Global Research Infrastructures for Biodiversity and Ecosystems Research

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Ruth Fitzgerald
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1 Global Research Infrastructures for Biodiversity and Ecosystems Research Alex Hardisty Director of Informatics Projects School of Computer Science & Informatics /alexhardisty 1

Take home messages Research infrastructures help data intensive science

Measuring and calculating EBVs on a global scale are a unifying use

No one is responsible for research infrastructure.

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. Pedro Ribeiro Simões, flickr.com Goodmami, flickr.com Michael Bentley, flickr.com 2

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

4 Research infrastructures help data intensive science 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 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, )

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

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

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

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

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

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

11 A few examples of infrastructure 360+ datasets Details of 800+ LTER sites around the World 679 sites, > 6000 users Index of the world s known species > 1.6 million taxa (84%) from 151 databases11

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

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

14 14

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

16 Equipping virtual labs for data intensive research Credit: WCN247, Westminster College, New Wilmington, PA. bits.nl/virtual lab Also, Marine VRE: Biodiversity Virtual elaboratory,

17 BioVeL Portal 17

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

19 More examples GBIF 2 papers published every day 19

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

21 Atlas of Living Australia 21

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

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 23

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

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: Image courtesy of bluebay at FreeDigitalPhotos.net In Europe, LifeWatch ERIC top down; community bottom up (USA for example) DataONE Exec. Team, Leadership Team and partners Globally, fledgling HLSG ERIC = European Research Infrastructure Consortium HLSG = High Level Stakeholders Group 25

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.

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 This is exactly the model we foresee for biodiversity and ecosystems research 26

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. H is for Home, flickr.com 27

GLOBAL INFRASTRUCTURES FOR SUPPORTING BIODIVERSITY RESEARCH

GLOBAL INFRASTRUCTURES FOR SUPPORTING BIODIVERSITY RESEARCH Main problem to solve How can we measure and calculate Essential Biodiversity Variables (EBVs) on a global scale? Which variables are most meaningful?