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Fisheries Linked Open Data - Claudio Baldassare
Fisheries Linked Open Data - Claudio Baldassare
Fisheries Linked Open Data - Claudio Baldassare
Fisheries Linked Open Data - Claudio Baldassare
Fisheries Linked Open Data - Claudio Baldassare
Fisheries Linked Open Data - Claudio Baldassare
Fisheries Linked Open Data - Claudio Baldassare
Fisheries Linked Open Data - Claudio Baldassare
Fisheries Linked Open Data - Claudio Baldassare
Fisheries Linked Open Data - Claudio Baldassare
Fisheries Linked Open Data - Claudio Baldassare
Fisheries Linked Open Data - Claudio Baldassare
Fisheries Linked Open Data - Claudio Baldassare
Fisheries Linked Open Data - Claudio Baldassare
Fisheries Linked Open Data - Claudio Baldassare
Fisheries Linked Open Data - Claudio Baldassare
Fisheries Linked Open Data - Claudio Baldassare
Fisheries Linked Open Data - Claudio Baldassare
Fisheries Linked Open Data - Claudio Baldassare
Fisheries Linked Open Data - Claudio Baldassare
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Fisheries Linked Open Data - Claudio Baldassare

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NPOs and NGOs are acting more-and-more as open data providers for various stakeholders like citizens, enterprises and communities. Linked open data becomes a key concept to meet several demands of …

NPOs and NGOs are acting more-and-more as open data providers for various stakeholders like citizens, enterprises and communities. Linked open data becomes a key concept to meet several demands of information professionals, for instance interoperability and accessibility of data, multilinguality and harmonisation of metadata.

The open data value chain is about to change from a rather simple to a more complex network of data streams which produces new revenue models and more differentiated roles – linked open data plays a central role in this development.

This webinar is about the use of linked open data and controlled vocabularies in the specific enviroments, NGOs and NPOs are working in. Get an overview about the underpinning motivation and concepts which drive the very concrete use cases which will be presented:

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  • Start introducing MDMA wide area of technological investigation in FAO (ref. from francesco, blog entry)FLOD is an instance of MDM hence inherits the features, the principles the business benefits, do that any applied technology to tackle a challenge that is localized in the fisheries domain could be elevated and shared for the enterprise master data management.
  • Start introducing MDMA wide area of technological investigation in FAO (ref. from francesco, blog entry)FLOD is an instance of MDM hence inherits the features, the principles the business benefits, do that any applied technology to tackle a challenge that is localized in the fisheries domain could be elevated and shared for the enterprise master data management.
  • Application scenariosStatisticsGISAnnotatorAdvanced searchKnwledge bridgefactsheet,spread
  • Application scenariosStatisticsGISAnnotatorAdvanced searchKnwledge bridgefactsheet,spread
  • Application scenariosStatisticsGISAnnotatorAdvanced searchKnwledge bridgefactsheet,spread
  • Application scenariosStatisticsGISAnnotatorAdvanced searchKnwledge bridgefactsheet,spread
  • Application scenariosStatisticsGISAnnotatorAdvanced searchKnwledge bridgefactsheet,spread
  • Start introducing MDMA wide area of technological investigation in FAO (ref. from francesco, blog entry)FLOD is an instance of MDM hence inherits the features, the principles the business benefits, do that any applied technology to tackle a challenge that is localized in the fisheries domain could be elevated and shared for the enterprise master data management.
  • What is the current status with respect to:A terminology is made of codes and names with multiple translations, hence also named codelist, sometimes controlled terms. Is a reference for one or multiple communities of practice and is organized in a hierarchical way.In some operational scenarios of data aggregation (e.g. statistics of global fish captures ) locally identified fishing gears, vessels, marine species need to be reduced to global code lists like FI ownsSome times the level of detaisamog terminologies/codelist is heterogeneous so that for one term/code n terms appear in another list
  • What is the current status with respect to:Managing multiple vocabulariesManging multilingualGovernanceImport exportIntegration with other services
  • What is the current status with respect to:Managing multiple vocabulariesManging multilingualGovernanceImport exportIntegration with other services
  • I left governace at last because is the aspect where we need more spin to boot strap the activityWe are trying to apply governance from iMarin project
  • Transcript

    • 1. Fisheries Linked Open Data HARMONIZATION AND INTERLINKING OF FISHERY REFERENCE TERMINOLOGIES CLAUDIO BALDASSARRE
    • 2. Outline Fisheries Linked Open Data  Harmonization  Interlinked Domains  Application Scenarios FLOD Consumer Applications FLOD as Master Data Management  Objectives, Challenges and Current Status
    • 3. Fisheries Linked Open Data A core of code lists that are references for statistical reports or data dissemination (e.g. yearbooks, web portals). The codes are associated to terms (and translations) to provide controlled vocabularies.  Fishing gears (ISSCGF) ex: purse seines - 01.1.0  Fishing vessels (ISSCVF) ex: purse seiners - 02.1.0  Fishing Area (FAO ) ex: western Mediterranean – 37.1  Marine species (ASFIS) ex: yellow fin tuna - YFT A dense network of cross domain relationships.  e.g. Sovereignty of a Country on Exclusive Economic Zone  e.g. Participation of a Country in fishing agreements Serves fishery communities of practice inside and outside FAO  Statisticians, Marine Scientists, Content Mangers
    • 4. Purse Seines and Purse Seiners
    • 5. Harmonization Supports statisticians inFLOD Fishery Statistics Fisheries Division to aggregate catch statistics from regional to en: Yellow Fin Tuna, global level. es : Rabil fr : Albacore lt : Thunnus Albacares asfis : YFT taxonomic : 1750102610 worms : 127027 aquamaps : 22833 fishbase : 22833
    • 6. Interlinked Domains  Enables users to formulate Land Geo- Politics complex requests leveraging cross-domain connections: Marine  Amount of fish caught in 2008 in Danish Fishery Geo- Statistics Politics Exclusive Economic Zone by vessels that practice fishing with traps? FLOD  Catch statistics reported in FAO subdivisions intersecting the marine areas sovereigned Fishery Fishery by Denmark? Vessels Technique  Countries interested in the expiration of the Fishery legal agreements involving FAO fishing area Legislation 18 ending in year 2012?Driving Competency Question: all deep-water species member of family x and family y that are criticallyendangered and predominately feed on prey species z that occur in this LME but only between latitudes Aand B, and longitudes C and D
    • 7. Application Scenarios  Reallocate species catch statistics Land Geo- Politics based on geospatial information, Marine and fishing agreements. Fishery Geo- Statistics Politics  Generate landing pages populated with data from remote FLOD open linked datasets. Fishery Fishery  Enhance search by exploiting Vessels Technique network of connections in FLOD. Fishery Legislation  Document retrieval driven by contextual information.Driving Competency Question: all deep-water species member of family x and family y that are criticallyendangered and predominately feed on prey species z that occur in this LME but only between latitudes Aand B, and longitudes C and D
    • 8. FLOD Portal: Harmonization Exposed Search for reference terms Display alternative codes from harmonized code lists Display translation for the controlled term Display meta information on data provenance (i.e. rights holder and publisher) Multilingual auto completion to avoid spelling errors All data are exposed through the FLOD SPARQL endpoint
    • 9. FLOD Portal: Network of Publications Display a list FLOD individuals annotating this publication. Display the occurrence of the user query in a specific page of the publication. Display provenance information for this publication. Multilingual auto completion to avoid spelling errors All data are exposed through the FLOD SPARQL endpoint
    • 10. Enrich User Information Context Mine FLOD entities into the web page browsed by the users Enrich the content with data from the FLOD SPARQL endpoint retrieved through the hyperlinks Provides an alternative to search the portal or the SPARQL endpoint for casual users
    • 11. SPREAD: Time Series Spatial Reallocation Retrieves all Exclusive Economic Zone where a Country is allowed to fish. Retrieves reference species codes from regional code lists Retrieves spatial intersection of fishing areas Retrieves fishing rights based on fishing agreements All data are stored in the FLOD SPARQL endpoint
    • 12. Smart Time Series Mine FLOD entities into catch time series (i.e. species, water areas, country) Leverage the network of FLOD to associate geo- referential data to geographic entities (e.g. water areas) Generate KLM model including references to the entities URIs found in each statistical record Map time series records on Google map
    • 13. FLOD as Master Data Management Master Data Management is a wide area of technological investigation in FAO to identify a toolkit that enables the management/maintenance of reference data at corporate level.MDM Principles Features • Managing Multiple Vocabularies/Classifications and their Cross Mappings • Multilingual Services • Import/Export Routines Supporting Multiple Formats • Integration with Existing Tools and Systems through open APIs/Web services • Governance (data ownership and update workflows) BenefitsFLOD FLOD projects inherits the definition of principles and the benefits of MDM, and develops MDM features with the adoption of semantic technologies.
    • 14. Vocabularies and their Cross Mappings Objectives  Align reference terminologies of fishing gears, vessels, marine species and fishing areas.  Link individuals of fishing gears, vessels, marine species, fishing and administrative sea areas, geo-political territories, legal and governmental entities. Challenges  Evolve from an hierarchical structure to a data model design enabling accurate alignment and linking capabilities w.r.t. the heterogeneity of classifications granularity. Current status  FLOD is designed by architecting modules of part-whole, constituency, collection, and other reusable ontology engineering patterns.  Ingestion workflows are in place from structured sources of terminologies and relationships to generate linked datasets.
    • 15. Multilingual Services Objectives  Associate the name(s) of the reference terminologies among the variety of lexicalizations of local usage  Track evolution of lexicalizations over time. Challenges  A descriptive semantic model for lexicalizations that responds to the needs of selecting the appropriate name(s) in the user information context. Current status  FLOD implements most known RDFS:label property with metadata on language; it defers information on more lexicalizations or name change to the source system of names provenance.
    • 16. Import/Export Routines Objectives  Streamline workflows of data import and conversion to RDF.  Record and store versions of imported data.  Selective maintenance operations targeting specific datasets. Challenges  A framework for ETL operations for system administrator with low or no knowledge of linked datasets.  Keep synchronization among data sources and linked dataset on regular basis, with control on versioning. Current status  Semi-automatic processes of reading and casting reference terminologies in to datasets through FLOD ontology modules.  Each dataset receives a timestamp as an explicit metadata at its creation.
    • 17. Integration with Existing Tools and Systems Objectives  Homogeneously search remote reference terminologies hosted in a combination of DBs and KBs.  Empower search engines with query expansion based on the knowledge available in FLOD.  Expose knowledge base content trough RDF agnostic API. Challenges  Define a top level domain ontology that contains the reference super concepts to address the reference terminologies.  Implement a mechanism to cast user terms as individuals or concepts in the top level ontology. Current status  An implementation of OpenSearch with semantic extension is being prepared to enable query services on top of FLOD SPARQL endpoint.  FLOD portal includes spelling support to convert user query terms in to references to FLOD individuals.
    • 18. Governance Objectives  Model the role and activity of the data providers with explicit reference to owner, publisher, rights holder, right to update, and system of provenance.  Inject the Import/Export maintenance routine with the roles and activity of governance. Challenges  Identify licensing schemas that can drive the modeling activity. Current status  Round tables on governance have been started in contexts where the data providers have active participation.
    • 19. Conclusions FLOD represents a source of harmonized reference data and controlled terms for applications of statistics and marine science. FLOD it is consumed by applications in need to aggregate either data instances, or documental resources relevant to users’ need (e.g. search or context). FLOD approach to maintenance of linked reference datasets leads to a decentralized maintenance effort under the responsibility of respective data owner. FLOD roadmap is at point where robust maintenance framework and a scalable operational infrastructure are recommended. Where FLOD approach to code lists and controlled terms maintenance proves to be successful it can provide good practice and recommendations to corporate Master Data Management.
    • 20. Acknowledgements iMarine project supports the development of:  FLOD Web Portal  SPREAD geospatial reallocation engine  FLOD content enricher iMarine: http://www.i-marine.eu/

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