Introduction to research infrastructures for biodiversity and ecosystems research, and their global importance to support modern research. Essential Biodiversity Variables (EBV) are a unifying use case for interoperability. We are all collectively responsible for research infrastructure.

1. Global Research Infrastructures
for Biodiversity and Ecosystems
Research
Alex Hardisty
Director of Informatics Projects
School of Computer Science & Informatics
email: hardistyar@cardiff.ac.uk
/alexhardisty
1

2. Take home messages
• Research infrastructures help data intensive science
and collaboration between scientists.
• Measuring and calculating EBVs on a global scale
are a unifying use case to drive interoperability
across Research Infrastructures.
• No‐one is responsible for research infrastructure.
We’re all responsible for research infrastructure.
2
Pedro Ribeiro Simões, flickr.com Goodmami, flickr.com Michael Bentley, flickr.com

3. Fig.1. Workflow for estimating SD, FD, and ES potential for tropical South America.
Molecular Ecology Resources
19 NOV 2014 DOI: 10.1111/1755‐0998.12341
Setting the scene: The era of data‐intensive science
Monitoring forest microclimate, www.fraunhofer.de
Satellite tagging saltwater crocodiles
Danau Girang Field Centre, Cardiff University and Sabah Wildlife Service

4. Research infrastructures help data intensive science
Simply:
Anything semi‐permanent that researchers
need to do their job
• Physical equipment
(labs, instruments, survey sites, ships, …)
• Computers
(desktop, mobile, HPC, e‐Infrastructure, …)
• People
(capacity, competencies, training, help, …)
“A collective term for the subordinate parts of an undertaking; substructure,
foundation; spec. the permanent installations forming a basis for military
operations, as airfields, naval bases, training establishments, etc.”
Oxford English Dictionary

5. Research Infrastructures support scholarly cycle
Source: Liz Lyon, www.ariadne.ac.uk, July 2003
and JISC/SURF/CNI Conference May 2005
Learning &
Teaching
workflows
Research &
Science
workflows
Aggregator
services: national,
commercial
Repositories :
institutional,
e‐prints, subject,
data, learning objects
Institutional
presentation
services: portals,
Learning
Management
Systems, u/g, p/g
courses, modules
Harvesting
metadata
Data creation /
capture /
gathering:
laboratory
experiments,
fieldwork,
surveys, media
Resource
discovery,
linking,
embedding
Deposit / self‐
archiving
Peer‐reviewed
publications: journals,
conference proceedings
Publication
Validation
Data analysis,
transformation,
mining, modelling
Resource
discovery, linking,
embedding
Deposit / self‐
archiving
Learning object
creation, re‐use
Searching ,
harvesting,
embedding
Quality assurance
bodies
Validation
Presentation services: subject, media‐specific, data, commercial portals
Resource
discovery, linking,
embedding

6. Collect
Assure
Describe
Deposit
Preserve
Discover
Integrate
Analyse
Data Lifecycle
Credit: W. Michener
Research & teaching (scholarly cycle) involves data

7. Collect
Assure
Describe
Deposit
Preserve
Discover
Integrate
Analyse
Data Lifecycle
Credit: W. Michener
Research Infrastructures support the data lifecycle
Data Acquisition
Data Access
Data Curation
Community Support
Data
Processing

8. Wide context of environmental RIs in Europe
Atmosphere Marine
Biosphere Solid Earth
Multi‐Domain

9. How we fit together: European view
Based on an original by Wouter Los, UvA
9
Reference data,
e‐Infrastructures
In situ,
In natura
Reference data
(collections, taxonomy, sequences, environmental)
Modelling and analysis
Observation and
monitoring data
Experimental
data
Data
mobilization
Knowledge
production

10. How we fit together: European view
Based on an original by Wouter Los, UvA
10
Reference data,
e‐Infrastructures
In situ,
In natura
Modelling and analysis
Observation and
monitoring data
Experimental
data
Data
mobilization
Knowledge
production
EUDAT EGI.eu PRACE
Life
Watch
ANAEE
BioVeL
LTER
Europe
SYN‐
THESYS
CETAF
BioCASE
MARS
PESI
Sp2000
CoL
WoRMS
Bio
FRESH
Sea
Data
Net
ELIXIR
MIRRI
Aqua
Maps
Synth.
centres
Scratch‐
pads
UvA
BiTS
Alien
Species
Italy
iMarine
INTER‐
ACT
EU BON EMBRC
EMSO

11. A few examples of infrastructure
11
Index of the world’s known species
> 1.6 million taxa (84%) from 151 databases
679 sites, > 6000 users
360+
datasets
Details of
800+
LTER sites
around
the World

12. You may have heard about it before
12
Progress at grass‐roots level
• particularly with national
initiatives
• and specific projects, like
BioVeL

13. A typical Research Infrastructure
Adapted from: Tjess Hernandez, VLIZ

14. www.biodiversitycatalogue.org
14

15. Credit: WCN247, Westminster College, New Wilmington, PA.
Equipping analysis labs for data intensive research

16. Credit: WCN247, Westminster College, New Wilmington, PA.
Equipping virtual labs for data intensive research
Biodiversity Virtual eLaboratory, http://portal.biovel.eu
http://www.uva‐bits.nl/virtual‐lab
Also, Marine VRE:
http://marinevre.lifewatch.be
https://www.analysisportal.se
http://www.iplantcollaborative.org

17. BioVeL Portal
17

18. Global Research Infrastructures
GBoWS Germplasm Bank of Wild Species,
also IB CAS, IOZ CAS
SANBI Integrated Biodiversity Information System (SIBIS)
Information System on Brazilian Biodiversity
Reference Center on Environmental Information

19. More examples
19
GBIF – 2 papers published every day

20. 20
287,768 files (4.2TB) from 25
member nodes and growing

21. Atlas of Living Australia
21
http://spatial.ala.org.au

22. How we fit together: Global view
22
Regional / national
Global
Data
mobilization
Knowledge
production
GBIF GeoBON
WFCC
(CAS)
LifeWatch
DataONE
CAS
genetics
resources CRIA/
SiBBr
Atlas
Living
Australia
NEON
SANBI
Competence
centres
Source: CReATIVE‐B project

23. 23
1. Increased global coordination and common
technical interoperability between RIs
2. Priority for discovery and access
3. Data and tools for research, management and
conservation
4. Effective governance for legal interoperability
5. Broker for scientists, policy and citizens

24. A recommended joint action plan: Support
development and testing of biodiversity indicators
24
Pursue it in GLOBIS‐B

25. No‐one is responsible for infrastructure.
We’re all responsible for infrastructure.
• A set of rules and standards
governs infrastructure
• Coordinating body(ies) to
apply them
• For us:
• In Europe, LifeWatch ERIC top‐down; community bottom‐up
• (USA for example) DataONE – Exec. Team, Leadership Team
and partners
• Globally, fledgling HLSG
25
Image courtesy of bluebay at FreeDigitalPhotos.net
ERIC = European Research Infrastructure Consortium
HLSG = High Level Stakeholders Group

26. Creating social value
from shared resources
• Open Science: opening (the process) of knowledge
creation and dissemination to a multitude of
stakeholders, including society in general.
• Commons: Community governed mechanism
reinforcing need of sharing in a way that allows
non‐discriminatory access, while ensuring
adequate controls to avoid congestion or depletion
when capacity is limited
• A backbone of data, e‐Infrastructures, instruments,
knowledge, expertise … overlain with related
community specific capabilities
26This is exactly the model we foresee for biodiversity and ecosystems research

27. Take home messages
• Research infrastructures help
data intensive science and
collaboration between scientists.
• Measuring and calculating EBVs
on a global scale are a unifying
use case to drive interoperability
across Research Infrastructures.
• No‐one is responsible for
research infrastructure.
We’re all responsible for
research infrastructure.
27
H is for Home, flickr.com