Research Organization of Information and Systems

ROISEstimation of disaster recovery condition
based on Web reservation data
Yu Ichifuji†‡, Noboru Sonehara‡† : Research Organization of Information and Systems,
Transdisciplinary Research Integration Center‡ : National Institute of Informatics

17/3/2014 in Sendai, Japan

Background: Lessons from the Great
East Japan Earthquake
ROIS
Research Organization of Information and Systems• Before the Great East Japan Earthquake– Goals of disaster prevention before the disaster:• Evacuation drills ⇒ Cause for failure to escape• Emergency systems⇒ Users don’t understand usage procedures, are not used tothe system, are unable to operate them (loss of power, etc.), do
not know about their existence, etc.
• “Super-levees” ⇒Reduce tsunami damage• After the earthquake– Behavior of disaster victims: made use of available systems
that they are used to using or have been using• E.g. Use SNS (Twitter, Mixi, etc.) for confirming safety and location• E.g. Use data for detecting traffic congestion in checking passableroads

Background: Lessons from the Great
East Japan Earthquake
ROISResearch Organization of Information and Systems• Issues that have come to the fore:– Information systems that activate only during emergencies• Since users do not know how to use them or are not used to them,the systems were not helpful.
• Unable to operate due to loss of power, etc.

– Breakdown of administrative functions• Unable to provide evacuation instructions• Difficult to monitor situation in disaster areas from outside• The kind of information systems needed :– Social systems that are used also in normal times and areroutinely available without having to change the methods
for operation during emergencies.

Systems used in normal times
Research Organization of Information and SystemsROIS• Target: Tourism– Local governments implement tourism policies andhave a grasp of tourist movements and status ofhotels.
Hotels have beds and food and are useful as places forevacuation during disasters. If the above information can becollected, they will be useful in determining situations during
occurrence of disasters.

– Data that serve as scientific basis for deciding policies
are obtained through social surveys using
questionnaires and other means.

Systems used in normal times
Research Organization of Information and Systems• Problems with statistical data– Collecting data takes time and money– Collecting data prevents their use for grasp situations
during emergencies.

Can Web data be used to enable grasping
emergency situations at reduced cost and time?
• Collectible data
– Web reservation data for hotels– Web reservation data for Shinkansen

ROISUsefulness of Web reservation data
• Hotels

Research Organization of Information and Systems

ROIS– Business reopening information can be interpreted as
information that business is restored.
• Areas where disaster damage has been checked and lifelines (water,gas, electricity) have been secured, or where their restoration isforeseen• Possible that distribution channels have been secured(Bed sheets are changed once every three days)(Gasoline, food, and other supplies are secured)– Base for disaster victims, volunteers• Can be used as temporary evacuation shelter for disaster victims• Number of volunteers that can be accommodated can be known

Usefulness of Web reservation data
Research Organization of Information and Systems• Means for transportation

ROIS– Business reopening information ＝ secured routes todisaster areas⇒For ensuring distribution channels, routes fortransporting personnel, and road safety
Possibility of visualizing recovery situation in disaster areas
based on Web reservation data for hotels and for Shinkansen• Objective
Visualize situation in disaster areas and recovery situation inreal time using Web reservation data

Contents of gathered data
Research Organization of Information and SystemsROIS• For hotels (target: general Web reservation sites)– Hotel names– Plans available for reservation, number of available plans,
number of available rooms, and details, for up to twomonths from the date of data collection– Rates for each plan, number of visitors• For transportation means (target: Shinkansen)– Departure/arrival areas, departure/arrival stations– Departure time, arrival time
– Names, class, seat availability for all trains up to one weekahead• E.g. Open, few seats available, full, etc.

Collection of Web reservation data anddata items to collectResearch Organization of Information and Systems…

Hotel 3

Hotel 2

Hotel１

Information on accommodationplans and prices

Reservations
through the Web
Site A

Site B

Information onremaining
available plansand prices…

Site CPrivate guests

Collect information across sites

Web reservation DB
Detailed facility information
Hotel ID

Hotel name

Access information

Overview of facility

Other facilities and services

Detailed plan information
Plan ID

Plan nameRoom ID

Room namePrice information

Plan details

Detailed price information
Plan ID

Room ID

Reservation
date

Walk-in rate

Reservation
date

Walk-inavailability

1-day-before rate…

60-days-before rate

1-day-before
availability…

60-day-before
availability

Detailed information on availability
Plan ID

Room ID

ROIS

Advantages and problems of Web
reservation data
ROIS
Research Organization of Information and Systems• Advantages of Web reservation data for hotels andShinkansen– Data are updated in real time
– Information-provider voluntarily uploads data

• Problems– As a feature of e-commerce, data are provided to multiple
sites, making it difficult to ascertain actual situation– Unclear whether reservation data reflect the real world
situation exactly in normal time and emergencies
There is a need to show that reliability of data has been
ensured through comparison with the real world

Reliability of Web reservation data during
and after disaster
ROIS
Research Organization of Information and Systems• Web reservation data in Sendai City

– Reservation data for hotels– Reservation data for Shinkansen from Tokyo to Sendai• Data collection period– Nov. 1, 2010 to May 31, 2011

• Data collection method– Obtain data from websites– Web reservation system was available during and afterdisaster• Method for confirming reliability– Comparison with data from the real world

Reliability of Web reservation data during andafter disaster
ROIS
Research Organization of Information and Systems• Real world data
– Data corresponding to statistical data for tourism in normal
times are not available during and after disaster occurrence.
⇒Business reopening dates were determined manually
through hotel websites and hotel staff blogs.
Example:*From official website of a hotel in SendaiWeb reservation data during and after disaster• Web reservation data

Research Organization of Information and Systems

ROIS– Information on available plans could not be obtained for sometime for hotels that showed an available plan at least once afterthe earthquake.
– Reasons:
Number of available rooms were few due to accommodation ofdisaster victims; there was an influx of reservations since thehotel was used as a base for volunteers
Actual situation cannot be determined using the same methodand criteria as in normal times.
After the earthquake, if a reservation plan becomes available even at least
once, consider the hotel to have resumed operations, as a means tovisualize recovery situation.

Comparison of real-world data and Web reservation datafor hotels
ROIS
Research Organization of Information and Systems

Number of hotels in operation

120
100
80
60
40
200

Actual data
現実データ（確認済みのみ）(confirmed only)

Around 10 facilities forwhich date of resumptionof operations is unclear

Web予約データ
Web reservation data

Usefulness of reservation data for hotels
during and after disaster

Research Organization of Information and Systems

ROIS• Advantages of visualization through Web reservation
data– Possible to determine recovery situation of hotels; easy tocollect information on recovery since information isuploaded by owner of facility– Possible to infer recovery situation from reservation data
Possible to determine whether there is delay in recovery
Indications of possible delay in recovery can be used as
criteria for providing support and for prioritizing assignmentof volunteers.

Recovery situation for Shinkansen operations
Research Organization of Information and Systems

ROIS• Real-world data

– Check news reports and press releases– Reservations not possible from March 12 onwards– Reservations resumed for trains traveling from April 25– All lines for Tohoku Shinkansen reopened in April 29– Some areas had reduced-speed operations, reduced number oftrains• Web reservation data

– Complete match with the real-world data
– Reservations resumed starting April 23– Operated at 44 trains per day for one week from April 25– All lines for Tohoku Shinkansen reopened in April 29, operating
at 54 trains per day

Recovery situation of hotels and Shinkansen operations
based on Web reservation data
Research Organization of Information and Systems

Number of facilities in operation

120100Hotel新幹線

Shinkansen

807060806040504030202001002011

Number of Shinkansen trains in operation

ホテルROISUsefulness of online reservation data during andafter disaster
ROIS
Research Organization of Information and Systems• Web reservation systems operate during and even afterdisaster• Collecting and analyzing Web reservation data during
and after disaster enable visualization of recovery
situation.
• Since hotels are used as evacuation centers, andtransportation means are essential for the transport ofgoods, the ability to determine current situation fromWeb data is an advantage.
• In particular, reservation data provide the advantage ofbeing able to determine future recovery situation.
• Visualization of recovery situation is possible through theuse of data used in normal times, without the need forbuilding new systems, ensuring a system that is routinelyavailable also during emergencies.

Summary
BackgroundResearch Organization of Information and Systems

ROIS• There is a need for social systems that are routinely available and are usedwithout having to significantly change the methods for operation, both innormal times and in emergencies.
Objective• Visualize situation in disaster areas and recovery situation in realtime using Web reservation data.
Results• Situation based on Web reservation data matches real-worldsituation.
• Possible to determine recovery situation from reservation data
– Possible to determine flow of persons, i.e. disaster victims andvolunteers– Possible to ensure transportation routes and confirm safety

Future issues to address• Construction of a system that takes use during emergencies intoconsideration.

Research Organization of Information and Systems

THANK YOU FOR YOUR ATTENTIONROIS