Data accessibility and the role of informatics in predicting the biosphere
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The document discusses the need for improved predictive biosphere modeling through data accessibility and collaboration within the biodiversity informatics community. It emphasizes the importance of integrating diverse data sources and establishing standards to enhance data interoperability. The ultimate goal is to create a global, accessible dataset to better forecast ecosystem dynamics and biodiversity metrics.
Data accessibility and the role of informatics in predicting the biosphere
- 1. Data accessibility and the role of informatics in predicting the biosphere Alex Hardisty Director of Informatics Projects, School of Computer Science & Informatics Coordinator, FP7 BioVeL project www.biovel.eu email: [email protected] /alexhardisty (occasionally!) 1
- 2. Structuring the biodiversity informatics community at the European level and beyond Biodiversity Informatics Horizons 2013 180 experts conclude that there is “a growing need for predictive biosphere modelling” • Integration: Make better use of what we have • Cooperation: Data from the whole world is needed • Promotion: Europe is well placed to offer leadership 2
- 3. What if …? Imagine if we could … … Predict community level dynamics of ecosystems (i.e., behaviours) at scales from local to global, based on the ecology and biology of all individual organisms … e.g., Ecosystems: Time to model all life on Earth. Purves et al., Nature 493 (2013) Image: StuartMiles / FreeDigitalPh3otos.net
- 4. Imagine if we could … … Measure and calculate “Essential Biodiversity Variables” … … for any geographic area (continental, regional, local), by any person anywhere, using data for that area that may be held by any (research) infrastructure. Not only that, but also learn how to forecast EBVs 4
- 5. Depend on collaboration to deliver the evidence, i.e., based on synthesis and modelling of • Increasingly large amounts of data from multiple sources (environmental, taxonomic, genomic and ecological) • Gathered by manual observation and automated sensors, digitisation, nextgen sequencing and remote sensing Beyond the abilities of any one individual or any single research community to collect, observe or generate. Variety, Velocity and Volume of “Big Data” 5 Photo: Smokestacks against skyline and sunset, Estonia. © Curt Carnemark / World Bank Photo Collection
- 6. From informatics perspective, how close are we to that? Topical coverage 100% Data sharing and QC 100% 0% Data types Data source tracking Data citation tracking Data integration User applications & interfaces Funding Access policy Technology GIS Standards Data 9 research infrastructures from around the world exhibit “a satisfactory level of potential interoperability” Software architecture 100% 0% Programming languages Authentication Authorization Middleware Computing infrastructure Standards Technology Service logic 0% Geographical coverage Infrastructure topology Native interoperability and enablers Merging of science & policy needs Merging of science & industry needs Engagement of citizens Licensing and business model General 6
- 7. A computational challenge: Greater than that of weather forecasting; greater than that of climate prediction? Image from climateprediction.net HarfootMBJ, Newbold T, Tittensor DP, Emmott S, et al. (2014) Emergent Global Patterns of Ecosystem Structure and Function from a Mechanistic General Ecosystem Model. PLoS Biol 12(4): e1001841. doi:10.1371/journal.pbio.1001841 For 1km resolution, “… 3 to 6 orders of magnitude larger, … an exascale problem” Jack K. Horner Independent consultant & 7 Adviser to KU Biodiversity Institute
- 8. The situation today can be likened to meteorology in 1950’s, 60’s and 70’s (and later in climatology) when the emergence of numerical weather prediction drove demand for: • New observations • The emergence of a global infrastructure for acquiring, mobilising and normalising data, and • Better models of global atmospheric behaviour 8
- 9. Accessible data is useful data, not just for research Global policies/reports Regional policies/reports National policies/reports Data and information Direct provision of data/information Indirect provision through reports Assessment processes Green accounting etc 9 Diagram courtesy of EC FP7 EU BON project
- 10. To be able to predict the biosphere we need to mobilise data and make it accessible 10
- 11. It’s a journey towards • Global data, covering the whole planet. There are significant gaps everywhere today • Making all our small-scale, local data – which often characterises the current day practice of field ecology – global That is to say, we have to mobilise, clean, normalise and quality assure many small sets of data that together can give us the global data we need to calibrate models We are achieving that for certain classes of data but it is not without its difficulties 11
- 12. Issues arise in each of the 4 stages of mobilising data for synthesis • Data acquisition – Standardised measurement protocols • Data curation – Assigning right metadata and persistent identifiers – Finding a home for the data – and putting it there • Data discovery and access – Finding relevant data – Machine readable access to data i.e., WS front-end • Data processing / analysis, including re-use – Owners want attribution – Tracking provenance and follow licensing conditions – Problems at every step, on every workflow run http://envri.eu/rm 12
- 13. See also: “Showing you this map of aggregated bullfrog occurrences would be illegal” http://peterdesmet.com /posts/illegal-bullfrogs. html “Our analysis of the licenses of all 11.000+ GBIF registered datasets shows a bleak picture. Very few GBIF registered datasets can be easily and legally used, let alone without restrictions. This is mainly due to data being published with no or a non-standard license.” 13 Peter Desmet and Bart Aelterman, 22nd Nov 2013, peterdesmet.com
- 14. See also: “Showing you this map of aggregated bullfrog occurrences would be illegal” http://peterdesmet.com /posts/illegal-bullfrogs. html “Our analysis of the licenses of all 11.000+ GBIF registered datasets shows a bleak picture. Very few GBIF registered datasets can be easily and legally used, let alone without restrictions. This is mainly due to data being published with no or a non-standard license.” 14 Peter Desmet and Bart Aelterman, 22nd Nov 2013, peterdesmet.com
- 15. Data re-use: Owners want attribution Example 1) Taxonomic data refinement Workflow BioSTIF CoL 3 levels of attribution • complete work • contributing database of the record • expert who provides taxonomic scrutiny of the individual record. Tool license (s) GBIF data use agreement • Respect restrictions of access to sensitive data. • Identifier of ownership of data must be retained with every data record (through the workflow) • Publicly acknowledge the Data Publishers whose biodiversity data they have used. 15 • Any additional terms and conditions of use set by the Data Publisher.
- 16. More problems at every step, on every run Example 2) Niche Modelling Workflow Create model Model test Model projection High quality occurrence data set Select algorithm Select parameter values for the chosen algorithm Assemble the model on openModeller service Test the performance of the parameter in the model Test performance of the distribution prediction on the model Project Model with prediction layers Changing algorithm, parameter values, and set of layers Project Model with original layers Visualize and publish results Select layers with environmental factors that are likely to influence the distribution of the species Select prediction layers • License on algorithm • License on software Licenses on environmental data layers • Permissions to use • AuthN/AuthZ Moving data from one service to another • 3rd party software • All issues associated with publication 16
- 17. In a recent EU BON study Only 35% of surveyed datasets (wider scope than just GBIF) are accessible under an open license or waiver, without restriction on use For 29 scientific questions relating to needs of European environmental policy, the availability of datasets to answer the questions is in the range ‘satisfactory’ (3) to ‘poor’ (2) 17
- 18. Multiple initiatives to make data more accessible; some are general purpose https://rd-alliance.org/ … builds the social and technical bridges that enable open sharing of data … researchers and innovators openly sharing data across technologies, disciplines, and countries to address the grand challenges of society. http://www.datafairport.org/ … successful community supported conventions, policies and practices for data identifiers, formats, checklists and vocabularies that enable data interoperability, citation and stewardship. ORCID and DataCite initiatives to uniquely identify (respectively) scientists and data sets 18
- 19. Some are more domain specific Promoting free and open access to biodiversity information A framework to focus effort and investment to deliver biodiversity knowledge more effectively www.biodiversityinformatics.org/ www.bouchout-declaration.org 19
- 20. A shared and maintained multi-purpose network of computationally-based processing services in an open data domain Image: CoolDesign / FreeDigitalPh2o0tos.net With 78 contributors, we published the whitepaper, April 2013 - since viewed more than 34,000 times.
- 21. Building a heterogeneous Service Network 21 Users’ workflows and applications Sustained Service and Data Providers GBIF, CoL, OBIS, WoRMS, EMBL-EBI, BGBM, CRIA, EoL, BHL, ALA, LTER, etc. & more. www.biodiversitycatalogue.org Recognised and stable Infrastructure Providers National, EGI.eu, PRACE, commercial, EUDAT, etc.
- 22. Preparing the next, coordinated steps 22 Diagram from LinkD Concept Note, September 2014
- 23. LinkD Develop the highly responsive digital framework required to enable high throughput research and support science of scale towards the long term vision of modelling Life on Earth LinkD Science of Scale for L i fe on Ear th What we want to do in LinkD? ELODINS ENVRI+ From slides by Vince Smith, LinkD proposal coordinator, Natural History Musuem, London
- 24. Take home message: “It’s a journey” • Accessible data is the enabler of “in-silico” science that leads towards predicting the biosphere • A shared multi-purpose network of processing services, sitting on top of open data is the route to interoperability •Working together as a community is essential 24 Photo: A lone farmer walks among rice paddies. © DFATD-MAECD/Tick Collins
Editor's Notes
- #16: (s)
- #24: Inspired by roadmap publications such as GBIO and the White paper. Mandated by European and global societal challenges. Supported by the maturity of the available foundational e-Infrastructures. Science of Scale: To maximize the efficiency of the available data, services and tools. This is what the commission calls science 2.0. In short is using economies of scale in data collection and associated infrastructure to do big things.