Tuna atlas

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Tuna atlas

  1. 1. iME4a. iMarine Tuna AtlasiME4a. iMarine Tuna Atlas Marc Taconet/ Anton Ellenbroek / Yann Laurent FAO Fisheries Department
  2. 2. Tuna Atlas Presentation Outline • Collection • Harmonization • Aggregation Tuna Atlas Use Case Tuna Atlas Data Analysis and Dissemination • Code List Management • Mapping and mapping; COTRIX and GEO-Explorer • Statistical data analysis • Spatial Data Analysis; SPREAD, • Storage and Dissemination; SDMX and FIRMS Tuna Atlas Data Analysis and Dissemination The results and summary iMarine Event - 7 March 2014 – FAO-Rome 2
  3. 3. The Tuna Atlas use case the seascape Collection HarmonizationHarmonization Aggregation iMarine Event - 7 March 2014 – FAO-Rome 3
  4. 4. Data Collection • FAO compiles global tuna nominal catches and tuna and billfishes catches (Tuna Atlas) annually • Loaded in a database and published on-line: – http://www.fao.org/fishery/statistics/tuna- catches/query/en Tuna Atlas Use Case catches/query/en – http://www.fao.org/figis/geoserver/tunaatlas/ • Mostly manual, data sources are heterogeneous • How can a VRE improve the collection process? 4iMarine Event - 7 March 2014 – FAO-Rome
  5. 5. • Convert to one standard structure • Validate against reference standards (e.g. to the ISSCFG / ASFIS / ISO Country code list) • Validate content (errors, gaps, formats) Time series harmonization Tuna Atlas Use Case • Validate content (errors, gaps, formats) • Reconcile with existing data (older) • How can a VRE produce Harmonized time series for analysis, mapping, publication 5iMarine Event - 7 March 2014 – FAO-Rome
  6. 6. Aggregation; much more than the sum of all contributions, about more than data • Policy framework for co-management of tuna data: – based on Open Access / Open Data – sharing data, tools and processes – software development policies – Guidelines and best practices Tuna Atlas Use Case – Guidelines and best practices • Policy for governance – Any institution can become an iMarine partner – Everybody can be part of the development of the tools • How can a VRE deliver flexible interoperable data sharing; FIRMS aggregation offers leading examples 6iMarine Event - 7 March 2014 – FAO-Rome
  7. 7. Harmonization • Code list management • Data validation • Shared formats (SDMX) • Shared standard (FLUX) Aggregation • Fisheries • Vessel data • Occurrences TA Requirements summary Tabular Data Policy Guidelines Best Practices AnalysisAnalysis • Time series Sharing • Repositories • Open Data • Fact sheets • Print Collection • Multiple formats • Multiple structure • Multiple domains • Data quality MapDisplay • GeoCode • Store and synchronize • Project and share iMarine Event - 7 March 2014 – FAO-Rome 7 Tabular Data Management • Time series trends • Forecasting • Modelling
  8. 8. Tuna Atlas Data Analysis and Dissemination a selection of components Code list management Mapping iMarine Event - 7 March 2014 – FAO-Rome 8 Spatial Data Reallocation Analysis Storage and dissemination
  9. 9. iMarine network of interoperable, managed and shared resources TA Analysis and Dissemination components iMarine Event - 7 March 2014 – FAO-Rome 9
  10. 10. • TabMan supports the validation and harmonization of tuna atlas data – Code list manager exposes reference data (including from RFMO) TA Analysis and Dissemination components Code list management (including from RFMO) – Code lists are easily added in a VRE • COTRIX will extend this support – Manage code lists ‘outside’ iMarine – Living apart together …. Remote but integrated iMarine Event - 7 March 2014 – FAO-Rome 10
  11. 11. Cotrix Import Manage, Publish Code Lists iMarine Event - 7 March 2014 – FAO-Rome 11
  12. 12. TA Analysis and Dissemination components Mapping 1 Link data: Occurrences Enrichment Associate Environmental information to a set of occurrence points of a species using their code lists iMarine Event - 7 March 2014 – FAO-Rome 12
  13. 13. Spatial Data Reallocation Reallocate from FAO areas to EEZ Change spatial resolution and precision of capture data to better understand fisheries • SPREAD use FIGIS geospatial data• SPREAD use FIGIS geospatial data infrastructure and iMarine • Spread data processing with WPS using Terradue resources iMarine Event - 7 March 2014 – FAO-Rome 13
  14. 14. SPREAD WPS Select an external process Remote resource iMarine Event - 7 March 2014 – FAO-Rome 14 Parameters for the re-allocation
  15. 15. Statistical Manager; Operators E.g to extract indicators from Tuna Atlas data • Tabular data can be processed to e.g.: – Spatial data reallocation => SPREAD – (Species) name reconciliation => BiOnym TA Analysis and Dissemination components – Trend Analysis => Trendylyzer – Bayesian modelling => FishBayes • Select your algorithm and resources – Algorithms can be predefined, or bring your own – Resources in infra, remote, or cloud iMarine Event - 7 March 2014 – FAO-Rome 15
  16. 16. Integrating WPS with the D4Science e-Infrastructure D4Science Information System Other D4Science Facilities E.g. Storage, Social, Geo AnotherAnother External (Cloud) Computing Facility WPS Interface WPS Interface Statistical Manager Services Statistical Manager Services D4Science Cloud Computing User System User’s Data 101010101 Processing WPS
  17. 17. Example: Occurrence Enrichment Occurrences Table with fields indication iMarine Event - 7 March 2014 – FAO-Rome 17 User-defined spatial resolution for the projection Layers: inputs can be i-Marine Geonetwork UUIDs or Titles, or direct external HTTP links to files Supported Formats: WCS, WFS, NetCDF, ASC, GeoTiffs Names of the environmental features
  18. 18. Mapping; Project aggregated data Effort indicator iMarine Event - 7 March 2014 – FAO-Rome 18
  19. 19. • SDMX one option for Tuna Atlas data storage • Tabular data are easily exposed as Open Data (as Chimaera will explain) • Tabular data can be extracted and included in iMarine infrastructure Components Data storage, sharing and dissemination Example options • Tabular data can be extracted and included in iMarine information fact-sheets such as VME-DB • Tabular data can be displayed on maps and stored as map-products • Dissemination can also rely on sharing through mail, the workspace, or download 19
  20. 20. Not a product, but an advanced solution • A pool of tools: – SDMX format / registry to facilitate data exchange – An opportunity to access a rich library of integrated tools • Time series presented as Graphs, Maps • Code lists manager to share reference data and mapping • Standard Mapping capacities • R statistical capacities for advanced data analysis and processing TA Results • R statistical capacities for advanced data analysis and processing • Access to remote data (write your own plugin) – Environmental – Biodiversity – Fisheries • A Collaborative managed infrastructure – Policies, basic best practices, and generic guidelines 20FIRMS SC8 – Rome – Feb 2013

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