Delivering Biodiversity Knowledge
in the Information AgeGlobal Biodiversity
Informatics Outlook

Contributing authors

Editorial assistanceAcknowledgements

Donald Hobern (coordinating author)
Alberto Apostolico
Elizabeth Arnaud
Juan Carlos Bello
Dora Canhos
Gregoire Dubois
Dawn Field
Enrique Alonso García
Alex Hardisty
Jerry Harrison
Bryan Heidorn
Leonard Krishtalka
Erick Mata
Roderic Page
Cynthia Parr
Jeff Price
Selwyn Willoughby

Tim Hirsch
Sally Hinchcliffe
Samy Gaiji

The authors extend their gratitude to allorganizers, workshop leads, sponsors, participants
and facilitators at the Global Biodiversity
Informatics Conference (see Annex on page 36),whose creative discussions and inputs gave rise to
the framework outlined in this document. Special
thanks are due to the following for additional
helpful comments during the drafting period:
Donat Agosti, Ana Casino, Walter Berendsohn,
Lee Belbin, Don Doering, Gregor Hagedorn,
Keping Ma, Michelle Price, Hugo von Linstow
and Zheping Xu.

For affiliations of authors,see page 36.

Funding for the Global Biodiversity Informatics Conference and Outlook was contributed by:

Delivering Biodiversity Knowledge
in the Information Age

The Global Biodiversity Informatics Outlook
The Global Biodiversity Informatics Outlook helps to focus effort and investment
towards better understanding of life on Earth and our impacts upon it. It proposesa framework that will help harness the immense power of information technology
and an open data culture, to gather unprecedented evidence about biodiversity
and to inform better decisions.
This document is accompanied by a website, www.biodiversityinformatics.org,
that will report progress towards each part of the framework and provide a forum
for ideas, projects and funding sources supporting the goals of the Outlook.

Delivering Biodiversity Knowledge in the Information Age

Foreword
Our knowledge of the natural world and its complexity continues to grow at a staggering rate.
We continue to understand more and more of the mind-bending intricacy of DNA-based life andhow the various products of evolution interact. In many ways we are still engaged in the sameendeavour as the naturalists of earlier centuries. We are trying to develop an understanding of thiscomplex reality and how it works — only now we see even more levels to that complexity thanearly naturalists could have imagined.
We are fortunate to have in our hands an increasing number of tools to assist us with observing,recording and measuring this complex system. We have rapid sequencing technologies, a wealthof imaging systems, remote-sensing systems, physical and chemical sensors of all kinds, globalpositioning tools, the information backbone and processing power of the web and modern
high-performance computing, a global workforce of biologists with greater understanding ofevolutionary processes than ever before, and an army of amateur observers contributing theirskills and efforts. We also have political recognition of the importance of understanding thissystem and applying that understanding to support a sustainable future for mankind, the planet
and all the other species around us.
This outlook proposes a framework for making better use of all these opportunities, to benefit
us all. We hope you will join us in building and developing it.
Donald Hobern

Executive Secretary, Global Biodiversity Information Facility
Coordinating author, Global Biodiversity Informatics Outlook

2/3

Contents
Executive Summary

4

Introduction

5

Contribution of the GBIO to Aichi Targets

7

What you can do

8What happens next?

10

The GBIO Framework

11

Focus area A: Culture

12

Focus area B: Data

18

Focus area C: Evidence

24

Focus area D: Understanding

30

Annex – The Global Biodiversity Informatics Conference

36

Acronyms and Abbreviations

39

Endnotes

40

The origins of the Global Biodiversity Informatics Outlook
This document has been developed in consultation with the community, in a process initiated by the Global Biodiversity
Informatics Conference (GBIC).1 The conference gathered together around 100 experts from a wide variety of disciplines to meetin Copenhagen in July 2012.2 Scientists, informatics experts, policy makers, and others were invited to identify how best to harness
the power of information technology, biodiversity science and social networks to improve our understanding of life on Earth.
Through a series of workshops they identified the highest priority questions and the tools that would be needed to answer themand outlined the steps that would need to be taken to create those tools and deploy them effectively.
The ideas and priorities identified during the discussions at GBIC were subsequently distilled and structured by the workshop
leads and a core writing team. This document aims to present a consensus view and framework that will be widely adopted by
the people and institutions that will be key actors in its implementation.

Delivering Biodiversity Knowledge in the Information Age

Executive Summary

In summary, the GBIO proposes actions in the following key
areas:In order to preserve the variety of life on Earth, we must
understand it better. The world’s governments missed theirtarget to reduce significantly the rate of biodiversity loss by
2010. One of the main reasons for this was the shortage ofavailable information. To create appropriate policies to protect
habitats we must understand what they contain, how thespecies within them interact, and how they might respondto changes and pressures, natural and manmade. With the
adoption of the Strategic Plan for Biodiversity 2011-20,
including the Aichi Biodiversity Targets, governments havere-affirmed the importance of preserving and restoring
biodiversity and maintaining the planet’s ecosystem services.
Biodiversity informatics does not merely contribute towards
meeting these goals: it is fundamental to achieving them.

• Creating a culture of shared expertise, robust common
		 data standards, policies and incentives for data sharing
		 and a system of persistent storage and archiving of data.

The last 250 years of biodiversity research have produced awealth of information, but too much of it is still locked away
and inaccessible. At the same time, new technologies andscientific approaches are today unleashing a flood of new datathat could help us towards this fundamental understanding,but only if we are able to harness it effectively. Mobilizing
all biodiversity data, old and new, in a structured andstandardized form would enable a vast range of uses,
creating new opportunities for research and putting
biodiversity-related policy making on a sounder footing.
Much progress has been made in the past ten years to fulfil
the potential of biodiversity informatics. However, it is dwarfed
by the scale of what is still required.
The Global Biodiversity Informatics Outlook (GBIO) offers aframework for reaching a much deeper understanding of
the world’s biodiversity, and through that understanding
the means to conserve it better and to use it moresustainably.
The GBIO identifies four major focal areas, each with a numberof core components, to help coordinate efforts and funding.
The co-authors, from a wide range of disciplines, agree these
are the essential elements of a global strategy to harness
biodiversity data for the common good.

•
		
		
		
		
		
		

Mobilizing biodiversity data from all available sources,
to make them promptly and routinely available. Datashould be gathered only once, but used many times.
This includes data in all forms from historic literature andcollections to the observations made by citizen scientists;from the readings of automated sensors to the analysis of
the genetic signatures of microbe communities.

•
		
		
		
		
		
		
		

Providing the tools to convert data into evidence byenabling those data to be discovered, organizing theminto views that give them context and meaning. This
includes major collaborative efforts to improve theaccuracy of data and their fitness to be used in researchand policy; to provide a taxonomic framework; andto organize information about the traits of species and theinteractions between them.

•
		
		
		

Generating understanding of biodiversity and our
impacts upon it, by applying the evidence in models,
tools for visualization and identifying gaps to prioritize
future data gathering.

We invite funders, policymakers, researchers, information
technology specialists, educators and the general public
to unite around the framework detailed in the following
pages. The rewards of coordinated action will be as exciting
and significant as the great scientific collaborations toadvance our understanding of space, the human genome
and the fundamental particles of matter.

4/5

Introduction“I am convinced that the lack of adequate biodiversity
monitoring is at the heart of our difficulties to makeconvincing arguments. A Government that sees what its
policies do to biodiversity because it has access to reliabledata will be less likely to risk biodiversity loss and more likely
to find solutions that embrace biodiversity as a part of such
solutions.“ – Braulio Dias, Executive Secretary, Convention
on Biological Diversity (CBD), message to Global Biodiversity
Informatics Conference.
“Not only will biodiversity informatics projects need to deal
with an explosion in the amount of biodiversity-relevant
data, they may well need to accommodate data that areof a conceptually different form.” – Bob Robbins, Global
Biodiversity Informatics Conference.
A fundamental problem confronts us as we seek to preserve
the diversity of life on Earth: we need to know much more
about biodiversity if we are to understand how best to
protect it. We missed a target to reduce significantly therate of biodiversity loss by 2010 partly because of a lack of
information. As the 2010 deadline arrived, we had few reliableindicators that could provide us with a clear picture of thestatus of global biodiversity, and we lacked the informationand tools to foresee the impact of human activities.
And yet, we have a wealth of data — it is just that too often
it is locked up in museum drawers or printed publications, inisolated desktop computers or in incompatible digital formats,and in multiple human languages. Fortunately we live in an
increasingly networked world where more and more people
understand that information gains most value when it isshared. The new norms of social media and the developmentof the semantic web, as well as advances in data captureand handling ‘big data’, have transformed our approach
to information. There are improvements in modelling andinformation processing, and increasingly collaborative
developments within the biodiversity community itself.
Combined, these developments give us the opportunity toclose the current gap in our understanding, by mobilizing all
available biodiversity data – past, present and future – andmaking them useful for science and society.
Imagine a world in which every field observation, birdringing record, specimen image or species description was
permanently stored in a way that it was accessible, searchable

and usable, through standards that were commonly agreed
and well understood. Imagine that the efforts of scientists andexperts to improve, validate and synthesize these records werealso automatically captured and stored in a transparent
and accessible form, along with the information held in
the biodiversity literature from Linnaeus to the present day.
Nothing is lost or wasted, no effort needs to be repeated,freeing researchers to concentrate on the areas where weknow the least. It would be possible to develop large-scaleecological models, based on a constantly improving andgrowing body of data. Indeed, it would be possible to doquite unexpected things with the data, outcomes we have notanticipated. Not only would this contribute to our efforts tounderstand and track the rate of biodiversity loss — it would
enable better policy choices to be made to slow and evenhalt this loss.
After the failure to meet the 2010 biodiversity target,
governments agreed the ambitious 2011-20 Strategic
Plan for Biodiversity, including the new and more detailed
Aichi Biodiversity Targets. The plan aims to halt the loss of
biodiversity in order to ensure that by 2020, ecosystems
are resilient and continue to provide essential services(see page 7).3 As a result, policy makers now urgently require
the means to monitor the status and trends of life on Earth, tomodel the impact of changes, and to support the right policies
to slow and ultimately to end the depletion of the planet’s
biological diversity. Aichi Target 19 explicitly sets the goal of
improving, sharing and applying knowledge about biodiversity(see page 7); but in fact biodiversity information will befundamental to the achievement of all of the Aichi Targets.
Improved access to information will also be critical forthe new Intergovernmental Science-Policy Platform on
Biodiversity and Ecosystem Services (IPBES)4, which aims tostrengthen the science-policy interface for biodiversity andecosystem services for the conservation and sustainable useof biodiversity, long-term human well-being and sustainable
development.5 Improved access to information is not only vitalfor the assessments that IPBES is expected to deliver, but it has
also been identified as one of the key capacity building needs
the platform is required to meet as part of its functions.6
The GBIO and the framework it proposes will serve as essential
support to these and many other policy needs, by extending
our understanding of ecosystems and the services they
provide, making conservation and biodiversity management
policies more effective.

Delivering Biodiversity Knowledge in the Information Age

We can provide the information tools that researchers andpolicy makers need, but only if we work together to mobilize
the data we already have and ensure that the data we collectin future are fit for purpose. We will also need to collaborate toput in place the core infrastructure and data-related policies
that will provide a solid and sustainable foundation for future
research and future decisions affecting biodiversity.

Biodiversity informatics
Biodiversity research seeks to understand the variation
within and between species, and their relation togeographical, ecological, temporal and anthropogenic
factors. It explores the interactions among organisms,
including with humans; and between organisms and theenvironment. Further research can then explore trends,
analyse drivers of change and make predictions about the
future. All of these activities depend on access to the best
available data on recorded observations for each species,
supported by the best possible understanding of thebiases and uncertainties associated with each dataset.
Biodiversity informatics relates to the use of information
technology (IT) to support these needs, by organizing
knowledge about individual biological organisms andthe ecological systems they form. Over time, biodiversity
informatics will deliver an increasingly interconnecteddigital resource supporting scientific research of thenatural world.

Actions must be both local and global. Each country
should be committed to increasing the knowledge baseand to strengthening local, national, regional and global
infrastructures by making its data and information openly
available. When a country is committed to producing data
and knowledge, the chance that this data and knowledge
will be used in policies and decision support systems isgreater. Such buy-in will be essential if the tools enabledthrough the following framework are to achieve theirpotential in addressing the biodiversity crisis.

The first decade of the millennium witnessed growinginterest in biodiversity informatics and the emergence ofa community of scientists and IT professionals who havecollaborated to develop new capabilities in the field.
A number of global initiatives have been establishedto further the goals of biodiversity research throughinformatics, including the Species 2000 Catalogue of Life
(CoL),7 Biodiversity Information Standards (TDWG),8 the
Global Biodiversity Information Facility (GBIF),9 Encyclopediaof Life (EOL),10 the Consortium for the Barcode of Life
(CBOL),11 the Biodiversity Heritage Library (BHL)12 and theGroup on Earth Observations Biodiversity Observation
Network (GEO BON).13
Despite these initiatives, and many more at global, regionaland national scales, the biodiversity informatics landscaperemains very fragmented. The challenge for the GBIO is tohelp coordinate not just these efforts but the contributionsof all biodiversity research.

6/7

Contribution of the GBIO
to Aichi Targets
Focus area A: Culture
The whole of the GBIO framework will contribute to Aichi
Target 19, improving the world’s biodiversity knowledge base,and this is especially true of the components outlined in focus
area A. This foundational layer will underpin contributions toother targets from the remaining focus areas as detailed below.

Focus area B: Data
Increasing the use of crowd-sourcing and volunteers,
especially with field observations, will support Target 1,
making people aware of the value of biodiversity, in a very
direct and immediate way. Indigenous and local communities
will need to be engaged in the effort, so this will also support
Target 18, respecting traditional knowledge and practices.
Making field and remote sensed data immediately available
will be key to tackling Target 9, identifying and targetinginvasive species, while better integration of genetic data will
also support efforts to meet Target 13, safeguarding genetic
diversity.

Focus area C: Evidence
Having access to increasingly comprehensive data about
species, their occurrences, traits and interactions will beessential to achieve Target 9, identifying and targeting invasive
species and Target 12, preventing extinction of threatened
species, while integrated occurrence data will be important for
Target 4, implementing plans for sustainable consumption,
Target 5, halving the rate of loss of natural habitats, Target 6,
managing aquatic stocks sustainably, and particularly Target
11, the creation and expansion of protected areas.

Focus area D: Understanding
The real impact this focus area will have is on improving theeffectiveness of decision making and policies, vital to Target
3, phasing out harmful subsidies, Target 4, implementing
plans for sustainable consumption, Target 5, halving therate of loss of natural habitats, Target 6, managing aquatic
stocks sustainably, Target 9, identifying and targeting invasive
species, Target 11, creation and expansion of protectedareas, and Target 12, preventing the extinction of threatened
species. Arguably as important, improved visualization andcommunication of the information will transform people’s
understanding of biodiversity, underpinning Target 1, making
people aware of the value of biodiversity, and hence providing
the political will to make the other targets a reality.

Aichi Targets: an overview
The Aichi vision is that “By 2050, biodiversity is valued, conserved, restored and wisely used, maintaining ecosystem services,sustaining a healthy planet and delivering benefits essential for all people.”
This is to be achieved through five strategic goals, including 20 individual targets. The goals are:Strategic Goal A: Address the underlying causes of biodiversity loss by mainstreaming biodiversity acrossgovernment and society
Strategic Goal B: Reduce the direct pressures on biodiversity and promote sustainable use
Strategic Goal C: Improve the status of biodiversity by safeguarding ecosystems, species and genetic diversity
Strategic Goal D: Enhance the benefits to all from biodiversity and ecosystem services
Strategic Goal E: Enhance implementation through participatory planning, knowledge management and capacity building
Of the individual targets, the GBIO will form a cornerstone of efforts to meet Target 19: “By 2020, knowledge, the sciencebase and technologies relating to biodiversity, its values, functioning, status and trends, and the consequences of its loss, are
improved, widely shared and transferred, and applied.”
The GBIO will also provide important support for meeting several other targets, across all of the five strategic goals.
Source: Aichi Biodiversity Targets. https://www.cbd.int/sp/targets/Delivering Biodiversity Knowledge in the Information Age

What you can do

If you run a regional, national orinternational biodiversity organization

The overall aim of this document is to outline the proposed
GBIO framework and its interdependent components, andto make the case for its adoption. It also offers a snapshotof what progress has already been made and priorities forthe short, medium and long-term future, as well as thesteps needed to take it forward. The GBIO is intended to
be a dynamic and interactive process, and the website atwww.biodiversityinformatics.org will be updated with projects,
ideas and funding sources proposed by the community,
providing much more detail about the individual components
as they evolve over time. Please visit this website and shareyour ideas and expertise.

We invite you to build the GBIO framework into your mission
and align your ongoing and project work to take into accountthe components outlined here. We also invite you to mobilize
any relevant collections you hold, in whatever form, and sharethem freely and openly.
The priority steps will be to identify which components you
can best support and how you can align your planned andexisting work with the GBIO framework. If you have run
successful pilots or projects in any of the component areas
you should share these and scale them up, while piloting
any promising new approaches and adopting best practicefrom elsewhere. Any disincentives to sharing or annotating
data should be dismantled.

If you’re a policy maker
We invite you to look at the relevant legislation and makethe changes necessary to underpin a culture of data sharing,
to provide the right policy incentives, and above all to fundthe data mobilization effort. We also invite you to work withresearchers to develop the decision-making tools you need tosupport your conservation policies and to make use of them.
The priority steps will be to communicate data and analysis
needs in relation to biodiversity, to fund digitization efforts,
to develop long-term national or regional data repositories,
and to put in place open access legislation to ensure data
are made freely and persistently available in appropriate
and usable forms.

If you’re a funder
We invite you to align your funding criteria with any or all of
the components listed here, and make collaboration with the
GBIO effort a condition for funding relevant projects. We also
invite you to consider how long-term data mobilization andstorage can be supported.
The priority steps will be to develop policies ensuring
project data are made freely and persistently available inappropriate and usable forms and to fund projects working
within the GBIO framework outlined here.

If you are an owner or custodian of
biodiversity data
We invite you to make this information permanently, freely
and openly available for reuse, so that it can form part of thewider data resource. If you have information that is not yet
digitized, we invite you to take advantage of the incentives andresources available to mobilize these resources as quickly as
possible.
The priority steps will be to agree common systems
with other data custodians for serving data, managing
annotations and recognizing onward use of data; andto adopt common standards, tools and licences where
possible. It will also be important to collaborate withother data providers to recognize, develop and share
best practice in priority areas such as digitization, error
detection and correction, annotation systems, and crowd
sourcing.

8/9

If you’re a biodiversity researcher
We invite you to consider how your research and projectwork could contribute to any or all of the individualcomponents described here and to build their goals into any
future proposals you make. We also invite you to consider
contributing to any follow-up activities to this framework inwhatever capacity as well as contributing corrections andannotations to data where possible.
The priority steps will be to help us understand in moredetail where the knowledge and information gaps are thatbiodiversity informatics can address, and to identify how
you can help to bridge them. You may wish to identify themost promising modelling and visualization approaches
and work with others to help establish the requirements(data, standards, workflows and techniques) needed tomake them a reality.

If you’re an IT professional or
biodiversity informatics specialist
We invite you to consider what standards, technologies,
protocols and tools you could deliver in support of thecomponents described here, and to contribute your technicalexpertise to any follow-up activities to this framework. We also
invite you to consider what opportunities the mobilization of
biodiversity information offers to create exciting new tools.
The priority steps will be to work with researchers
to identify gaps in existing standards and identify
commonalities and map overlaps in standards fromother disciplines. Developing and refining modellingand visualization tools will also be a high priority area.

If you’re a member of the public
We invite you to investigate the opportunities to share yourknowledge and passion for biodiversity through participationin biodiversity-related science projects and to lobby yourgovernment and other organizations to increase support forbiodiversity research and for policies to encourage free andopen access to data.
The priority steps will be to encourage development of
resources making it easier for the public both to contributebiodiversity records, and to discover biodiversity data andinformation in accessible formats.

Delivering Biodiversity Knowledge in the Information Age

What happens next?
The GBIO framework outlines the priority steps we areinviting individuals, organizations and nations to take. Eachcomponent also provides a more detailed set of actions that,over the next five to ten years, would make the vision outlinedin the framework a reality. A GBIO working group will planfollow-ups to this document, helping to track projects, funding
and ideas around the framework, and develop mechanisms
for monitoring progress in each of the focus areas andcomponents. The website (www.biodiversityinformatics.org)
will enable people and organizations to register projects andoffer support for particular activities. The website will also act
as a clearing house for ideas and tools, and showcase some of
the results as they are developed.

Members of the GBIO working group will also collaborate
with key networks and processes such as the Convention on
Biological Diversity and the Intergovernmental Science-Policy
Platform on Biodiversity and Ecosystem Services (IPBES) toensure that the framework and its components help to meet
key biodiversity information needs in coming years.
A second Global Biodiversity Informatics Conference is plannedfor 2014, and this will be an opportunity to follow up on theframework presented here. Please watch the website for details.

10/11The GBIO framework
The framework described here is organized into four focus areas,each of which is broken down into several core components. Allfour interconnect and strengthen each other; all four are needed
if biodiversity informatics is to achieve its full potential. Eachfocus area – and the individual components within them – can be
progressed independently but as they develop they should start
to feed into and reinforce each other, making them together far
greater than the sum of their parts.

CULTUREDATAEVIDENCE

UNDERSTANDING

At the root lies the culture focus area which puts in place thenecessary elements to turn biodiversity information into acommon and connected resource – stable and persistent storage,pooled expertise, the culture and policies to support sharing,and common data standards. Building on those foundations, the†The diagram below shows how the focus areas interconnect,
and breaks them down into their individual components.

Multiscalespatialmodelling

Trends andpredictions†

Modelling
biologicalsystems†

Visualizationanddissemination†

Prioritizing
new data
captureFitness-for-use
and annotation

Taxonomic
framework

Integrated
occurrencedata

Aggregatedspecies trait
data

Comprehensive
knowledge
accessPublishedmaterials

Collections andspecimens

Field surveys
andobservations

Sequences andgenomes

Automated,
remote-sensed
observations†

Open accessandreuse culture

PROGRESS KEY:

data focus area aims to accelerate the mobilization of data fromall sources, unlocking the knowledge held in our collections andliterature, improving data quality and filling in gaps, and bringing
observations and data from all sources from satellites to genomes
online. The evidence focus area deals with refining, structuring
and evaluating the data, to improve quality and place it withina taxonomic framework that organizes all known information
about any species. Finally, the understanding focus area enables
a broader synthesis, providing the modelling tools to enable us tolook at whole ecosystems, make better policy decisions and react
to any changes.

Datastandards

Persistentstorage andarchives†

Significant

Some

Considered to be of high urgency, but have made limited progress to date

Policyincentives†

Limited

Biodiversity
knowledge
network

MinimalDelivering Biodiversity Knowledge in the Information Age

Focus area A: Culture
Putting the foundations in place to makebiodiversity data an openly shared, freely
available, connected resource.
Without stable foundations, all of the other components
outlined here risk proving both fragile and fragmented. We
cannot fill the gaps in our understanding of biodiversity
without pooling the past, present and future efforts of many
projects and individuals — and making sure that the resulting
data are neither lost nor wasted. In an ideal world, every
fragment of biodiversity knowledge generated would be held
as part of a common global resource — able to be preserved,
searched, found, reused and linked in ways its creator neverimagined.
With the development of information and communication
technologies in the last decades, knowledge production
increasingly involves actors from different disciplines,
specialisms, institutions, countries and cultures.14 Thisis particularly true in areas such as biodiversity and thepromotion of sustainable development. Communication is
crucial throughout the process, and the traditional paradigmof sharing scientific data and results only through publications
in books and specialized journals is not sufficient.15 Nor is it
enough simply to make data available on the Internet. The
data infrastructure must be capable of offering long-termpreservation and curation of data, searchable both by humans
and by machines, and of serving the data in useful and usableformats which are interoperable with other systems.
The culture focus area addresses this by directing efforts on
the changes in community attitudes and processes needed
to make biodiversity data open, shared and reusable; and thesocial, legal and technical underpinnings needed to maintainthose data resources in a stable and permanent form. It also
covers incentives to encourage researchers to make full use of
the opportunities offered by this infrastructure. The goal is toengage the whole community in developing and managing
the world’s biodiversity data and ensuring they remain freely
available to all. This will build on some of the same tools andcultural changes as those used by other fields of research anddata management.

Components:• A1. Open access and reuse culture: make open sharing
		 of data standard practice through public funding		 and other incentives and through proper attribution
		 and recognition of primary data resources, data creators
		 and curators, including individuals as well as institutions.
• A2. Data standards: deliver a flexible set of data		 standards that support the reuse and interoperability
		 of all biodiversity data.
•
		
		
		

A3. Persistent storage and archives: provide a
distributed network of data repositories for all types of
biodiversity data, along with consistent handling of
metadata, identifiers, licences, tools and services.

•
		
		
		

A4. Policy incentives: ensure that public policies,
legislation and funding initiatives at all scales combine
to reinforce this strategy and support its individualcomponents.

•
		
		
		
		
		

A5. Biodiversity knowledge network: create thetechnical infrastructure to support curation andannotation of data using the best-available community
expertise, in a way that makes such curation immediately
visible to future users as well as providing feedback todata holders.

Progress: With the exception of data standards, where there
has been a long-standing community effort to develop
common vocabularies and structures, progress at the global
scale has generally been limited in this area although
individual countries have made significant advances towards
making scientific data openly accessible.
Priorities and dependencies: This focus area acts as afoundation, enabling all of the other areas rather than directly
depending on them. However, we anticipate that as the otherelements develop, they in turn will feed back into this focus
area, setting up a cycle of positive reinforcement. For instance,
as more systems are built combining multiple data sources,
the underlying data standards (A2) and persistent storage
and archives (A3) will need to be refined to support them, inturn enabling more sophisticated systems to be built. Within
the focus area, the first priority has to be the developmentof policies that promote an open access and reuse culture(A1) as without a willingness to allow data not just to be used
but also to be annotated and combined in unanticipatedways, the whole enterprise will fail. In practice, this will require12/13

Encyclopedia of Life

http://eol.org/

PANGAEAGenBank

http://www.ncbi.nlm.nih.gov/genbank/
An open access, annota
ted collection of all
publicly available DNA
sequences. GenBank ispart of the International
Nucleotide Sequence
Database Collaboration, which also comprises
the DNA DataBank of Japan and the European
Molecular Biology Labora
tory. Data sharing
between these three org
anizations occurs
daily. In addition, mostjournals require DNA
sequences cited in article
s be submitted to a
public sequence reposit
ory, such as GenBank.

DATA

ewww.pangaea.d
renced datalibrary for georefe
An open accesstaset isdachm research. Ea
from earth syste
OI), with
(D
r
ifie
nt
Ide
t
al Objec
assigned a Digit
ensuresmstesy
identified. The
which it can berough a
th
t
en
nt
co
its
of
ility
long-term availab
titutions.
the operating ins
commitment of

CULTURE

having the right policy incentives (A4) in place – or at least to
remove disincentives to providing access to data. Both of thesecomponents will also benefit from a positive feedback loop:
data sources will gain prestige from being involved in highprofile projects, encouraging other data providers to join in.
Similarly, as users and data sources alike see benefits from thebiodiversity knowledge network (A5), through fitness-foruse and annotation (C1) it will be more widely adopted andused, generating network effects.

An initiative to bring tog
ether information on spe
cies
into a single database,accessed via an online
portal.
Data contributions to EOL
come from individuals
andorganizations, and are rev
iewed by a communityofvoluntary curators who
help improve the qualityofcontent on the website.
EOL has created three lev
els
of curators, based on eac
h person’s expertise andexperience. Each curato
r’s work is displayed ontheirprofile page, and commu
nity members can assesseach other’s contributions.

Darwin CoreEVIDENCE

Archive
http://rs.tdw
g.org/dwc
A biodiversit
y informatics
data standard
terms from thwhich usese Darwin Co
re body of st
produce data
andards tosets for spec
ies occurrenc
data, as welle or checklist
as accompany
ing metadat
provide a staba. It helps
le, standard reference for sh
information
aring
on biologicaldiversity.
d
Office of Science anyTechnology Policp/v/administration/eo.net/
www.canadensys
to unlock thetwork which aims
A Canada-wide neons. Data are
cti
lle
co
l
biologica
information held inard, and a centralndDarwin Core sta
the
ing
and
us
ed
sh
bli
pu
twork’s specimen
es access to the ne
of
ase
tab
web portal providDathemwell as names fro
geospatial data, as
the Catalogue ofnts (VASCAN) and
Pla
lar
scu
Va
Canadiand more than 1.2
steho
2013, Canadensys
Life. As of Augusto available throughm 20 collections, als
million records fro
ility (GBIF).
Fac
ity Information
the Global Biodivers

The projects and initiatives highlighted here are for illustration only – many
more contribute to the objectives of GBIO. Each will often cut across several
focus areas, as indicated by the icons (see page 11 for the icon key).

UNDERSTANDING

Canadensys

gowww.whitehouse.
t
ou
ab
ostp/
to
ited States Congress
Established by the Un
ce and
en
sci
of
s
ect
on the eff
advise the President
nal affairs. In
atio
ern
int
d
an
stic
technology on dome
ents forunced new requirem
2013, the OSTP annot policies
op
ad
to
ts
jec
pro
ch
publicly funded resear
de
ma
er
Ord
ive
. An Execut
on open data accessnorm for
the
ta
da
ble
da
rea
open and machinen.
government informatio

Delivering Biodiversity Knowledge in the Information Age                 A1. Open access and reuse culture
Making data sharing the norm.
Progress: some progress (issues understood, needs operational implementation)
At the national and institutional level, individual researchers and projects need to build data sharing into their daily work.
Researchers are not necessarily rewarded for providing and improving raw data, but are judged largely on their publication record.
This gives them an incentive to control access to their datasets until after they have published their results. As a consequence,
datasets are either built for a particular project or publication and access is restricted; or sharing of data becomes a neglected
effort, operated on an inadequate budget despite its great value to the community at large. The whole of this framework relies onfreely available, reusable data, yet even now some new data are being published in restricted forms, so it is important to tackle thisas a matter of urgency.
In some fields, such as genomic research, publication relies on the underlying data being deposited in a common data store suchas GenBank.16 The next step will be to broaden this to other fields, so that funding or publication is compromised if the underlying
data are not made permanently or openly available.
In the short term, the priority will be to implement mechanisms for citing data, including use of DOIs and data standards (A2),and promoting recognition of data owners and data managers, in concert with changes to policy incentives (A4) to use data
sharing as a criterion for awarding funding. In the medium term, providing data and making improvements to data quality should
become valued as a service to science, giving institutions and individuals an incentive to make data available. In the long term,
data sharing through permanent archives or national repositories will become part of the language of science, just as citing
publications or type specimens is now.

                 A2. Data standards
Ensuring data can be understood and used across systems and across disciplines.
Progress: significant (significant progress made, further investment needed to complete)
Simple and clear but rigorous data standards ensure that both machines and humans can interpret and use data arising fromthousands of different sources. As community-wide efforts accelerate the digitization and collection of data, including from
unstructured and non-traditional sources (focus area B), having the right standards in place from the start will be crucial.
Aggregating, integrating and simply discovering data (focus area C) all depend on common structures and vocabularies to work
well. Closing gaps in the existing set of standards and driving the uptake of robust and well-supported standards are therefore
urgent tasks.
The importance of common data structures has long been understood in the biodiversity informatics community, with
Biodiversity Information Standards (TDWG)17 leading efforts to develop common standards. The next steps will be to workwith the other component areas to identify where the most important gaps are in existing standards and whether there arecommonalities and overlaps with standards from other disciplines.

14/15CULTUREIn the short term, the priority will be to develop interoperable standards and common vocabularies to support planned data use
and reuse in all components of this framework. In the medium term, as the use of the underlying data sources becomes moresophisticated these standards will evolve from simple data structures and vocabularies. In the long term, they will develop into
structures capable of supporting full semantic reasoning, fully integrated with the relevant standards from other disciplines, fromgeo-sensing to socio-economics.

                *A3. Persistent storage and archives
Creating a stable data archiving infrastructure to ensure no data are lost or mislaid.
Progress: limited (needs further development)* Considered to be of high urgency, but have made limited progress to date.

UNDERSTANDING

In the short term, clear recommendations are needed for researchers and projects on how best to organize their data to simplify
future archiving and curation including providing stable identifiers, and for institutions and research infrastructures to plan storage
facilities that will guarantee long-term access and interoperability. In the medium term, national publicly funded data repositories
should be established which follow these recommendations and provide a free, or low-cost, persistent home for research data andkey citizen science data products. In the long term, global collaboration should ensure that all data sets are maintained throughreplicated copies.

EVIDENCE

Biodiversity Information Standards (TDWG) and the Global Biodiversity Information Facility (GBIF) have already worked tostandardize some common protocols and to build a consensus around persistent universal identifiers for biodiversity data.18 Such
identifiers are essential to allow all users and applications to refer reliably to particular datasets or records. However, these offer
limited benefits unless the associated data also remain reliably accessible in stable locations on the web and in usable formats.
Significant planning and investment is required to deliver persistent repositories that guarantee long-term access to data, andthat can be developed to offer additional services to support community peer-review and annotation and to ensure that thedata remain accessible and usable as data access technologies change. Most datasets are today held in private or institutional
databases which cannot guarantee this stability.

DATA

The costs of digitizing and organizing data are significant and we cannot afford either to lose data or to digitize a second time.
Many of the records already created are held in legacy systems or systems created for short-term projects whose funding is ended,making them vulnerable to being lost or taken offline. Internet technologies are fast moving and constantly evolving, meaningthat even when records still exist, links to them may be broken or identifiers changed. Data sources may disappear, go offline orchange protocols, making any systems built on top of them unreliable and increasingly costly to maintain. Without persistent,
long-term digital archives being available to house the data gathered in focus area B, or to form the foundation for the tools andaggregators in focus area C and focus area D, we risk wasting time, money and effort. As a key underpinning for the whole of the
GBIO framework – and one where very limited progress has been made – providing stable data storage is a matter of very highurgency.

Delivering Biodiversity Knowledge in the Information Age                  * A4. Policy incentives
Creating a policy framework that actively encourages the sharing and reuse of biodiversity data,
however the data have arisen.
Progress: limited (needs further development)
Science is built on shared knowledge, yet the incentives and funding mechanisms that support research sometimes act against
an open data culture. Governments are understandably keen to protect national interests, including data gathered at taxpayers’
expense, while institutions sometimes see their data stores as a possible source of income or the basis of future research funding.
Even where policies support open access, short-term project funding does not support the ongoing maintenance and serving of
data, and funding bodies are reluctant to support the sort of day-to-day running costs that are needed to provide long-term data
access. As this component enables the vital open access and reuse culture (A1) it should be tackled as a matter of urgency.
Many governments now have open access legislation at least for government-funded data. For example, the United States Officeof Science and Technology Policy (OSTP)19 recently mandated all federal research agencies to have clear policies to increase
open access,20 and the South African National Biodiversity Institute (SANBI)21 has legislative responsibility to organize national
biodiversity information.22 The next step will be to encourage all governments to follow suit.
In the short term, the priority should be to concentrate funding on projects that make their data freely and openly available to allusers, targeting the components in focus area B. In the medium term, governments and funding bodies should ensure that their
guidelines support open access data, both de jure and de facto, by ensuring the resulting data archives are on a sustainable footing
both technically and financially, in concert with the efforts to create persistent storage and archives (A3). Governments andlegislators should ensure that laws favour open access and enhancing biodiversity knowledge. Sensitive data must be dealt withas an exception. In the long term, all projects should build permanent data access into their plans, with sub-national, national andinternational structures in place to support it.

                  A5. Biodiversity knowledge network
Benefitting from the expertise of the whole global community.
Progress: limited (needs further development)
Researchers in biodiversity have long had a culture of curating and annotating data — from identifying specimens to correcting
and cleaning up entire downloaded datasets. These efforts are a key part of the data validation process: even with the best
automated tools, identifying and correcting most errors still requires an expert, human eye. Yet these annotations are not always
made available to the original data owners, and even when they are, there may be neither the resources nor the mechanisms inplace to incorporate them. As a result, mistakes get replicated or have to be repeatedly corrected, duplicating effort, while there islittle incentive for researchers to continue to correct and annotate records more widely.
Data aggregators generally encourage users to report mistakes; several GBIF national nodes have developed systems of data
curation, including amateur networks to curate citizens’ observations23 while the EU OpenUp! project24 includes a data quality
toolkit for GBIF data. Some projects are already using expert curation for aggregated data, for example the Encyclopedia of Life25* Considered to be of high urgency, but have made limited progress to date.

16/17CULTUREand the Fish Barcode of Life Initiative (FISH-BOL).26 However, too often these use ad hoc systems and require an extra effort on thepart of the contributors, especially if they want to make corrections in many different sites, while data providers or publishers may
not feel confident in trusting changes submitted over the Internet. The next step will be to agree with individual institutions andprojects how data cleanup efforts can be recognized and valued, putting the incentives in place to ensure that annotations are
made and fed back into the system. In combination with the fitness-for-use and annotation (C1) component – which considers
the systems needed to enable annotations to be integrated into the data – this will be the first step towards making distributed
data curation the norm.
In the short term, the priority should be developing a shared identity management system for contributors, whether professionals
or citizen scientists, so that they can have a common identity and contribution history across platforms — particularly the key data
networks and publishers. In the medium term, key data networks will be able to trace back any changes to the original contributor
and over time it will be possible to use metrics to value contributions automatically, based on the contributor’s past history. In
the long term, annotating data will become the norm and the curation of data will come to be considered a shared responsibility
among the biodiversity community.

DATA
EVIDENCE

UNDERSTANDING

Delivering Biodiversity Knowledge in the Information Age

Focus area B: Data
Mobilizing biodiversity data from all sources andorganizing it in forms that can support large-scale
analysis and modelling.
Over the centuries, our knowledge of biodiversity has been
built from many millions of observations and measurements,
as well as countless publications which are now held ina variety of digital and non-digital forms. These resources
may have been originally collected for a single purpose, but
could further our understanding in many other fields. Whilesome of these are structured and standardized so that they
are automatically accessible, the majority are not, meaningthat they can only be reused with difficulty. As a result, theefforts of both professional biologists and, increasingly, citizen
scientists are not achieving their full potential, leading towasted time and duplicated effort.
The data focus area addresses this by putting in place the tools
and standards to ensure that such information is gathered
once but used many times. It offers ways to accelerate andcoordinate current digitization and data gathering efforts andto ensure that the resulting information is as useful and freely
accessible as possible.
Components:• B1. Published materials: developing mechanisms
		 to extract the biodiversity data currently embedded in		 publications and other, multimedia formats and to		 provide them as freely available, standardized and		 structured information.
• B2. Collections and specimens: developing and sharing
		 more efficient techniques to accelerate the efforts to		 digitize and capture historic data from collections.
•
		
		
		

B3. Field surveys and observations: capturing all
biodiversity observations, including sounds and images,
and making them available as soon as they are made, orwithin a defined period.

•
		
		
		

B4. Sequences and genomes: capturing all relevant
data from genomic activity, including voucheredreference sequences, environmental metagenomics,
genetic variation and full genomes.

•
		
		
		
		

B5. Automated and remote-sensed observations:
exploiting opportunities for automated and semiautomated recording and identification of species andpopulations from sources ranging from satellite images
down to automated gene sequencing.

Progress: This focus area is probably the most advanced of
the four, with the community already undertaking significant
digitization projects and most new information now
automatically held in digital form. However, such is the scale ofthe task that future projects will need to use more automation
and algorithmic techniques. Moreover, digitized information of
all kinds needs to be standardized and given a structure thatenables it to be automatically processed: the importance of
this task should not be underestimated.
Priorities and dependencies: Completing this focus area
depends primarily on the right policy incentives (A4) andpolitical will: governments and funding bodies need to provide
the substantial resources required. An open access and reuse
culture (A1) will encourage institutions and copyright holders
to share the resulting information while persistent storage
and archives (A3) will ensure the digitized material has apermanent home. In order to scale up efforts, the work can nolonger be confined to the professionals: projects will need toharness the skills and enthusiasm of the amateur communityof ‘citizen scientists’ both to gather and to annotate data,
and the infrastructure will need to be in place to handle
these contributions (A5. biodiversity knowledge network;
C1. fitness-for-use and annotation). With more distributed
data gathering efforts – and more disparate sources of data
becoming available – clear and interoperable data standards(A2) will be essential and the parallel development of acomprehensive taxonomic framework (C2), adequate spatial
and temporal tags through integrated occurrence data (C3)and online identification tools based on aggregated species
trait data (C4) will do much to improve data quality. The
components of this focus area will to a certain extent dependon each other: accelerated collection and specimen (B2)
digitization efforts will benefit from data extraction techniquesdeveloped for published materials (B1), while remote andautomated sensing tools (B5) will undoubtedly benefit fromrefinements developed for field surveys and observations(B3).

18/19Biodiversity

www.biodive

Heritage Librsitylibrary.orary

Atlas of Living Au

www.ala.org.australia

The ALA aims to cre
ate a national datab
ase of allof Australia’s flora an
d fauna, accessed thr
ougha single, easy-to-use
website. It engages
thepublic through a nu
mber of innovations
such asthe Volunteer Portal,
encouraging users to
help
digitize informationfrom specimen labels, field
notes and survey she
ets from various Austra
lianmuseums. ALA also
produces software too
ls tohelp capture field data.

iNaturalist

EVIDENCEde project
Moorea Bioco
code.org/

DATA/
www.inaturalist.org
zen
y of naturalists and citi
An online communit
vations
ser
ob
s
cie
spe
g
rin
scientists built on sha
bsite or from a mobile
via the iNaturalist weands may include images
ord
application. Data rec
ed
tat
no
an
be
can
d
nates, angeographical coordi
ed
firm
con
h
wit
ta
Da
by the community.
Globalblished through theidentifications are pu
IF).
(GB
ility
Fac
n
atio
Biodiversity Inform

io
http://mooreaba genetic libraryg survey to build
A DNA barcodin, an island inrea
ial life on Mooof all non-microb
stematicallySpecimens are sy
French Polynesia.
quencesseticfield and genecollected in therary. The
lib
ss
ce
ac
en
op
this
recorded to build
Genomicofkortwpart of a ne
Moorea Project isolo‘bi gical
ed at taking theObservatories aimt.
pulse’ of the plane

CULTURErg/
A consortiumof natural hist
ory and botanithat cooperat
cal libraries
e to digitize the public dom
and journals heain books
ld within their collections. BH
also obtained
L haspermission fro
m rights holdavailable conters to makeent that is under copyright. As
2013, the BHLof Augustportal provided
access to mor
million pages
e than 41
from over 60,000 separate tit
les.

Movebank

https://www.m

The projects and initiatives highlighted here are for illustration only – many more contribute to the objectivesof GBIO. Each will often cut across several focus areas, as indicated by the icons (see page 11 for the icon key).

UNDERSTANDING

ovebank.org/
An online datab
ase which allow
s the sharing,
managing and arc
hiving of animal
tracking
data. The inform
ation helps us understand how
individuals and po
pulations move
within local
areas, migrate ac
ross oceans andcontinents
and evolve throug
h millennia. Researchers who
contribute dataretain full ownersh
ip and control
over the level ofaccess to their data. Movebank
also provides tools
for making basic
edits to thedata.

Delivering Biodiversity Knowledge in the Information Age                 B1. Published materials
Using data mining and semantic tools to turn unstructured and inaccessible data into information.
Progress: some progress (issues understood, needs operational implementation)
Published materials – primarily printed literature, but also images, videos and other multimedia forms such as sound recordings– have long served as the primary means for disseminating biodiversity knowledge. Along with collections and specimens (B2)they also form the primary source of species-level trait and descriptive data, vital for identifications and taxonomic research. Much
progress has been made by research institutions and by the Biodiversity Heritage Library (BHL),27 scanning historical materials into
digital formats, while new materials are almost exclusively developed as digital objects. Nevertheless the information in theseresources remains largely inaccessible to automated processing due to a lack of internal structure and mark-up, and for older
literature errors introduced during the scanning process. Multimedia objects need consistent indexing to make them properly
discoverable. Consistent standards, including text recognition standards, keywording and indexing, data mining techniquesand crowd sourcing will enable the community to step up the rate at which such data are made fully accessible. The resulting
information, and the tools to generate it, also need to be made freely available to all. Despite progress in recent years, the scale ofthe task and its importance to the framework means this component requires continued and long-term investment and it will beurgent to find ways to accelerate and streamline the process.
There are already a number of initiatives working on the relevant tools and techniques with research projects investigating
automated image extraction and crowd-sourced tagging (BHL),28 data mining (EOL)29, semi-automatic (GoldenGATE30) andautomatic markup of taxonomic descriptions (MARTT [MARkupper forTaxonomic Treatments],31 TaxonFinder,32 TaxonGrab33,
FAT [Find All Taxa]34), and handling multiple languages (SciELO [Scientific Electronic Library Online]35) as well as using structured
data in taxonomic publications. The next steps will be to catalogue and define the types of unstructured biodiversity data available(TaxPub, TaxonX, taXMLit)36 and understand their particular challenges, and to agree standards for future publication in a form
that makes the data immediately available not just to experts but to searches and automated processing.
In the short term, the priority will be to build on some of the existing pilots and implement some full-scale crowd sourcing andautomated data mining projects. In the medium term, the software behind such projects should be made available as open source
tools. Countries will start to establish their own bibliographies of national biodiversity. New publications will increasingly comein an enhanced, semantically structured form.37 In the long term, such enhanced publication will be the norm and automatedand semi-automated data mining tools will be freely available for unstructured biodiversity data. As a result, complete bodies ofthematic or geographical information will be progressively made available as linked datasets.

                 B2. Collections and specimens
Accelerating the rate at which historic specimen-based data are made discoverable and accessible.
Progress: significant (significant progress made, further investment needed to complete)
The past 250 years of biodiversity research have resulted in a treasure trove of preserved specimens held in the world’s natural
history collections, and they are still being added to today. These collections form the irreplaceable foundation of our knowledgeof biodiversity, as well as a source of DNA samples for future analysis. Digitizing the data embedded within these specimens

20/21In the short term, natural history collections should continue to develop and document accelerated digitization techniques
which organizations like GBIF and its nodes can use to develop training materials and programmes for smaller institutions. In themedium term, GBIF and digitization projects should develop global infrastructure to support accelerated workflows, including thegeneration of identifiers and crowd-sourcing clearing houses. In the long term, fully automated mass digitization should eliminate
most bottlenecks, clearing the way to complete the digitization effort.

DATA

In recent years, museums and herbaria have increasingly begun to capture the data contained in these specimens and their labels,
and in accompanying field notes, making them available through aggregators such as GBIF, its network of national nodes anddata publishers, and through thematic networks such as the Ocean Biogeographic Information System (OBIS).38 But the work is
labour intensive and their efforts are dwarfed by the scale of the task. Some have begun to accelerate digitization efforts throughexploring automation, adopting highly-efficient workflows, and the use of volunteers. Others have pioneered crowd sourcing
through making specimen images available online, for example the Biodiversity Volunteer portal of the Atlas of Living Australia(ALA),39 and the ‘Herbonautes’ initiative of the Muséum National d’Histoire Naturelle in Paris.40 The next step will be to document
and share current best practices to help institutions choose the optimum approach to accelerate digitization. Institutions will needto prioritize digitization, while funding bodies and governments will have to make the resources available to develop the skills
and deploy enough people to accelerate the task. Data quality improvements are also fundamental as digitization rates accelerate,
whether through automated tools, or feedback mechanisms via the biodiversity knowledge network (A5) and fitness-for-use
and annotation (C1).

CULTUREdramatically improves our understanding of species distributions, morphology and population variation, including changes overtime. As with published materials (B1), the scale of the task and its importance to the framework means this component requires
continued and long-term investment. Widespread development and adoption of the most efficient techniques could dramaticallyaccelerate current digitization efforts, making continued improvement of methodologies an urgent task.

                 B3. Field surveys and observations

Progress: significant (significant progress made, further investment needed to complete)

Some small-scale projects have piloted mobile field capture systems, such as the Moorea Field Information Management System41
and the FieldData software developed for Atlas of Living Australia,42 while hundreds of citizen science projects have developed
tools for distributed data capture and online identification. The next step will be to review existing tools and approaches anddocument the best, providing guidance for projects and users on methodologies suitable for citizen science groups, consultantsor professional researchers. The United Kingdom’s Natural Environment Research Council (NERC) Centre for Ecology and Hydrology(CEH)43 has made a valuable contribution to this effort through a detailed review and analysis of existing citizen science projects
and a guide to future activities.44

UNDERSTANDING

Much of the biodiversity data collected in the field stays trapped for years in notebooks or stand-alone databases before
being transcribed into more accessible locations, if at all. Many citizen science projects engage the wider community in data
gathering projects that could add significantly to our knowledge if they were integrated with other sources of biodiversity data.
Increasing numbers of projects are using georeferenced images and sound recordings to support and enhance field observations.
Improvements in mobile and handheld technology now make it possible to enter data directly from the field into institutional
databases and to make them immediately accessible.

EVIDENCE

Making field data immediately accessible and interoperable from the moment it is collected andengaging the public in its collection.

Delivering Biodiversity Knowledge in the Information Age

In the short term, the priorities will be to build on the existing pilot data capture tools, ensuring that the tools integrate withresolution services using globally unique identifiers (GUIDs)45 and that they use common standards for data exchange, integration,
identity management and contribution tracking. In the medium term, fully integrated open source mobile applications should
be widely available to capture field data and support species identification, while networked communities will develop aroundcommon interests (taxonomic, regional or thematic). In the long term, some funding and permits might be dependent on projects
using real-time mobile data capture, and it will be possible to target gaps dynamically based on data gathered in this way.

                 B4. Sequences and genomes
Incorporating data arising from genomic and genetic exploration of the living world.
Progress: significant (significant progress made, further investment needed to complete)
Molecular research – including the analysis of genomic information, or biodiversity genomics – contributes to our understandingof the biology and evolution of species, and increasingly offers a way of detecting and monitoring organisms in the environment.
Eco-genomic sampling and sequencing can provide data on the composition of biological communities; for some communities,
especially in the microbiome, it may be the only feasible way to determine the species they contain. Mapping genes could
enable the discovery of individual species traits, while measuring genetic variation across a population or populations provides
information about their overall health, their habitat and the extent to which they are isolated or interconnected.
Databases of reference sequences such as DNA barcodes can map genetic data into the wider world of biodiversity information
by tying them to species and vouchered individuals. Collaboration through initiatives such as the Genomic Standards Consortium(GSC)46 has started the process of mapping genomic-level data standards to those recording biodiversity observations of named
species.47 Place-based genomic studies offer an unrivalled opportunity to combine best practice, standardized data capture,
uniform methods of analysis and rigorous and systematic characterization of DNA, the foundational layer of biodiversity, toadvance our knowledge of biodiversity on earth.
Of note in this respect is progress towards a network of Genomic Observatories (GOs),48 a combined initiative of the GSC andthe Group on Earth Observations Biodiversity Observation Network (GEO BON).49 This is an international effort to bring together
premier sites engaged in long-term research programmes to help contextualize ongoing and new genomic observations at the
DNA level. Leading sites in this consortium include the island of Moorea (see also B3 and project profile); and the ‘L4’ site in theWestern English Channel, which has been studied for more than a century and is now one of the best studied sites in the world interms of metagenomic information on microbial communities.
In the short term, the priority will be to develop the Genomic Observatories network of sites into a range of case studies on the
integration of biodiversity genomic work in the content of long-term ecological, evolutionary and environmental studies, with the
production of training materials and best-practice guidelines for gathering genomic-level data. In the medium term, research sites
will work to generate well-contextualized genomic observations in line with global data standards. In the longer-term, genomic
observations will enable more systems-based approaches to the study of biodiversity and ecosystem services, providing data on
interactions within an ecosystem and contributing ecosystem-wide biodiversity models.

22/23                  *B5. Automated and remote-sensed observations
CULTURE

Harnessing automated monitoring technology to provide planet-wide surveys, filling in the gaps leftby traditional field research.
Progress: limited (needs further development)

The Icarus Initiative (International Cooperation in Animal Research using Space)50 is working to establish a remote sensing platform
for tracking small organisms while MoveBank51 provides an online platform for sharing tracking data. Continuing improvementsin the technology, especially in earth observation imagery, and the reduced costs of accessing the data, will dramatically increase
the volume of data available. Currently and for some time to come, human expertise will still be needed in some forms of remotesensing such as acoustic monitoring and camera traps to extract and process the data if they are to be correctly interpreted, forexample in identifying species, although there is scope for using crowdsourcing for these tasks.

* Considered to be of high urgency, but have made limited progress to date.

EVIDENCE

In the short term, the priorities will be to put more standard format data into open repositories from existing land and sea-based
automated sensors and remote sensing, and to develop the algorithms needed to extract the information automatically. In themedium term, the priorities will be to expand remote sensing networks to create a complete global picture of biodiversity at
multiple resolutions. In the long term, automated change detection and data integration will help signal unexpected change andtrigger more intensive conventional field research, helping to prioritize new data capture (D5).

DATA

Field research is labour intensive and it will never be possible for the whole planet to be sampled and monitored in detail, leaving
large gaps in our models. Remote sensing technologies allow the repeated capture of information from any location and/or
over large areas. While camera traps, acoustic sensors and buoys can provide regular observations from the most remote areas,satellites and drones can cover very large areas in a short space of time, generating huge numbers of high-resolution images.
Tracking devices further allow us to follow the movements of species, large and small, in real time. Remote-sensed data canbe accompanied by abiotic observations (such as temperature or humidity), adding further depth to our understanding of
ecosystem interactions. This component is in its infancy in the area of biodiversity research, but its potential to provide otherwise
unobtainable information makes it a priority area for investment.

UNDERSTANDING

Delivering Biodiversity Knowledge in the Information Age

Focus area C: Evidence
Providing the tools to support consistent andcomprehensive global discovery and use of datafrom all sources about the biodiversity of any
defined area over time, covering all taxonomic
groups.
Ultimately, our understanding of the natural world is basedon the data sources addressed in focus area B. For most
purposes, however, what users need are organized views
and discovery tools that enable them to access efficiently therelevant information at the right level of detail, without being
hampered by the need to find obscure data sources, allow fordifferences in taxonomic views or correct for data quality.
This focus area addresses these requirements by providing
services to index content from all relevant resources, theinfrastructure to organize species-level data (traits, interactions
and occurrences) and providing the means for data quality to
be improved, whether manually or automatically.
Components:• C1. Fitness-for-use and annotation: an efficient		 mechanism to enable amateurs, experts and automated		 tools to correct and annotate individual data elements
		 to improve quality and their fitness to be used for		 particular purposes, and to ensure that these annotations
		 have to be made only once.
•
		
		
		

C2. Taxonomic framework: a comprehensive, expertcurated catalogue of species, including data on names,
classification and phylogeny (evolutionary relatedness)and incorporating taxa lacking formal names.

• C3. Integrated occurrence data: bringing together data		 from all sources to document the known occurrences of		 all species in time and space.
•
		
		
		

C4. Aggregated species trait data: providing the tools
to bring together all available data on species traits andinteractions and ensure it is held in forms suitable for use
in digital analysis and modelling.

•
		
		
		
		

C5. Comprehensive knowledge access: making all
published biodiversity knowledge linked and accessible
through the rich indexing of biodiversity literature, data,
multimedia and other resources, including presentationof the information as species pages and via web services.

Progress: Some of this work is already on course andsignificant progress has been made, although further
investment will be needed to complete the process.
International collaboration has delivered key components
for building the taxonomic framework (C2) and work on
integrated occurrence data (C3) is already mature andoperating at a global scale. Mechanisms for recording fitnessfor-use and annotations (C1) are starting to be developedin pilot while many of the individual pieces needed forcomprehensive knowledge access (C5) have been trialled indifferent projects, but not brought together in one coherent
framework. Standards for species trait data and interactions
are starting to be adopted but there is as yet no common
infrastructure in place to capture and query such data in aconsistent way.
Priorities and dependencies: Completing the taxonomic
framework (C2) will underpin almost all of the other work inthis focus area as names provide the key to most biodiversity
data. Enabling a community-wide effort to improve data
quality and fitness for use will need widely accepted data
standards (A2) and depend heavily on the biodiversity
knowledge network (A5) and on the policy incentives (A4)and open access and reuse culture (A1) being in place toencourage it. The more data can be mobilized into digital andstructured forms (focus area B), the richer and more accurate
the information in this layer will be.

24/25

Catalogue of Li
fewww.catalogu

CULTUREeoflife.org/
A global index of
species with infor
mation on
their names, relati
onships and distri
butions. The
Catalogue compil
es data from 115
peer-reviewed
taxonomic datab
ases maintainedby specialist
institutions, andhelps provide ataxonomic
backbone for ot
her data portals
on biodiversity.
The list for 2013
included more th
an 1.4 million
species.

Global Biodiversity
Information Facility

www.gbif.org

SpeciesLinkbr/http://splink.cria.org.
dedeveloped by the Centro
An information system(CRIA) in Brazil,
l
nta
bie
Am
o
açã
rm
Referência em Info
diversity data records. The
to provide access to bio
ludingof data quality tools inc
bersystem offers a num
r
iste
reg
to
rs
use
g
enablinan annotations system
cation of species,
ntifi
ide
the
on
le
mp
comments, for exa
data curator and remainthat are reported to thes.
consulting those record
rs
use
available for futureobwww.morph

ers
lows researchbase which al
ta
da
d
an
An online dataesagphological imyto upload mor
e for the studs, and use thes
sm
ni
ga
obank
ph
or
M
about oreTh.
relationshipsrof evolutionary
al platform fo
provides a virtu
n
tio
ica
eneticplogylphweb apildbullaborate andscientists to coage data.
imithw
matrices

Ocean Bio
Informatiogeographicn System
http://www.io

The projects and initiatives highlighted here are for illustration only – many more contribute to the objectivesof GBIO. Each will often cut across several focus areas, as indicated by the icons (see page 11 for the icon key).

UNDERSTANDING

bis.org/
An online op
en access database of m
species distarine
ributions, now an activity
the Internat
under
ional Ocean
ographic Dat
Information
a and
Exch
Intergovernm ange programme of UN
ESCO’sental Ocean
ographic Co(IOD). Integr
mmission
ating data fromworld, OBIS
institutes around theallows users
to identify bi
hotspots anodiversity
d large-scaleecological pattanalyse spec
erns,
ies dispersions over timeand plot specand space,ies’ locationsw
salinity andith tempera
depth.
ture,

EVIDENCEkMorphobanank.org/

DATA

An intergovernmental
scientific infrastructure
aimed at providing free
and open access tobiodiversity data, via theInternet. GBIF offers asingle online access poi
nt to over 400 million
biodiversity records fromover 10,000 datasets
published by nearly 500
institutions, ranging frommuseum specimens collected from the earliest
days of natural history exp
loration, to current
observations by ‘citizen
scientists’ and monitoringfrom research expeditions.

Delivering Biodiversity Knowledge in the Information Age                 C1. Fitness-for-use and annotation
Creating a network of expertise to manage and curate biodiversity data and permanently capture
data cleanup efforts.
Progress: some progress (issues understood, needs operational implementation)
Over the years, millions of biodiversity data records have been created from a variety of sources, offering varying degrees ofaccuracy and quality, with even the best-quality records affected over time by changes in taxonomy, vocabulary and geospatial
precision. While the biodiversity knowledge network (A5) component will encourage people to contribute their expertise inimproving these records, currently there are few systems in place to make the resulting annotations immediately available or tolink them securely to the original record. This can result in the creation of a new and contradictory version of the original data, or –more often – the changes are completely lost.
A number of projects have begun to look at how annotations can be incorporated into or combined with the original records.
AnnoSys and the Filtered Push project have been developing networked annotation system for biodiversity data,52 while theSpeciesLink network from Centro de Referência em Informação Ambiental (CRIA) allows users to exclude records from searches ifthey have been flagged with geographical inconsistencies.53 The next step will be to agree common standards and mechanisms
for incorporating annotations for data curators to adopt.
In the short term, the priority will be to pilot easy-to-use tools and systems that can capture annotations and tie them to backthe original data record. In the medium term, integrated or online tools for data cleanup will be widespread and available to bothprofessionals and amateurs while data records will increasingly have a curation status indicating what checks and corrections they
have received. In the long term, it should be possible to filter most data by curation status and robust systems will be in place toprovide real-time delivery of community annotations, including mechanisms to resolve any conflicts or contention.

                 C2. Taxonomic framework
Providing a stable and comprehensive catalogue of all species.
Progress: significant progress (significant progress made, further investment needed to complete)
The classification of species has been developed over the last few centuries, and will continue to change in the future as ourunderstanding of evolutionary history develops, and new species are discovered and described. This means that the actualnames applied to specimens, observations or populations are subject to change over time – or according to the person doing thenaming – while specimens or observations may be of currently undescribed species without a formal scientific name at all. Yet
names – vernacular or scientific – are one of the primary means for retrieving and grouping information. It is crucial to be able todraw correlations between names used (currently and in the past) and the taxa they relate to, according to the major classification
schemes and phylogenies in use, and to map between different classifications. Although progress has been made in this area, it is
one of the key underpinning components to make data fully available, and it should be completed as a matter of urgency.
Scientists have been working to create a comprehensive formal taxonomic classification since work began on Species 2000/
Catalogue of Life.54 Some projects such as Centro de Referência em Informação Ambiental (CRIA) already identify taxonomic and26/27

geographical gaps in the record to help identify priorities for research.55 Collaborations are creating architectures that can handle
multiple taxonomies as well as informal and vernacular names through the Global Names Architecture and most recently thei4Life project, contributing to resources such as the GBIF backbone or nub taxonomy.56

CULTUREIn the short term, a clear road map is required to consolidate all these existing activities and deliver a suite of reliable, robust andopen tools for accessing basic information on species names and classifications. In the medium term, global taxonomic expertisemust be organized to fill remaining gaps in the underlying datasets and to address linkages with key species lists such as the IUCNRed List and CITES (the Convention on International Trade in Endangered Species),57 and with approved national species lists. In
the long term, all new species names and descriptions should automatically be integrated into this framework.

                 C3. Integrated occurrence data
Making accessible all data about when and where any given named organism has been recorded.

DATA

Progress: significant progress (significant progress made, further investment needed to complete)
Documenting the distribution of species in time and space may be viewed as the ‘weather observations’ of biodiversity: thefundamental underpinning for any accurate model of existing patterns and trends. All of the data sources outlined in focus area
B will contribute species occurrence records in some form or another, but the key elements of every record need to be brought
together in a more readily accessible and usable form to enable efficient discovery and use.
Many national, regional and thematic efforts such as the Ocean Biogeographic Information System (OBIS)58 and VertNet59 are
already mobilizing significant quantities of data on specimens and biodiversity observations. Mature data standards such as
Darwin Core and the Access to Biological Collection Data (ABCD) schema60 have enabled GBIF to index and organize data fromthousands of such sources. The GBIF data portal already offers access to more than 400 million species occurrence records.61

EVIDENCE

In the short term, national, regional and thematic networks that already handle occurrence data should work to link their data to
global networks. Global activities such as GBIF should enhance their processes to improve understanding and fitness-for-use of all
mobilized data, to provide support for data on species abundance and sampling events, and to ensure that all contributors receive
appropriate acknowledgement and feedback for their work. In the medium term, additional sources of data on species occurrence,
including published materials (B1), sequences and genomes (B4) and automated and remote-sensed observations (B5),should also be integrated. In the long term, globally-connected networks should continuously and automatically process all newobservations and samples of biodiversity.

UNDERSTANDING

Delivering Biodiversity Knowledge in the Information Age                 C4. Aggregated species trait data
Providing the framework to capture all available trait information for any species, and interactions
between species.
Progress: limited (limited existing standardization; needs further development)
Scientists need access to analysable data about the characteristics of organisms and the interactions between them. Being able tocapture, index, query and curate such data will revolutionize how we understand large-scale biological systems. This will enable us
to build more accurate models of how they will behave over time and under changing conditions, and to create a new generationof identification tools.
The community has already developed some major data repositories. For traits these include: TraitNet, TRY, LEDA, MorphoBank,
Animal Diversity Web, the Phenoscape KnowledgeBase, species traits in the Encyclopedia of Life and a growing number of modelorganism and agricultural resource databases.62 Interactions are recorded in the Interaction Web Database (IWDB), Semantic Web
Informatics for Species in Space and Time (SWISST) and the Encyclopedia of Life.63 Species trait data standards include Structured
Descriptive Data (SDD), the Plinian Core, the Phenotypic Quality Ontology, and the Animal Natural History ontology, which also
includes species interactions.64 The next tasks are to standardize across these vocabularies; ensure that the data recorded reflect
the complex relationships among traits, their genetic base and the environment; and report traits and interactions at multiple
scales.
In the short term, the priority will be to produce summaries of which organisms interact with each other in defined ways such aspredator/prey or parasite/host relationships or in more general terms (pollinators, invasive species) and to continue to develop
and improve identification tools. In the medium term, the priorities will be systems to serve rich trait data for the best-understoodorganisms, and identifying techniques for large-scale trait data capture building on focus area B. In the long term, the priorities
will be to capture high-quality trait and interaction information at increasingly large taxonomic and geographic scales using highthroughput descriptions equivalent to NextGen sequencing.

                 C5. Comprehensive knowledge access
Delivering access to all published biodiversity knowledge.
Progress: some progress (issues understood, needs operational implementation)
The other elements in this focus area have related to the provision of central indexes of particular types of structured information
which can feed directly into modelling and analysis tools. However the biodiversity data that have been gathered and publishedare much richer than these core subsets – consisting of anything from video recording to identification tools to conservationassessments. Locating all information about a species – or the biodiversity of a defined area– requires seamless access to theunderlying information resources, structured and unstructured. Users may also want to retrieve information in other ways, such as
by usage or threat level, or in other languages.
Many national and thematic activities – and other web communities such as Wikipedia and Wikispecies65 – organize and deliver
web content for particular species, either as online databases or as species pages. The Encyclopedia of Life (EOL), now represents

28/29In the short term, relevant data standards (A2) and links into the taxonomic framework (C2) need to be widely adopted tosupport the sharing of different types of species information along with mechanisms enabling users to locate materials in alanguage that they can understand. In the medium term, comprehensive catalogues should be developed to simplify access andreuse of authoritative species descriptions, images, identification keys, etc. In the long-term, all species information should cometo be managed and curated as an inter-connected digital knowledge base.

CULTUREan international partnership of institutions and agencies committed to providing open access to authoritative species information,
including multimedia,66 while EUBrazilOpenBio aims to combine open access resources including data, tools and services in asingle ‘e-infrastructure’.67 Other organizations manage key expert-curated data sets such as the IUCN Red List and the United
Nations Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) World Database on Protected Areas.68
Users need efficient mechanisms to discover, access and integrate all of these resources.

DATA
EVIDENCE

UNDERSTANDING

Delivering Biodiversity Knowledge in the Information Age

Focus area D:
Understanding
Using the combined biodiversity data frommultiple sources to generate new information,
inform policy and decision makers, and help
educate wider society to improve the way wemanage the Earth’s resources.
Society needs systems that deliver the best possible estimateof the abundance and distribution of all species in all areas
and at all scales, now and at any time in the recent past, andprojections into the future depending on human actions
and decisions. We need the best possible understanding of
how different species interact and how communities andecosystems function. For all our efforts in the other focus areas,
our data resources can only provide a partial and fragmented
picture of the world’s biodiversity today, let alone in the past.
As importantly, all the data in the world will not help achieve
the Aichi Biodiversity Targets unless they are presented topolicy makers and the public they serve in a compelling andeasily understood way.
This focus area addresses these challenges by integrating
biodiversity data sources with other disciplines – from geology
to economics – to bring to bear all of our expert knowledge
to create the best possible models of existing biodiversity
patterns and how they might respond to human activities.
It addresses how to make these immediately and vividly
understandable through visualizations and interactive tools,
and how they can be used to support policy makers andmonitor the effectiveness of the policies already in place, as
well as alert us to potentially dangerous changes before it is
too late.
It is envisaged that by integrating information from multiple
sources – from local to global, and from different fields ofknowledge – by acquiring new expertise, and by developing
new tools, new questions will be asked which will require
new types of analysis. Progress, therefore, depends oncontinuous and dynamic planning and evaluation, interaction,
cooperation, suitable governance and adequate long-term
funding.

Components:• D1. Multiscale spatial modelling: Integrate data		 collected across disciplines and combine them with		 remote-sensed and geographic information systems
		 (GIS) datasets to create the fullest-possible picture of		 geographical species distributions.
•
		
		
		
		

D2. Trends and predictions: Integrate historical dataand changes over time to create predictive modelling
tools to support decision making, make biodiversity
estimates and predict the potential impact of changing
conditions anywhere on Earth.

•
		
		
		

D3. Modelling biological systems: Build virtual models– from the molecular level to whole ecosystems – toimprove understanding of biological systems andintegrate that knowledge into other models.

•
		
		
		

D4. Visualization and dissemination: Provide thetools to make biodiversity information accessible andunderstandable by diverse audiences, increasing
biodiversity literacy among the public and policy makers.

•
		
		
		

D5. Prioritizing new data capture: Use accumulating
data to identify and prioritize new opportunities for data
capture and to provide a timely response to changes inbiodiversity patterns.

Progress: This is the least developed of the four focus
areas, and one, modelling biological systems (D3) has
not progressed much beyond the conceptual stage. The
biodiversity informatics community will have to draw heavily
on the knowledge of other disciplines — from climate
modelling and socio-economics, to games development
and web design.
Priorities and dependencies: Completing this focus area
depends on having as much high-quality data mobilized
as possible (focus area B) — both current observations ofexisting biodiversity, and historical records from the literatureand natural history collections. Synthesizing new knowledge
requires mobilizing data in sufficient volume from acrossmultiple disciplines, making the right data standards (A2)crucial. Displaying and using data in novel ways, and even inreal time, relies on an open access and reuse culture (A1) as
well as robust persistent storage and archives (A3) to serve
the underlying data stores. Vertical integration of species
traits and occurrences (C4, C3) around a strong taxonomic

30/31

EU-Brazil OpenBio

www.eubrazilopenbio.eu

http://vitalsign

e distribution
ge base about th
A global knowled
tform forof Life acts as a plaof species. Map
n of species,
tio
bu
tri
s on the disdeveloping map
ssing,
for querying, acceand provides tools
able data.
ail
av
g
zin
d summaridownloading an

Digital Observ
Protected Are atory foras
http://dopa.jrc.ec.europ
a.eu/Conceived as aset of ‘critical bi
odiversity
informatics infra
structures’, to pr
ovide users
such as park m
anagers, decision makers andresearchers withthe means to as
sess, monitor
and possibly forecast the stateof protectedareas and pressu
res upon them, at a global scale
DOPA supports.
the Group on Ea
rth Observations
Biodiversity Ob
servation Netw
ork (GEO BON).

The projects and initiatives highlighted here are for illustration only – many more contribute to the objectivesof GBIO. Each will often cut across several focus areas, as indicated by the icons (see page 11 for the icon key).

UNDERSTANDING

nearm that provides
onitoring syste
m
to
ed
s
at
ol
gr
to
c
te
in
sti
An
d diagno
access data anle scales
tip
ul
m
at
real time, opengin
ral decision-mak
rs of
inform agricultu
d level. Indicato
to the househol
al
ob
ging
gl
an
ch
re
he
– from thewe,line presented onpolicy makers
sustainability arriculture helps
ag
r
fo
els
lev
n
the decisio
offs.
to visualize tradelifwww.mapping

EVIDENCE

AfricaVital Signs s.org/

Map of Life e.org

DATA

An e-infrastructure project with integrated
data, tools and services for the use of
biodiversity scientists. The EUBrazilOpenBio
data e-infrastructure will bring together
existing data, cloud, and grid EU and Brazilian
infrastructures and resources across thebiodiversity & taxonomy domains.

framework of coupled models based on interlinked data andtools. Finally, both visualization and dissemination (D4) andprioritizing new data capture (D5) will depend on having
increasingly robust models to draw on.

CULTURE

framework (C2), including vernacular names, will be essential
when developing tools to make the data relevant to policy
makers and the general public. This focus area is also the mostclosely interdependent, with the three modelling components(D1, D2 & D3) needing to work in parallel to provide aDelivering Biodiversity Knowledge in the Information Age                D1. Multiscale spatial modelling
Estimating biodiversity patterns from available evidence.
Progress: some progress (some progress, issues understood, needs operational implementation)
Many issues in biodiversity research, conservation and management depend on understanding the spatial occurrence, distribution
and abundance of species and the communities of which they form a part. These questions operate at all scales from the planetary
down to small research plots. Underlying them is a general requirement – estimating the range of species that are to be foundin any area, their relative abundance and their functions and inter-relationships. Focus area B mobilizes the data needed to meetthis requirement while the integrated occurrence data (C3) component organizes these data into evidence for what has actually
been recorded of biodiversity patterns. However, these data will never be comprehensive enough to document which species
occur in every part of the planet. Some of the data may only provide very coarse indication of species occurrence, for example justthe fact that a particular species has been recorded within a particular country. We need to build models that make appropriate
use of all available evidence to provide the best possible estimate of the actual set of species in each area and of the relative
abundance of each. Such models can simultaneously help to compensate for errors in primary data and to address gaps in our
knowledge, for example providing estimates of species and species numbers where records are incomplete.
Progress has already been made in building models for individual species using approaches such as Maxent69 and OpenModeller,70
an online environment providing access to a range of published modelling algorithms, to assess and map the suitability ofdifferent habitats and environments for the species based on similarity to known localities for the species. The Map of Life71 aims
to integrate models with a wide variety of spatial biodiversity data sources to build a knowledge base and platform for species
distribution map development. Other approaches such as generalized dissimilarity modelling (GDM)72 support exploration ofpatterns involving whole communities of species. The next step will be to refine these foundations over time to use all available
sources of evidence, biotic or abiotic (e.g. environmental variables like temperature and precipitation), to build improved spatialmodels to support research and decision making. These models themselves should be made available in a standard format for
further research and shared using the infrastructure and culture addressed by focus area A.
In the short term, the priority will be to develop best practices for combining and using data with varying degrees of precision,from high-precision coordinates for samples or observations through to national species lists, and to organize consistent access tothe abiotic datasets required for spatial modelling. In the medium term, repositories are required to support efficient archival andreuse of models and modelled data. In the long term, insights and models derived from the modelling biological systems (D3)component must be accommodated to maximize the biological validity of spatial models.

                *D2. Trends and predictions
Using predictive modelling to assess status, trends and the impacts of any potential changes.
Progress: limited (limited existing efforts, needs further development)
Being able to model future trends in biodiversity under different conditions (such as the outcomes of particular policies or
climate change) are key to sound decision making. The wealth of historical data that focus area B will unlock from the literatureand museum collections, and the existing long-term ecological monitoring sites, provide a temporal dimension to the available32/33

A number of projects, such as the Wallace Initiative, ClimaScope, eHabitat and the Ermitage project, already use biodiversity data
to explore the impacts of environmental changes on biodiversity,73 while the Digital Observatory for Protected Areas (DOPA) islooking at building interoperable modelling services for biodiversity.74 The next step will be to create a group equivalent to the Task
Group on Data and Scenario Support for Impacts and Climate Analysis (TGICA) of the Intergovernmental Panel on Climate Change(IPCC)75 to establish the baseline data and methodologies, workflows and repositories needed.

DATA

In the short term, mechanisms are required to assess the suitability of integrated occurrence data for different species to support
development of a series of historical distribution models, and to establish guidelines for the work in focus area A and focus area
B to maximize the suitability of the data for temporal modelling. In the medium term, work should focus on visualization of suchmodels and on algorithms to explore the drivers behind apparent changes in biodiversity. In the long term, these insights should
support development of tools to model predicted changes in biodiversity in response to human-induced pressures such as
climate change, land use change and the expected impacts of invasive species on ecosystems.

CULTUREevidence for our spatial models. Mobilizing all of these data will enable not only multiscale spatial modelling (D1) of current
biodiversity patterns, but also to construct a series of historical models, at least for some taxonomic groups and for some regions
and scales of detail. These models will in turn help us to identify trends, to explore the key drivers behind these trends and to
predict responses to potential future changes. Having good predictive tools are a key element for the better management of
biodiversity, so developing this component should be a matter of high priority.

                *D3. Modelling biological systems
Building virtual models from molecules to ecosystems.
Progress: minimal (needs further investigation)* Considered to be of high urgency, but have made limited progress to date.

UNDERSTANDING

This is a complex area. Some use is already made of simple trait data to validate occurrence data, for example the indicators in theInterim Register of Marine and Non-marine Genera (IRMNG) of which genera are found in marine and terrestrial environments.76
A wealth of models has been developed for model organisms and for ecological communities. The most relevant and useful ofthese models could be integrated using a coordinated coupled framework approach and associated usage guidelines.77

EVIDENCE

Biodiversity is a complex and massively interconnected system with interactions that range from the molecular to the entire
biosphere. Current solutions in the multiscale spatial modelling (D1) and trends and predictions (D2) components primarily
depend on knowledge of recorded species occurrence and environmental spatial data to build models that estimate actual
distributions. Clearly such models do not reflect the complex realities of diverse ecosystems. Actual species distributions are driven
by specific aspects of the physiology and behaviour of each species, where an organism is in the food chain, and how it competes
and interacts with other species. Incorporating information from aggregated species trait data (C4) will make many refinements
and enhancements to spatial and temporal models possible. Understanding which taxa exist in marine, freshwater andterrestrial environments is fundamental to predicting their distributions. Knowledge of reproductive strategies, metapopulation
characteristics, dispersal and migration strategies, food requirements and many other features may support much more finegrained modelling. Some aspects of species and community biology may themselves be handled through models that could be
integrated into sophisticated models that better simulate the behaviour of complex systems in space and time. Predictive models
based on phylogeny may also allow inference of likely traits even for species for which these data have not been recorded. As thisis a key component for good decision making, and the least-developed area of the whole framework, it should be pursued as amatter of urgency.

Delivering Biodiversity Knowledge in the Information Age

In the short term, key species traits and interactions can be used to validate integrated occurrence data (C3) and to assess andrefine multiscale spatial modelling (D1) results. In the medium term, standards will be required for sharing and reusing traitbased factors and biological models within spatial and temporal modelling systems. In the long term, models for different species
and communities should be used to refine one another.

               *D4. Visualization and dissemination
Giving people – from the public to scientists to policy makers – access to information in ways thatwill revolutionize how we understand biodiversity.
Progress: limited (limited existing efforts, needs further development)
The way we present information is often as important as the content itself. Recent advances in mobile technology have
revolutionized the way we consume data, while information is being served in ever more inventive ways. The rapid developmentof processors and software is now enabling interactive visualization of data in ways that would have been impossible only a few
years ago. We need to engage game developers, web designers, communications experts and policy makers in rethinking how
biodiversity information is organized to support decision making and to communicate with the public. Building on the resources
we have, and the vertical integration being developed in focus area C, the goal should be to give everyone everywhere the means
to explore biodiversity information in context, increasing our understanding and thus increasing the value placed on biodiversity
itself. As better understanding of biodiversity is key to generating the political will to protect it, this is another urgent task.
Many online projects are already using interactive maps, charts, taxonomic and phylogenetic trees, and other tools to enhance
understanding and interpretation of biodiversity data. The next steps would be for projects to take a more multi-disciplinary
approach and expand to encompass clear and informative presentation of biodiversity information in combination with otherrelevant knowledge, including environmental, climatic, and sociological data. Good interfaces should assist all users to understandthe relevance and significance of available biodiversity information in relation to their interests and needs.
In the short term, more work is needed to bring experts in information science and interface design in conversation withbiodiversity experts and users of biodiversity information. In the medium term, this work will drive refinements to the components
in focus area C to deliver information in the most appropriate and effective forms. There will also be a need for developing newinteroperability standards to maximize the usefulness of visualization tools and applications. In the long term, such tools andapplications will lead to a new generation of code libraries and intuitive interactive platforms to support research, policy needs
and public understanding.

* Considered to be of high urgency, but have made limited progress to date.

34/35                 D5. Prioritizing new data capture
CULTURE

Making best use of limited resources by concentrating on the areas of greatest change and greatest
uncertainty.
Progress: limited (limited existing efforts, needs further development)
If we are to respond effectively to changes in ecosystems we need to be alerted to them as soon as possible, and be able toreallocate monitoring resources to determine the causes, and to take appropriate action. Policy interventions also need to bemonitored to ensure that they are having the desired effect and so modified where necessary. We can use our limited resources
best by coordinating with other agencies and using all sources of information from remote-sensing satellites to the observations
from local people on the ground.

EVIDENCE

In the short term, the priority should be on understanding the coverage, the gaps and completeness of existing data anddetermining the suitability of these data for addressing questions at different scales for different species and taxonomic groups.
In the medium term, gaps in this coverage can help to prioritize efforts to mobilize additional data, while understandingof which areas are already covered by good historical data can help to identify the most effective locations for establishingmonitoring activities. In the longer term, research and citizen science activities can be focussed to maximize the expansion of ourunderstanding of biodiversity and its patterns and processes. Regional, national and global intervention networks will be able toidentify changes and threats rapidly, and support decision making regarding the best response.

DATA

A number of projects are involved in monitoring biodiversity and environmental changes, including GEOBON, Vital Signs Africa,
the International Centre for Integrated Mountain Development (ICIMOD), Long Term Ecological Research Network (LTER Network),
the Global Observation Research Initiative in Alpine Environments (GLORIA) and Eye on Global Network of Networks.78 The next
step will be to enable monitoring efforts to track and report changes promptly, feeding the information in to governmental andnon-governmental action networks for rapid response. Existing monitoring agencies need to build in flexibility to share capacitywith other organizations. Mechanisms developed under the new Intergovernmental Platform on Biodiversity and Ecosystem
Services (IPBES) should help to identify priorities for filling gaps and to support efforts to fill them.

UNDERSTANDING

Delivering Biodiversity Knowledge in the Information Age

Annex – The Global Biodiversity Informatics Conference
Organizing committee
Donald Hobern		
Leonard Krishtalka 		
Wouter Los 		
Norman MacLeod		
Erick Mata			
David Schindel		

Executive Secretary, Global Biodiversity Information Facility
Chair, GBIF Science Committee
CReATIVE-B (LifeWatch)
Natural History Museum, London
Encyclopedia of Life (EOL)
Consortium for the Barcode of Life (CBOL)

Workshop leads and the GBIO drafting team
Enrique Alonso García
Alberto Apostolico		
Elizabeth Arnaud 		Juan Carlos Bello 		
Dora Canhos 		
Gregoire Dubois 		Dawn Field 							Alex Hardisty		
Jerry Harrison 		
Bryan Heidorn 		
Roderic Page 							
Cynthia Parr 		
Jeff Price 			Selwyn Willoughby 		Consejo de Estado, Spain
College of Computing, Georgia Institute of Technology
Bioversity International
Alexander von Humboldt Institute for Research on Biological Resources, Colombia
Centro de Referência em Informação Ambiental (CRIA), Brazil
European Commission - Joint Research Centre
Molecular Evolution and Bioinformatics Group, NERC Centre for Ecology and Hydrology,
United Kingdom
CReATIVE-B (Cardiff University)
UNEP-WCMCJRS Foundation & University of Arizona
Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow,
United Kingdom
Encyclopedia of Life (EOL)The Wallace Initiative, ClimaScope and University of East Anglia
South African National Biodiversity Institute

Facilitators
Natasha Walker
Bart Slob
Niels Ferdinand

GBIF Secretariat support staff
Sampreethi Aipanjiguly
Olaf Bánki
Vishwas Chavan
Samy Gaiji
Alberto González-Talaván
Andrea Hahn
Tim Hirsch
Anne Mette Nielsen
Éamonn Ó TuamaDavid Remsen
Tim Robertson
Susanne Lønstrup Sheldon
Ciprian Vizitiu
Hugo von Linstow
Katja Wolfhechel Christensen

36/37

Participants
Agosti, Donat
Allen, Paul
Alonso García, Enrique
Ariño, Arturo H.
Baadsvik, Karl
Balslev, Henrik
Belbin, Lee
Berendsohn, Walter
Blum, Stan
Canhos, Vanderlei
Cao, Mingchang
Chenin, Eric
Chettri, Nakul
Cochrane, Guy
Costello, Mark
Dalcin, Eduardo
Daly, Joanne
Davies, Neil
Dulloo, Ehsan
Faith, Daniel P.
Ferrier, Simon
Flemons, Paul
Ganglo, Jean Cossi
Gärdenfors, Ulf
Gray, William Alex
Guala, Gerald Stinger
Guralnick , RobertHammond, Thomas
Hanner, Robert
Hardisty, Alex
Häuser, Christoph
Herrera Bachiller, Alfonso
Hilton-Taylor, Craig
Höft, Robert
Hugo, Wim
Jimenez Rosenberg, Raul 	
Johansson, Anna Maria 	
Kelly-Quinn, Mary
Koleff Osorio, Patricia
Kovaleva, Olga
La Salle, John
Llosent de Nárdiz, Maria
Loarie, Scott R.
Lund, Mette
Ma, Juncai
MacDevette, Monika

Plazi
Cornell University
Consejo de Estado
University of Navarra
Norwegian Biodiversity Information Centre
Aarhus University
Atlas of Living Australia
Botanischer Garten und Botanisches Museum Berlin-Dahlem
California Academy of Sciences
Centro de Referência em Informação Ambiental (CRIA)
Nanjing Inst. of Environmental Sciences, Ministry of Environmental Protection
GBIF-France/Institut de Recherche pour le Développement
International Centre for Integrated Mountain Development
European Bioinformatics Institute
University of Auckland
Instituto de Pesquisas, Jardim Botânico do Rio de Janeiro
Commonwealth Scientific and Industrial Research Organisation (CSIRO)
Moorea Biocode Project
Food and Agriculture Organization of the United Nations (FAO)
Australian Museum
Commonwealth Scientific and Industrial Research Organisation
The Australian Museum
Université d’Abomey-Calavi
Swedish Species Information Centre
Cardiff University
U.S. Geological Survey
University of Colorado
UNEP-GEF Scientific and Technical Advisory PanelInternational Barcode of Life (IBOL)
Cardiff University
Museum für Naturkunde
University of Alcalá
IUCN UK Office
CBD Secretariat
South African Environmental Observation Network (SAEON)
Comisión Nacional para el Conocimiento y Uso de la Biodiversidad
European Commission - DG Research
School of Biology and Environmental Science, University College Dublin
Comisión Nacional para el Conocimiento y Uso de la Biodiversidad
N.I. Vavilov Research Institute of Plant Industry (VIR)
Atlas of Living Australia
University of Alcalá
Carnegie Institution for Science
European Environment Agency
Institute of Microbiology, Chinese Academy of Sciences
UNEP, Division of Early Warning & Assessment

Iran
United States
Spain
Spain
NorwayDenmark
Australia
Germany
United States
BrazilChina
France
Nepal
United Kingdom
New ZealandBrazilAustralia
French Polynesia
Italy
Australia
Australia
Australia
Benin
SwedenUnited Kingdom
United States
United States
United States
CanadaUnited Kingdom
Germany
Spain
United Kingdom
CanadaSouth Africa
MexicoBelgium
Ireland
MexicoRussian Federation
Australia
Spain
United States
Denmark
China
Kenya

Delivering Biodiversity Knowledge in the Information Age

Annex – The Global Biodiversity Informatics Conference – continued
Participants
Mizrachi, Ilene
National Center for Biotechnology Information
Moat, Justin
Royal Botanic Gardens, Kew
Mora, Maria Auxiliadora
Instituto Nacional de Biodiversidad (INBio)
Moritz, Tom		
Nicholls, Miles
Atlas of Living Australia
Owens, Ian
Natural History Museum-London
Pagano, Pasquale
CNR-ISTI
Pando, Francisco
Real Jardín Botánico de Madrid (CSIC)
Roberts, Dave
Natural History Museum-London
Saarenmaa, Hannu
Digitarium - Digitisation Centre of the Finnish Museum of Natural
History and University of Eastern Finland
Saraiva, Antonio
University of São Paulo
Schalk, PeterETI Bioinformatics
Scholes, Bob
Council for Scientific and Industrial Research
Seberg, Ole
Botanic Garden & Museum
Segers, Hendrik
Royal Belgian Institute of Natural Sciences
Seltmann, Katja
American Museum of Natural History
Simiyu, Stella		
Soberón Mainero, Jorge
University of Kansas
Suárez-Mayorga, Ángela
Alexander von Humboldt Biological Research InstituteSvenning, Jens-Christian
Aarhus University
Thuveson, Maria
Swedish Research Council
Turner, Woody
NASA
Ulate, William
Biodiversity Heritage Library
Valland, Nils
Norwegian Biodiversity Information Centre, Artsdatabanken
Vicario, Saverio		
Vieglais, David A.
University of Kansas
Vogel, Johannes
Museum für Naturkunde
Walters, Michelle
Group on Earth Observations Biodiversity Observation Network (GEO BON)
Wang, Yu-Huang
Taiwan Forestry Research Institute
Wieczorek, John
Museum of Vertebrate Zoology
Wilson, Nathan
Encyclopedia of Life
Yang, Xiangyun
Kunming Institute of Botany, Chinese Academy of Sciences

United States
United Kingdom
Costa Rica
United States
Australia
United Kingdom
Italy
Spain
United Kingdom
Finland
BrazilNetherlands
South Africa
Denmark
Belgium
United States
Kenya
United States
Colombia
Denmark
SwedenUnited States
United States
NorwayItaly
United States
GermanySouth Africa
Chinese Taipei
United States
United States
China38/39Acronyms and abbreviations
ABCD
ALA
BDRS
BHL
CBD
CBOL
CEH
CITES
CoL
CRIA
DOPA
EOL
FAT
FISH-BOL
GDM
GEO BONGBIF
GBIO
GLORIAGSC
GUID
ICIMOD
IPBES
IPCC
IUCN
IRMNG
IWDB
LTER
MARTT
NERC
OBIS
OSTP
SANBI
SciELOSDD
SWISST
TDWG
TGICA
UNEP
WCMC
WDPA

Access to Biological Collection Data
Atlas of Living Australia
Biological Data Recording System
Biodiversity Heritage Library
Convention on Biological Diversity
Consortium for the Barcode of Life
Centre for Ecology & Hydrology
Convention on International Trade in Endangered Species of Wild Fauna and FloraSpecies 2000 Catalogue of Life
Centro de Referência em Informação Ambiental
Digital Observatory for Protected Areas
Encyclopedia of Life
Find All Taxa
Fish Barcode of Life Initiative
Generalized Dissimilarity ModellingGroup on Earth Observations Biodiversity Observation Network
Global Biodiversity Information Facility
Global Biodiversity Informatics Outlook
Global Observation Research Initiative in Alpine Environments
Genomic Standards Consortium
Globally Unique IdentifiersInternational Centre for Integrated Mountain Development
Intergovernmental Platform on Biodiversity and Ecosystem Services
Intergovernmental Panel on Climate ChangeInternational Union for Conservation of Nature
Interim Register of Marine and Non-Marine Genera
Interaction Web DataBase
Long Term Ecological Research Network
MARkuper for Taxonomic Treatments
Natural Environment Research Council
Ocean Biogeographic Information System
United States Office of Science and Technology Policy
South African National Biodiversity InstituteScientific Electronic Library Online
Structured Descriptive Data
Semantic Web Informatics for Species in Space and Time
Biodiversity Information Standards
Task Group on Data and Scenario Support for Impacts and Climate Analysis
United Nations Environment Programme
World Conservation Monitoring Centre
World Database on Protected Areas

Delivering Biodiversity Knowledge in the Information Age

Endnotes
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.

37.
38.
39.
40.
41.
42.

For more information about the Global Biodiversity Informatics Conference, see http://www.gbic2012.org/
For a full list of participants, workshop leads and organizers of the conference, see Annex on page 36
Strategic Plan for Biodiversity 2011-2020, including Aichi Biodiversity Targets – https://www.cbd.int/sp/
http://www.ipbes.net/
Appendix I (Functions, operating principles and institutional arrangements of the Platform) of UNEP/IPBES.MI/2/9,
accessible from http://ipbes.net/plenary/ipbes-1.html
Section B of IPBES/1/INF/10, accessible from http://ipbes.net/plenary/ipbes-1.html#three
Species 2000 – http://www.sp2000.org/; Catalogue of Life – http://www.catalogueoflife.org/
Biodiversity Information Standards (TDWG) – http://www.tdwg.org/
Global Biodiversity Information Facility – http://www.gbif.org/
Encyclopedia of Life – http://eol.org/
Consortium for the Barcode of Life – http://www.barcodeoflife.org/
Biodiversity Heritage Library – http://www.biodiversitylibrary.org/
Group on Earth Observations Biodiversity Observation Network – http://www.earthobservations.org/geobon.shtml
Gibbons et al. 1994
Schofield et al. 2010
GenBank – http://www.ncbi.nlm.nih.gov/genbank/
Biodiversity Information Standards (TDWG) – http://www.tdwg.org/
See for example the GUID and Life Sciences Identifiers Applicability Statement,
accessible from http://www.tdwg.org/standards/150
United States Office of Science and Technology Policy – http://www.whitehouse.gov/administration/eop/ostp
See the Memorandum for the heads of executive departments and agencies, Feb 22, 2013. Available at:
http://www.whitehouse.gov/sites/default/files/microsites/ostp/ostp_public_access_memo_2013.pdf
SANBI – http://www.sanbi.org/
See the National Environmental Management: Biodiversity Act 2004, Republic of South Africa Government Gazette,
June 2004. Available at: http://www.sanbi.org/sites/default/files/documents/documents/biodiversityact2004pdf.pdf
Belbin, L. et al., 2013. A specialist’s audit of aggregated occurrence records: An “aggregator”s’ perspective.
ZooKeys, 305, pp.67–76. Available at: http://www.pensoft.net/journals/zookeys/article/5438/abstract/a-specialist
OpenUp! – http://open-up.eu/
See “EOL Curators” on the EOL website – http://eol.org/info/curators
FISH-BOL – http://www.fishbol.org/
Biodiversity Heritage Library – http://www.biodiversitylibrary.org/
See “Interested in improving access to millions of digital images?”, Biodiversity Heritage Library website, 30 August 2012. Available at:
http://blog.biodiversitylibrary.org/2012/08/interested-in-improving-access-to.html
See for example the “EOL Computable Data Challenge”, EOL website, http://eol.org/info/323
GoldenGATE - see Agosti, D. and W. Egloff (2009), “Taxonomic Information Exchange and Copyright: The Plazi Approach”,
BMC Research Notes 2(53), http://www.biomedcentral.com/1756-0500/2/53, doi:10.1186/1756-0500-2-53
MARTT (MARkuper for Taxonomic Treatments). See Cui, Hong (2005) “MARTT: A General Approach to Automatic Markup
of Taxonomic Descriptions with XML”, http://www.cais-acsi.ca/proceedings/2005/cui_2005.pdf
TaxonFinder – http://taxonfinder.sourceforge.net/
Taxon Grab – http://taxongrab.sourceforge.net/
FAT (Find All Taxa). See Sautter, G., K. Böhm & D. Agosti (2006), “A Combining Approach to Find All Taxon Names (FAT)in Legacy Biosystematics Literature”, Biodiversity Informatics, 3, 2006, https://journals.ku.edu/index.php/jbi/article/view/34/19
SciELO (Scientific Electronic Library Online) – http://www.scielo.org/
See Penev, L. et al. (2012), “Implementation of TaxPub, an NLM DTD Extension for Domain-Specific Markup in Taxonomy,
from the Experience of a Biodiversity Publisher”, Journal Article Tag Suite Conference (JATS-Con) Proceedings 2012,
http://www.ncbi.nlm.nih.gov/books/NBK100351/, and, Penev, L. et al. (2011), “XML Schemas and Mark-up Practicesof Taxonomic Literature”, Zookeys 150, 89-116, doi: 10.3897/zookeys.150.2213
See for example Penev et al. (2010), “Taxonomy Shifts Up a Gear: New Publishing Tools to Accelerate Biodiversity Research”,
Zookeys 50, special issue: 1-4, doi: 10.3897/zookeys.150.2213
OBIS – http://www.iobis.org/
Atlas of Living Australia – http://www.ala.org.au/. For information about the Biodiversity Volunteer Portal see,
http://volunteer.ala.org.au/
Herbonautes – http://lesherbonautes.mnhn.fr/
See the Moorea Biocode Project website for more information: http://mooreabiocode.org/pages/it-platform
FieldData (http://www.ala.org.au/getinvolved/citizen-science/fielddata-software/) is based on the Biological Data
Recording System (BDRS) developed for the ALA by Gaia Resources (http:/www.gaiaresources.com.au)

40/41

43. Centre for Environment & Hydrology – http://www.ceh.ac.uk/index.html
44. See the Guide to Citizen Science available at http://www.ceh.ac.uk/news/news_archive/Citizen-Science-ReviewGuide_2012_59.html
45. For more information on the relevance of GUIDs to the community, see the TDWG wiki http://wiki.tdwg.org/GUID
46. Genomic Standards Consortium – http://gensc.org/
47. See for example the outcomes of a GBIF-led workshop in Oxford in Tuama et al. (2012) “Meeting Report:
Hackathon-workshop on Darwin Core and MIxS standards alignment (February 2012)” in Standards in Genomic
Sciences, 7(1), http://standardsingenomics.org/index.php/sigen/article/view/sigs.3166513
48. http://genomicobservatories.blogspot.co.uk/
49. GEO BON – http://www.earthobservations.org/geobon.shtml
50. Icarus Initiative – http://icarusinitiative.org/
51. MoveBank – https://www.movebank.org/
52. The Filtered Push Project – http://wiki.filteredpush.org/; AnnoSys – http://wiki.bgbm.org/annosys/index.php/Main_Page;
see Tschöpe, O. et al. (forthcoming), “Annotating Biodiversity Data”, Taxon
53. Species Link Data Cleaning – http://splink.cria.org.br/dc
54. Species 2000 – http://www.sp2000.org/; Catalogue of Life – http://www.catalogueoflife.org/
55. See “Lacunas de conhecimento da flora e dos fungos do Brasil” – http://lacunas.inct.florabrasil.net/
56. Global Names Architecture – http://www.globalnames.org/; i4Life – http://www.i4life.eu/
57. Red Lists are the International Union for Conservation of Nature (IUCN) lists of threatened species (http://www.iucnredlist.org/).
The Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) lists species which areprotected against overexploitation through international trade (http://www.cites.org/)
58. OBIS – http://www.iobis.org/
59. VertNet – http://vertnet.org/
60. Darwin Core – http://rs.tdwg.org/dwc/; ABCD – http://www.tdwg.org/standards/115/
61. www.gbif.org
62. TraitNet – http://traitnet.ecoinformatics.org/; TRY Plant Trait database – http://www.try-db.org/;
LEDA Traitbase – http://www.leda-traitbase.org/; MorphoBank – http://www.morphobank.org/;
Animal Diversity Web – http://animaldiversity.ummz.umich.edu/; the Phenoscape KnowledgeBase – http://kb.phenoscape.org/
63. IWDB – http://www.nceas.ucsb.edu/interactionweb/; SWISST – http://peacelab.cloudapp.net/swisst.html
64. SDD – http://www.tdwg.org/standards/116/; the Plinian Core – http://www.pliniancore.org/;
the Phenotypic Quality Ontology – http://obofoundry.org/wiki/index.php/PATO:Main_Page;
the Animal Natural History ontology – http://animaldiversity.ummz.umich.edu/about/technology/
65. Wikipedia – http://en.wikipedia.org/; Wikispecies – http://species.wikimedia.org
66. See for instance the list of EOL global partners http://eol.org/info/global_partners and content partners –http://eol.org/content_partners
67. EUBrazilOpenBio – http://www.eubrazilopenbio.eu/
68. The World Database on Protected Areas (WDPA) can be searched at http://www.protectedplanet.net/
69. Maxent http://www.cs.princeton.edu/~schapire/maxent/; Phillips, S.J., R.P. Anderson and R.E. Schapire (2006),“Maximum Entropy Modeling of Species Geographic Distributions”, Ecological Modelling 190, 231-259,
http://www.cs.princeton.edu/~schapire/papers/ecolmod.pdf
70. OpenModeller http://openmodeller.sourceforge.net/; Muñoz, M.E.S. et al. (2009) “OpenModeller: A Generic Approach toSpecies’ Potential Distribution Modelling”, Geoinformatica, DOI: 10.1007/s10707-009-0090-7,
http://link.springer.com/article/10.1007%2Fs10707-009-0090-7
71. Map of Life – www.mappinglife.org
72. Generalized dissimilarity modelling http://www.biomaps.net.au/gdm/ - see also Ferrier, S. et al. (2007), “Using generalized
dissimilarity modelling to analyse and predict patterns of beta diversity in regional biodiversity assessment”, Diversity andDistributions 13: 252-264, http://onlinelibrary.wiley.com/doi/10.1111/j.1472-4642.2007.00341.x/abstract
73. Wallace Initiative – http://wallaceinitiative.org/; ClimaScope – http://climascope.tyndall.ac.uk;
eHabitat – http://ehabitat.jrc.ec.europa.eu/; Ermitage – http://ermitage.cs.man.ac.uk/
74. DOPA – http://dopa.jrc.ec.europa.eu/
75. TGICA – http://www.ipcc.ch/activities/activities.shtml#tabs-4
76. IRMNG – http://www.obis.org.au/irmng/
77. For more information see Hardisty and Roberts (2013) “A decadal view of biodiversity informatics: challenges and priorities”,
BMC Ecology, 13(16), http://www.biomedcentral.com/1472-6785/13/16/abstract
78. GEO BON – http://www.earthobservations.org/geobon.shtml; Vital Signs Africa on the Conservation International website –http://www.conservation.org/about/centers_programs/funding/pages/vital_signs.aspx, ICIMOD – http://www.icimod.org/; 		
LTER Network – http://www.lternet.edu/; GLORIA – http://www.gloria.ac.at/; andEye on Global Network of Networks – http://www.eyeonearthsummit.org/special-initiative-global-networks

https://www.facebook.com/biodiversityinformatics@biodiversityinf
info@biodiversityinformatics.org

Design: Hoogs design
Printing: Ørskov
Production coordination: GBIF Secretariat
ISBN: 87-92020-52-6