BiOnym

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BiOnym

  1. 1. iME4d - BiOnym A concept-mapping workflow for taxon names reconciliation Friday 7 March 2014 – Rome A concept-mapping workflow for taxon names reconciliation Fabio Fiorellato, Edward Vanden Berghe, Gianpaolo Coro, Nicolas Bailly
  2. 2. Big Data make its way to biology • Data volumes increase dramatically – Management of large databases (millions of records) easier • no longer the realm of professional IT people• no longer the realm of professional IT people – Biologists wake up to the advantages of • Good data management, including preservation • Data sharing • Makes it possible to do science in a different way
  3. 3. ‘Big Data’: Need for data integration • Becoming a very realistic possibility – Management of DBs of millions of records • Needs integration of small, restricted-scope datasets into massive databasesdatasets into massive databases – Intra-discipline integration (homogenous) – Inter-discipline integration (heterogeneous) • Individual studies too small to inform on a scale commensurate with problems humankind faces – Evidence-based management of living resources – Climate change, global warming…
  4. 4. iMarine biodiversity ‘ecosystem’ Taxon name enrichment Taxon name reconciliationTaxon name access Occurrence data access Environmental data access openModeller AquaMaps Distribution modelling Occurrence data enrichment Occurrence data reconciliation
  5. 5. Central role of taxon name reconciliation Taxon name enrichment Taxon name reconciliationTaxon name access Occurrence data access Environmental data access openModeller AquaMaps Distribution modelling Occurrence data enrichment Occurrence data reconciliation
  6. 6. Taxonomic names are the keys… • … Keys to bind together information on the same taxon from different sources • But there are problems• But there are problems – Different research groups use different spellings – Accidental misspellings – Synonym, homonym reconciliation (but outside scope of ByOnym)
  7. 7. Some people can’t type • Asthenognathas inaefaipes • Asthenognathus inaeqipes • Asthenognathus maefaipes• Asthenognathus maefaipes • Astheognathus inaequipes • Asthenognathus inaeguipes • Astheognathus inaeqinipes • Asthenognathus inaequipes
  8. 8. Things can go wrong with Excel… • Clupea harengus Linnaeus, 1758 • Clupea harengus Linnaeus, 1759 • Clupea harengus Linnaeus, 1760• Clupea harengus Linnaeus, 1760 • Clupea harengus Linnaeus, 1761 • Clupea harengus Linnaeus, 1762 • …
  9. 9. … very wrong • Clupea harengus Linnaeus, 1758 • Clupea harengus Linnaeus, 1759 • Clupea harengus Linnaeus, 1760• Clupea harengus Linnaeus, 1760 • … • Clupea harengus Linnaeus, 2254 • Clupea harengus Linnaeus, 2255
  10. 10. Taxonomic names are the keys… • … Keys to bind together information on the same taxon from different sources • But there are problems• But there are problems – Different research groups use different spellings – Accidental misspellings • Reconciliation is necessity, not luxury!!!
  11. 11. Existing systems… • … Are not flexible – We need flexibility, as our use case will dictate what the ‘optimal’ behaviour of the system is • E.g. manual vs automatic systems • … Are often coupled to a single ‘reference list’• … Are often coupled to a single ‘reference list’ – Using different tax. Scope for test and reference only increases false positives • E.g. TaxaMatch with IRMNG… • …Don’t always have throughput needed for large-scale projects – Largest db appr. 20M names – too many pairs!
  12. 12. Our need • A flexible, highly customisable, workflow- based approach to taxon name matching – User controls input – Output can be used as input in other– Output can be used as input in other processes – Running on high performance computing infrastructure BiOnym!
  13. 13. Introduction to BiOnym • As a workflow for taxon name mapping and reconciliation, it is a real-world application of the concept-mapping principles • It is focused on the domain of taxonomy, with an initial restriction to marine species only • Provides a full workflow (not only the concept mapping part) • Tries to address - and possibly solve - many issues common to• Tries to address - and possibly solve - many issues common to the taxonomic community • Its key concept is “species taxonomy”, where concept properties are the taxonomic atoms • Is open to integration from third party components • Takes advantage of the iMarine distributed infrastructure
  14. 14. The iMarine solution: existing state-of-the-art • A general purpose concept mapping framework (COMET) was already available in FAO: – based on an existing FAO product (limited to the fishing vessels domain) initially developed with the support of the Japanese trust fund – domain independent (can be tailored to any custom– domain independent (can be tailored to any custom domain with little effort) – provided with all the necessary building blocks and components for general purpose usage
  15. 15. The iMarine solution: the quest for integration • The integration of COMET inside iMarine was hailed and expected. • Its main challenges: – Identify and define the custom domain (biological taxonomy) – Design and implement: • custom COMET matchlets (engine assigning similarity scores to pairs of names) • additional, reusable tools for data interchange and data preparation (DwCA converter, input parser, pre- and post-processors) – Enable components to be easily distributed among worker nodes inside the infrastructure – Integration in the iMarine Statistical Manager
  16. 16. The iMarine solution: a success story • The COMET integration inside iMarine, as part of the BiOnym workflow, is an example of success story: – Solving the integration challenges required limited effort • Harvest names for input through iMarine tools • Send output from BiOnym/COMET on to further tools – The core matching capabilities of BiOnym were first made– The core matching capabilities of BiOnym were first made available in June 2013 • Pre- and post-processing; parsing • Matching through (a series of) matchlets, assigning a similarity score to pairs of names – The modular architecture enabled developers to add new functionalities or improve existing ones with ease
  17. 17. BiOnym key concepts and features • Its modular architecture is open to contribution and alternatives – Workflow stages can be plugged-in with custom business implementations – Can leverage third party components (e.g. the input data parsing is available both as an in-house component or as a wrapper of the GNI parser from globalnames.org) • Based on standard and open formats• Based on standard and open formats – Reference data are synthesized from DWCA files – Input data and matching results are expected and produced as CSV files – Matching results can also be emitted as XML files in the COMET format • High flexibility – Multiple chained matchers, each with its own configuration and thresholds – Third party matchers (e.g. Tony Rees’ TaxaMatch) can be seamlessly ‘wrapped’ and plugged in the workflow – Support for collaborative matching results evaluation (expected soon)
  18. 18. BiOnym System: Overview
  19. 19. BiOnym Workflow
  20. 20. Where are we? • Infrastructure has largely been built • User-friendly GUI is under development • Evaluation – Efficiency: speed of computations– Efficiency: speed of computations • Parallel system, compares well with others – Effectiveness: are the results OK? • Ran experiments on different test datasets – Deliberately introducing misspellings in known lists – ‘Real’ misspellings manually corrected for other purposes
  21. 21. The Bionym Interface Never mind the small print. Step 1: Select your data Step 2: Compose the matching process. This relies on infrastructure resources Step 3: review results. This can be private and ‘for your eyes only’, or public.
  22. 22. The BiOnym Workflow
  23. 23. Visualising quality assessment of the results of BiOnym
  24. 24. Where to from here? • Validation – Not in terms of quality of output but… – Uptake by the biodiversity community • Sustainability• Sustainability – Who will take over maintenance after iMarine ends? • BiOnym is a tool, it is the means to an end – Support Ecosystem Approach to Fisheries
  25. 25. iMarine biodiversity ‘ecosystem’ Taxon name enrichment Taxon name reconciliationTaxon name access Occurrence data access Environmental data access openModeller AquaMaps Distribution modelling Occurrence data enrichment Occurrence data reconciliation
  26. 26. BiOnym in its environment Ecological modelling – Rich data management Taxa Authority FileTaxa Authority File Vernacular Names Authority File Vernacular Names Authority File Darwin Core ArchiveDarwin Core Archive Based on the COMET Framework developed by Fabio Fiorellato (FAO)
  27. 27. Biodiversity Maps Generation Retrieve via any GeoNetwork Ecological modelling - Processing

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