,” Prof.
Takeuchi said.
There is a movement to revamp math curriculum in Japanese secondary education with an eye toward providing all
students with the necessary statistical skills to live in the data
age. Prof. Takeuchi has actively been involved in that initiative in recent years.
“Until recently, middle and high schools in Japan weren’t
doing enough to teach the concept of an “average” and how
the “median” value and “mode” have statistical significance.
It makes you wonder how this will prepare the students fortheir future–if they will become capable of joining theircounterparts from around the world even for a casual business conversation,” Prof. Takeuchi said.
He said that the sports data used in the competition are“pretty clean and almost normally distributed.” Data that statistical scientists have to work with in real life, including
social survey data, is never that clean, he said, but having
neat data helps contestants explore and discover how toeffectively use data to draw useful analysis from it.
“At the end of the day, you want your sports team to win.
But, just because they won, it’s not necessarily clear why they
won or what worked the most. We have to figure that out scientifically. And we want the contestants to learn the thoughtprocess required in statistical science,” Prof. Takeuchi said.
“If I take the basketball as an example, we want them to analyze why the team has a low shooting rate, what winningteams or losing teams have in common and other factors byusing various analysis techniques. It is important to be able
to realize a new technique could shed light on causal relationships underlying what they’ve found.”This year’s entry from a team from Kannonji Daiichi HighProf. Sakaori explains data at the 7th annual Sports Data Analysis Competition
award ceremony. The infographics category of the 7th competition drew fewer
submissions than expected. Prof. Sakaori says he hopes prospective contestants
to give a lot of thought to what they want to communicate through infographics.

The results of the 7th annual Sports Data Analysis Competition for the Secondary
Education category is available at https://estat.sci.kagoshima-u.ac.jp/cse/sports.
htm (in Japanese).

School in Kagawa prefecture epitomized such learning,
according to Prof. Takeuchi. The team conducted analysis tofigure out ways to strengthen a local basketball team. The
students created a diagram for their poster that summarized
the causes and effects of game results. They conducted aprincipal component analysis and verified the analysis method, as well. The poster, which proposes a new strategy for thebasketball team, won the grand prize in the category.
“Regardless of whether you are interested in majoring science or want to study the humanities and become a marketing professional, data science skills provide the foundation
for all. This competition’s purpose is to raise the next generations who are fluent in the language of data.”

Released on: November 12, 2018
(The Japanese version released on April 12, 2018)87

Science Report

017 Changing the World with Data Science 05

Changing Patients’ Lives
with Data Science

Ask the Experts: Shin’ichi Satoh
Professor of
National Institute of Informatics (NII)

Ask the Experts: Yoichi M. Ito
Professor of The Institute of
Statistical Mathematics (ISM)

Professor at the National Institute of Informatics since 2004 after
serving as associate professor at the institute since 2000. Expert inimage and video analysis-based information search and knowledge
discovery. Previously worked at Carnegie Mellon University as visiting
research associate from 1995 to 1997. Holds a Ph.D and undergraduate degrees in engineering from the University of Tokyo.

Professor at the Institute of Statistical Mathematics. Specializes inbiostatistics with a focus in genomic and statistical analysis and provides consultation on the topics. Has served as an expert member on
the PMDA, a reviewing board for new drugs, since 2009. More recently, working to analyze clinical trial data through the lens of efficiency
to develop ways to improve data management. Holds a Ph.D. in healthsciences from the University of Tokyo.

88

Saving patients’ lives isn’t just the responsibility of medical
and healthcare professionals any longer. It takes a village toprovide the best care possible, and playing increasingly

important and larger roles in it are data scientists and people

in the associated fields. This trend precipitated the recent

openings of the two national data research centers–one at
the National Institute of Informatics (NII) and the other at
the Institute of Statistical Mathematics (ISM). The ResearchCenter for Medical Bigdata at the NII opened in November
2017, followed by the Research Center for Medical and
Health Data Science at the ISM’s opening in April 2018. Boththe NII and the ISM are part of the Research Organization ofInformation Systems (ROIS). The two new research centers
work to muster all the information technology (IT) and statistical knowledge and resources available in Japan while
promoting interdisciplinary collaborative research projects
as members of the Inter-University Research Institute Corporation. Well-managed data infrastructures can propel scientific discoveries and innovations, and so does superior analytical capacity, such as that of artificial intelligence (AI).
Now that the newly opened research centers aim to deliverboth, how will that help drive forward Japan’s medical
research and health care? The directors of the two centerswill share their visions for future applications of data sciencein medicine.

Bringing the Best of the Best in the IT World to
Help Physicians

Ask the Experts: Hisashi Noma
Associate Professor of
The Institute of Statistical Mathematics (ISM)
Associate professor at the Institute of Statistical Mathematics.
Appointed to the current position after studying biostatistics at theGraduate School of Medicine, Kyoto University and serving as the
ISM’s assistant professor. An expert in the fields of medical statistics
and public health, he hopes to “contribute to the advancement of medicine and health care through research and education.”

The National Institute of Informatics (NII), which is home to
the newly opened The Research Center for Medical Bigdata,
is Japan’s only general research organization solely focusedon information technology (IT). The NII became the Japan
Agency for Medical Research and Development (AMED)’s
partner organization in 2017 and has since worked with four
academic societies–the Japan Gastroenterological Endoscopy Society, the Japanese Society of Pathology, the Japan
Radiological Society, and the Japanese OphthalmologicalSociety–to develop the IT infrastructure for the medical andhealth care communities. The collaborative efforts include
image analysis, deep learning and work toward the development of AI.
The Research Center for Medical Bigdata now leads these
efforts. The center has about 10 research team members,some of whom are enlisted from such outside organizations
as the University of Tokyo, Nagoya University and Kyushu
University. The members also include some young post-doctoral researchers. They are among the brightest in their own
fields, but most of them don’t have any experience in analyzing medical images.
“I, for one, am a researcher specializing in image analysis
and deep learning and had never dealt with medical images
before,” said Prof. Shin’ichi Satoh of the NII, who serves as the
director of the Research Center for Medical Bigdata. “Thething is, we can analyze medical images. Though we don’tknow what we are looking at, the artificial neural networkthat we trained, which is a type of AI, does know what to do,”he said.

89

High-performance image-recognition systems aren’t foolproof. “If you add carefully crafted ‘noise’ to images of pandas and feed them to a machine, for example, 99.3 percent of the time, the system will tell you they are the images ofa gibbon,” Prof. Sato says. “We need to test the machines from various angles to understand how they process something out of the script.”

Until recently, scientists in the field of medical image
analysis were trying to create computer programs for dataprocessing that reflect their medical knowledge, according toProf. Sato.
“There has been a ‘shift in the tide,’ if you will, as we
became capable of feeding an astronomical amount of data toa machine to make some sense of it,” he said. “It’s been only ayear and several months since our collaborative researchbegan, but we are already seeing a lot of successes with theuse of machines. For example, very basic artificial neural networks can quite accurately diagnose diabetes and glaucoma,
particularly when using fundus images as a diagnostic tool.
These diagnoses are actually challenging ones for physicians
to make,” he said.

A Turning Point in the ‘Game of Computer Image
Recognition’sProf. Sato pointed out there have been three major “waves”
that pushed forward the research on artificial neural networks over the years.

90“The first wave was the emergence of a neural networkthat mimicked that of the human brain. This was technicallya single-layer network capable of learning how to use randomized linear functions. It proved that machines can learn
from inputs and became the framework for machine-learning. The second wave was the arrival of so-called neurofuzzy. This was a little more complex network with two to
three deep-learning layers,” Prof. Sato said.
“Then, in 2012, a revolutionary algorithm mimicking thehuman brain’s neuron network became available. Its ability
to learn and think far exceeded that of any other algorithm
that existed at the time. This spurred interest in leveraging
the technological advancement and availability of big data to
make discoveries. This is the third and latest wave in the history of neural network inventions,” he said.
The revolutionary computer vision algorithm was built by
University of Toronto professor Geoffrey Hinton–who is
known in the research community as the “Godfather of AI”–
and his students for a competition in which they participated.
The team gave the large, deep convolutional neural network
1.2 million images to train it to recognize 1,000 different

types of objects.
“The team’s research paper gave researchers an understanding of how much data a machine needs to do its job andat what level of accuracy. It became a turning point in thegame of computer image recognition,” Prof. Sato said.
“Before this, what objects a machine should recognize andhow it should be done were all determined by humans. What
sets Prof. Hinton’s neural network apart from the rest wasthat it was designed to teach itself from scratch what to do
and how,” Prof. Sato said. “When you train this type of network by giving a huge number of images containing 1,000
different objects, it does a superb job recognizing objects in
newly introduced images. Unfortunately, we don’t knowwhat the machine learned, but it clearly can carry out very
efficiently what we humans used to rack our brains to do.”Prof. Hinton’s algorithm had eight learning layers. Nowadays, deep-learning machines with 100 to 200 layers arecommonplace, according to Prof. Sato.
The theoretical analyses that provide the foundation ofdeep learning have remained unchanged for the past three
decades, Prof. Sato said. But, what you can do with artificial
neural networks, especially with computer vision recognition, has drastically improved over the years, and researchers
have now had experiences to better understand the possibilities as well as the limits that artificial neural networks present, he said.
At the Research Center for Medical Bigdata at the NII,
researchers are working toward finding efficient ways to use
computer image recognition technologies for analysis of
medical big data.

Making Doctors’ Lives EasierProf. Sato believes image recognition algorithms can help
reduce physicians’ workload. To achieve this goal, his team iscompiling “correct diagnostic interpretations” of image datathat can be used to train the machines.
“If you were analyzing image data to correctly recognize
cats and dogs, anyone could do it. But medical analysis
requires physicians’ expert knowledge. Data has to be looked
at by physicians, and they need to tell you what the rightinterpretation is. This defeats the purpose of making physicians’ lives easier,” Prof. Sato said. “So, we use self-learningalgorithms to narrow down the scope of data that requires
physicians’ judgement and request doctors to attach correctinterpretations to it. This considerably reduces physicians’
workload. But, I think we can and should make the algorithm
even more physician-friendly,” he said.
Algorithms could also assist physicians in other ways toimprove the quality of medical care.
“In the near future, we may have an image analysis systemdesigned to provide support to physicians. The system could
prevent physicians from overlooking important information
or offer an independent second opinion. It could also diagnose minor illnesses, so the physicians can use their time tofocus on other illnesses that are more difficult to diagnose,”
Prof. Sato said. “It’s our dream to develop an advanced AI
algorithm that has the judgement of experienced physicians.
If we create that, we can then make it available in remoteplaces like islands. It’s a program, and so you could easily replicate it, as well,” he said.

91

Prof. Yoichi Ito (left) and Dr. Hisashi Noma, who
serve as the director and vice director of the
Research Center for Medical and Health Data
Science at the ISM respectively.

Fostering Data Scientists in University Medical
Departments
In the meantime, the Research Center for Medical and
Health Data Science, which recently opened at the Instituteof Statistical Mathematics (ISM), aims to bring together
medical statistics experts and build different types of intelligence infrastructures to prepare the country for medical andhealth care in the coming data age.
“More than 60 universities across Japan have medical
departments, and they all critically lack biostatisticians. The
center’s missions include fostering the next generation ofdata scientists with the knowledge and skills required toassist the medical community, as well as providing training
for literacy in medical statistics,” said Prof. Yoichi M. Ito of
the ISM, who serves as the director of the center.
The center offers four courses a year on education of medical statistics. Five publicly accessible seminars have alreadybegun as part of these courses, and a symposium organized
to celebrate the center’s inception was also held on May 28,
2018.
“The foundation of this center would help raise the level ofenthusiasm for data science in the medical and healthcarecommunity, and the change was palpable,” said Dr. Hisashi
Noma of the ISM, who serves as vice director of the centerand directed the symposium’s operation.
Prior to the center’s opening, the ISM called for the formation of the Medical and Health Data Science Research Network to promote statistical education. More than 70 institutions, including universities and hospitals, quickly answered
the call, Dr. Noma said.

Rigorous Evaluation of Clinical Trials from Statistical Science’s Standpoint
Evaluation of clinical trials for new drugs is another area
where Prof. Ito believes the Research Center for Medical and
Health Data Science can make contributions.
“As you know, statistics has always played a critical role in92

life science, particularly pharmaceuticals. I mean, statistics
is an essential tool for understanding the effectiveness andsafety of a new drug when evaluating the result of a clinical,”said Prof. Ito, an expert of clinical trial evaluation who has
years of experience in helping design clinical researches as astatistical consultant.
“The human body has biologically complex systems andexhibits very different responses to drugs than other species
do. Over the years, we have seen human subjects in someclinical trials experience totally unexpected side effects to
drugs that had proved safe in mice, dogs, and even monkeys
that are biologically more similar to humans. To understandwhether a new drug has any therapeutic benefit or if it’s safefor humans from the result of clinical trials, we must apply
statistical science to come up with an exact margin of error
and scientifically evaluate the data. This is where statisticalskills come in,” Prof. Ito said.
“Design methods for clinical trials are also improving
every day, and so we need to keep pace with new methodologies for statistical analysis. This is a highly specialized field inwhich every step is intentional and calculated–which makesa sharp contrast with analysis of big data,” Prof. Ito said.

Accurately Estimating Harmful Environmental
Factors
Epidemiology, the study of distributions and determinants ofhuman health and diseases, is another area in which statistical science is making a big difference. The history of epidemiology goes back to the 19th Century England when scientists
began researching what caused the spread of cholera andother infectious diseases and how to prevent them. Since
then, it has evolved into the study of medical care and healthin general as disease patterns have diversified in modern
society. More specifically, epidemiologists refer to those who
make scientific assessments of the health impact of suchenvironmental factors as cigarette smoke, hormone-disrupting chemicals and air pollutants, using observational studies
of humans as their basis, according to Dr. Noma, who has

Prof. Ito says he often fell ill as a child and wanted to become a doctor to help people like him. Now in his ninth year of serving as an expert member of the Pharmaceutical and Medical Devices Agency, Prof. Ito reviews a lot of new drug applicationfrom an outsider’s point of view. “This is an important role through which I can contribute to improving the quality of new drug reviews,” he says.

The Research Center for Medical and Health Data Science has recently publishedseveral new “meta-analysis” methodological papers. Meta-analysis refers to synthesis analyses of systematic evidence from past clinical trials to investigate theeffectiveness and safety of medical technologies, according to Dr. Noma.

worked on epidemiological research projects since college.
“The problem is that we have no way of controlling those
harmful environmental factors like you would in normal scientific experiments. We rely on statistical methodology to
precisely determine how and from which subjects we shouldcollect data and whether other factors are involved,” he said.
Epidemiological experts particularly try to look at data
through the lens of statistical science to minimize the effectof biases.
“Measuring biases is very difficult. It’s just not possible toset ‘perfect’ questions that produce no biases in evaluation,”
Dr. Noma said. “But, because you are evaluating publichealth risks, even though you know what you have includes abias, you have to take action in response to it to protect the
public. Then you again need the help of statistical science tofigure out what an effective action would be.”Epidemiology began a long time ago, way before statisticalscience did. In recent years, the methodologies used in epidemiology started becoming more refined. Methodologies
didn’t originate in clinical trials, which is my specialty, but
the fields of epidemiological statistics and life science statistics, such as what you obtain in clinical trials, are crossing
over, spurring advancement of methodologies,” Prof. Ito said.

and 1960s. But, in 1999, a group of scientists in the U.S.
proved that the drug that prevents angiogenesis, can effectively be used to treat myeloma, resulting in the approval asan anti-cancer agent in Japan in 2008. Through data analyses that use data science methodology, researchers are now
finding out that the nature and degrees of a drug’s effects
vary from patient to patient,” Prof. Noma said.
“Let’s say you have cancerous cells removed from apatient. You measure all sorts of things for comprehensive
analysis of genetic and molecular-level information, and you
will end up with more than several million dimensions ofdata. This is what you call omics data. Omics data has become
available, partly thanks to the considerable advancement of
measurement techniques in the past two decades,” Prof.
Noma said. “Using our new statistical methodologies to analyze patients’ omics data in connection with thalidomide’s
effects, for example, it becomes clear that those who weretreated with the drug have better prognoses than patients
who didn’t take the drug. In addition, thalidomide affects
individual patients differently, depending on whether theirmolecular cells show certain gene expression patterns. By
applying newer methodologies to the analysis of omics data,
you can gain such detailed insights,” he said.
“With research projects beginning to leverage big data inmore diverse ways, methodology for data analysis is needing
to change and diversify, as well. The Research Center for
Medical and Health Data Science strives for fundamental
research to help fulfill this demand, conducting research on
such topics as the use of machine learning technology for
exploratory analysis of genetic data, as well as the theoreticaldevelopment of classical statistics,” Prof. Ito said. “It is ourhighest priority to establish an analysis model to offer
patients accurate prognoses, rather than to get a complete
picture of a group of patients. This is the most urgent task forus. It’s also an intriguing challenge for us to tackle.”

Building New Methodologies from the Base
The Research Center for Medical and Health Data Sciencehas six ongoing research projects, and one of them is called,the “Project to develop methodologies for clinical researches
and evidence synthesis.” The project brings together the center’s dual interest in developing novel methodologies andpromoting big data analysis to make “precision medicine”
available in daily medical practices. Efforts to advanceresearch on precision medicine are taking place around theworld, including in the United States where former President
Barack Obama announced the Precision Medicine Initiative
during his 2015 State of the Union address.
“For example, thalidomide is infamous for bringing on
horrible side effects in patients worldwide during the 1950s

Released on: December 18, 2018
(The Japanese version released on May 10, 2018)93

Science Report

018 Changing the World with Data Science 06

What’s on the Horizon in
the Changing World of Big
Data?

Ask the Experts: Masaru Kitsuregawa
Director of National Institute ofInformatics (NII)

Ask the Experts: Tomoyuki Higuchi
Director of The Institute of
Statistical Mathematics (ISM)

Since 2013, Dr. Kitsuregawa has served as the director of the National Institute of Informatics, the Research Organization of Informationand Systems, and professor at the Institute of Industrial Science at the
University of Tokyo. As an expert in database engineering, he leads
some of the most prominent informatics research projects in Japanand has developed a high-speed database engine, using “out-of-order
execution schemes.” He is known for operating the mammoth Global
Environmental Database. The 1983 graduate of the University ofTokyo holds a Ph.D. in engineering from the same university. He previously served as vice chairman of the Information Processing Societyof Japan and 23rd chairman of the Informatics Committee of the Science Council of Japan.

Since 2011, Dr. Higuchi has served as the director of the Institute of
Statistical Mathematics, the Research Organization of Informationand Systems. An expert of Bayesian modeling, he is known for statistical modeling derived from real-world problems as well as researchon data assimilation that combines mass data and theories behindsimulative calculations. He leads various integrated research andworks to foster the next generation of researchers. He serves on the
ROIS’s board of directors and as an advisor to the Japan DataScientist
Society. He received his bachelor’s degree in 1984 and his Ph.D. in
1989, both from the University of Tokyo.

94

We are living in the era of big data. Easy access to colossal
amounts of data being constantly gathered and compiled on
virtually every topic imaginable is enabling businesses andresearch institutions, such as universities, to gain insightsthat would have seemed impossibly far-fetched only a few
years ago. As artificial intelligence (AI) becomes more sophisticated in its ability to autonomously make data-driven decisions, many of us are asking ourselves how soon we may
reach the singularity — the tipping point where computer
intelligence exceeds that of humans. This causes us to pause
and examine in which directions data science is advancing
and what kind of research we need to conduct to help solve
complex problems. The directors of the National Institute ofInformatics (NII) and the Institute of Statistical Mathematics(ISM) – which are both part of the Research Organization ofInformation and Systems (ROIS) – recently sat down to talkabout all these issues and share their outlooks on the futureof big data with the Science Report’s readers. Here are theirperspectives and the latest on the leading-edge technology
and research.

Creating Big Data from Small Data
Data analysis techniques and AI technologies are constantly
evolving and advancing. Where are we at in this journey, andwhat type of research projects are commanding the science
community’s attention?
Kitsuregawa: The most interesting challenge we are tasked totackle is the question of how to make small data big. For
example, typhoons hit Japan typically 10 times a year, andthis means we only get 100 incident data to learn from over
10 years. The question is, how we can draw the informationthat we need from the data on these 100 incidents? Inother words, how do we data scientists do what we dowhen data is intrinsically lacking in certain fields?
That’s the biggest challenge facing us right now.
Higuchi: Those are so-called rare events. They spur
innovations and help make risk analysis more accurate.
In mathematical statistics, researchers have traditionally used the “experimental design” method to prove a
hypothesis through a limited number of experiments.
But today’s science calls for an even more intentional
system–a system that merges experiments, measurements and observations into a single process.
Kitsuregawa: Prof. Takaaki Kajita of the University ofTokyo, for instance, had very little experimental data,but his interpretation of the data has led to his discovery
that neutrinos have mass, for which he received a Nobel
Prize in 2015. This “interpretation” was a very sophisticated one and on a completely different level than AI’s
pattern recognition and learning. But because Prof.
Kajita was studying a phenomenon that occurs inaccordance with the rules of physics, it was possible forhim to trace it, step by step, to its causation. In mostcases, you can’t do the same with what we see happening in this world. Take rare diseases as an example. It’san area that we’ve been interested in, because unlike
diabetes and hypertension from which millions of people suffer, we may only find one patient in Japan andanother in England who have a certain rare disease. So,
how do we go about finding a cure for a rare disease likethat? Tackling such a problem requires us to bring
together all talents and expertise and try different ideas.
Higuchi: In material data science, we may be able to95

determine the molecular bond and structure that gives substance a certain feature, but it is difficult to actually createthat substance. This is the bottleneck in the practical application of advanced material data science. Researchers areexperimenting with different approaches, such as simulating
an experiment and searching for a pattern among its results.
But when it comes to figuring out the process of creating a
new material, experience still remains a more reliable tool
than data science.
Kitsuregawa: In other words, just because a certain calculation method worked in identifying a material’s structure,that doesn’t tell you how to extend the method for finding a
way to create the material. Also in natural language processing, the machine’s ability to use big data for deep-learning is
still limited. We need to figure out our next “card” that gets
us through this bottleneck. In that sense, we are in a transitional phase.

techniques have grown tremendously sophisticated over theyears, contributing to the advancement of AI. The question
now is how we are going to develop extrapolation techniques
to provide solutions to problems. This is where we hit thebrick wall. Another limitation of data science, currently, isthat while it can show how things are correlated, it’s nearly
impossible to demonstrate if there’s any causal relationshipamong them.
Kitsuregawa: Yeah, it’s impossible.
Higuchi: Right. I mean, you extrapolate data to predict theunpredictable, and it’s not possible yet to pinpoint exactly
when and where an earthquake is going to happen, for example. Not, at least, until data science advances a little more andwe have far better simulation models. The good news is that

Getting Through Data Science’s ‘Bottleneck’

The Language of Data as Part of Basic Education

Data science is becoming an integral part of research in awide range of fields from earth science to nanotechnology tohealth care to material development. While industry puts
high hopes on data science as the key to innovations, directors Kitsuregawa and Higuchi say data science still has a long
way to go before it can solve more complex problems.
Kitsuregawa: Science can effectively solve various problems,
but there are certain areas where science can’t be of help, as I
mentioned earlier. I believe we, the scientists, ought to academically identify those limitations, as well.
Higuchi: That’s right. I often explain this limitation issue
through the concepts of interpolation and extrapolation. In
data science, we basically make predictions within thebounds of existing data. That’s interpolation. Extrapolation isto go beyond the bounds and make predictions. Interpolation

The big data era is here to stay, and data technology is expected to grow more sophisticated. So, how should we equip ourchildren with the knowledge necessary to live in datasociety?
Kitsuregawa: Science and technology is advancing so much
faster nowadays than in the past, following the “law of accelerating returns.” Eventually, it will reach the “singularity.”
The biggest conundrum will be people’s slowness in digesting
the fact and adapting to the new reality in everyday life. Just
think about how long it may take to reform the Copyright Act
to make it suitable for the internet era. You may adopt newtechnology to make society a less confusing place, but if people don’t understand its benefits, society would only growmore chaotic. I just wonder if there is a way to expedite thehuman recognition process.

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we are becoming better at quantitative risk analysis by making good use of high-speed computation and abundant datacollected through observation networks.

Looking back on human history, a drastic transformationor the collapse of a culture has always occurred in its very
final moment–equivalent of one last second versus an entire
year. In hindsight, you can see there is a sequence leading up
to such big changes, which is usually triggered by an unforeseen, peculiar human act, which then develops into a war,causing fear among the population. If this is any indication, if
only technologies continue to advance without adequate
time for people to appreciate what’s happening, it will sooner
or later trigger major changes to our society. That’s myconcern.
Higuchi: I feel the same way. This leads to the question of how
we should educate the new generation. By the way, what are
your thoughts on programming education in secondary
schools?
Kitsuregawa: In Japanese schools, students learn Japanese
first, English some years later and another language in college. I think the education of programming language should
be given as much weight as any non-Japanese language, if
not more. By having good English skills, you will be able tocommunicate with people from around the world and understand them, and that enriches your life. Programming language allows you to turn your idea into a tangible “thing.” Inevery IT course I teach, I always tell my students to bringsomething manmade to the first class. You will realize prettymuch every product has a computer in it. This goes to show
you that, without some knowledge of programming language, you won’t be able to make anything, and you may evenhave difficulty striking up a casual conversation with someone. In that regard, programming language should be part ofthe basic education for everybody. It is crucial that people
begin learning how to make things at young ages.
Higuchi: We are also surrounded by data in today’s society. I
hope future generations will grow up analyzing and interpreting data themselves to improve their daily lives. At theISM, we have a program for secondary school students called
ISM Data Science High School. It may sound like a place thatteaches complex machine learning and analytical methods,
but that’s not our focus. We want to provide the students withlearning opportunities to figure out on their own that how
they select a problem to tackle, and what angle they take tosolve it, matter the most in data science.

Released on: January 21, 2019
(The Japanese version released on June 11, 2018)

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ISBN978-4-909638-09-0 C0040