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Global Research Infrastructures 
for Biodiversity and Ecosystems 
Research
Alex Hardisty
Director of Informatics Projects ...
Take home messages
• Research infrastructures help data intensive science 
and collaboration between scientists.
• Measuri...
Fig.1. Workflow for estimating SD, FD, and ES potential for tropical South America.
Molecular Ecology Resources
19 NOV 201...
Research infrastructures help data intensive science
Simply:
Anything semi‐permanent that researchers 
need to do their jo...
Research Infrastructures support scholarly cycle
Source: Liz Lyon, www.ariadne.ac.uk, July 2003
and JISC/SURF/CNI Conferen...
Collect
Assure
Describe
Deposit
Preserve
Discover
Integrate
Analyse
Data Lifecycle
Credit: W. Michener
Research & teaching...
Collect
Assure
Describe
Deposit
Preserve
Discover
Integrate
Analyse
Data Lifecycle
Credit: W. Michener
Research Infrastruc...
Wide context of environmental RIs in Europe
Atmosphere Marine
Biosphere Solid Earth
Multi‐Domain
How we fit together: European view
Based on an original by Wouter Los, UvA
9
Reference data,
e‐Infrastructures
In situ,
In...
How we fit together: European view
Based on an original by Wouter Los, UvA
10
Reference data,
e‐Infrastructures
In situ,
I...
A few examples of infrastructure
11
Index of the world’s known species
> 1.6 million taxa (84%) from 151 databases
679 sit...
You may have heard about it before
12
Progress at grass‐roots level
• particularly with national 
initiatives
• and specif...
A typical Research Infrastructure
Adapted from: Tjess Hernandez, VLIZ
www.biodiversitycatalogue.org
14
Credit: WCN247, Westminster College, New Wilmington, PA.
Equipping analysis labs for data intensive research
Credit: WCN247, Westminster College, New Wilmington, PA.
Equipping virtual labs for data intensive research
Biodiversity V...
BioVeL Portal
17
Global Research Infrastructures
GBoWS Germplasm Bank of Wild Species,
also IB CAS, IOZ CAS
SANBI Integrated Biodiversity I...
More examples
19
GBIF – 2 papers published every day
20
287,768 files (4.2TB) from 25 
member nodes and growing
Atlas of Living Australia 
21
http://spatial.ala.org.au
How we fit together: Global view
22
Regional / national
Global
Data
mobilization
Knowledge
production
GBIF GeoBON
WFCC 
(C...
23
1. Increased global coordination and common 
technical interoperability between RIs
2. Priority for discovery and acces...
A recommended joint action plan: Support 
development and testing of biodiversity indicators
24
Pursue it in GLOBIS‐B
No‐one is responsible for infrastructure.
We’re all responsible for infrastructure.
• A set of rules and standards
governs...
Creating social value 
from shared resources
• Open Science: opening (the process) of knowledge 
creation and disseminatio...
Take home messages
• Research infrastructures help
data intensive science and
collaboration between scientists.
• Measurin...
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Global Research Infrastructures for Biodiversity and Ecosystems Research

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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.

Published in: Technology

Global Research Infrastructures for Biodiversity and Ecosystems Research

  1. 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. 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. 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. 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. 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. 6. Collect Assure Describe Deposit Preserve Discover Integrate Analyse Data Lifecycle Credit: W. Michener Research & teaching (scholarly cycle) involves data
  7. 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. 8. Wide context of environmental RIs in Europe Atmosphere Marine Biosphere Solid Earth Multi‐Domain
  9. 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. 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. 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. 12. You may have heard about it before 12 Progress at grass‐roots level • particularly with national  initiatives • and specific projects, like  BioVeL
  13. 13. A typical Research Infrastructure Adapted from: Tjess Hernandez, VLIZ
  14. 14. www.biodiversitycatalogue.org 14
  15. 15. Credit: WCN247, Westminster College, New Wilmington, PA. Equipping analysis labs for data intensive research
  16. 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. 17. BioVeL Portal 17
  18. 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. 19. More examples 19 GBIF – 2 papers published every day
  20. 20. 20 287,768 files (4.2TB) from 25  member nodes and growing
  21. 21. Atlas of Living Australia  21 http://spatial.ala.org.au
  22. 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. 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. 24. A recommended joint action plan: Support  development and testing of biodiversity indicators 24 Pursue it in GLOBIS‐B
  25. 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. 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. 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

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