Assisting Biologists in Editing Taxonomic Information by Confronting Multiple Data Sources using Linked Data Standards
During the last decade, Web APIs (Application Programming Interface) have gained significant traction to the extent that they have become a de-facto standard to enable HTTP-based, machine-processable data access. Despite this success, however, they still often fail in making data interoperable, inso...
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description | During the last decade, Web APIs (Application Programming Interface) have gained significant traction to the extent that they have become a de-facto standard to enable HTTP-based, machine-processable data access. Despite this success, however, they still often fail in making data interoperable, insofar as they commonly rely on proprietary data models and vocabularies that lack formal semantic descriptions essential to ensure reliable data integration. In the biodiversity domain, multiple data aggregators, such as the Global Biodiversity Information Facility (GBIF) and the Encyclopedia of Life (EoL), maintain specialized Web APIs giving access to billions of records about taxonomies, occurrences, or life traits (Triebel et al. 2012). They publish data sets spanning complementary and often overlapping regions, epochs or domains, but may also report or rely on potentially conflicting perspectives, e.g. with respect to the circumscription of taxonomic concepts. It is therefore of utmost importance for biologists and collection curators to be able to confront the knowledge they have about taxa with related data coming from third-party data sources.
To tackle this issue, the French National Museum of Natural History (MNHN) has developed an application to edit TAXREF, the French taxonomic register for fauna, flora and fungus (Gargominy et al. 2018). TAXREF registers all species recorded in metropolitan France and overseas territories, accounting for 260,000+ biological taxa (200,000+ species) along with 570,000+ scientific names. The TAXREF-Web application compares data available in TAXREF with corresponding data from third-party data sources, points out disagreements and allows biologists to add, remove or amend TAXREF accordingly. This requires that TAXREF-Web developers write a specific piece of code for each considered Web API to align TAXREF representation with the Web API counterpart. This task is time-consuming and makes maintenance of the web application cumbersome.
In this presentation, we report on a new implementation of TAXREF-Web that harnesses the Linked Data standards: Resource Description Framework (RDF), the Semantic Web format to represent knowledge graphs, and SPARQL, the W3C standard to query RDF graphs. In addition, we leverage the
SPARQL Micro-Service
architecture (Michel et al. 2018)
,
a lightweight approach to query Web APIs using SPARQL. A SPARQL micro-service is a SPARQL endpoint that wraps a Web API service; it typically produces a smal |
doi_str_mv | 10.3897/biss.3.37421 |
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To tackle this issue, the French National Museum of Natural History (MNHN) has developed an application to edit TAXREF, the French taxonomic register for fauna, flora and fungus (Gargominy et al. 2018). TAXREF registers all species recorded in metropolitan France and overseas territories, accounting for 260,000+ biological taxa (200,000+ species) along with 570,000+ scientific names. The TAXREF-Web application compares data available in TAXREF with corresponding data from third-party data sources, points out disagreements and allows biologists to add, remove or amend TAXREF accordingly. This requires that TAXREF-Web developers write a specific piece of code for each considered Web API to align TAXREF representation with the Web API counterpart. This task is time-consuming and makes maintenance of the web application cumbersome.
In this presentation, we report on a new implementation of TAXREF-Web that harnesses the Linked Data standards: Resource Description Framework (RDF), the Semantic Web format to represent knowledge graphs, and SPARQL, the W3C standard to query RDF graphs. In addition, we leverage the
SPARQL Micro-Service
architecture (Michel et al. 2018)
,
a lightweight approach to query Web APIs using SPARQL. A SPARQL micro-service is a SPARQL endpoint that wraps a Web API service; it typically produces a small, resource-centric RDF graph by invoking the Web API and transforming the response into RDF triples.
We developed
SPARQL
micro-services to wrap the Web APIs of GBIF, World Register of Marine Species (WoRMS), FishBase, Index Fungorum, Pan-European Species directories Infrastructure (PESI), ZooBank, International Plant Names Index (IPNI), EoL, Tropicos and Sandre. These micro-services consistently translate Web APIs responses into RDF graphs utilizing mainly two well-adopted vocabularies: Schema.org (Guha et al. 2015) and Darwin Core (Baskauf et al. 2015). This approach brings about two major advantages. First, the large adoption of Schema.org and Darwin Core ensures that the services can be immediately understood and reused by a large audience within the biodiversity community. Second, wrapping all these Web APIs in SPARQL micro-services “suddenly” makes them technically and semantically interoperable, since they all represent resources (taxa, habitats, traits, etc.) in a common manner. Consequently, the integration task is simplified: confronting data from multiple sources essentially consists of writing the appropriate SPARQL queries, thus making easier web application development and maintenance. We present several concrete cases in which we use this approach to detect disagreements between TAXREF and the aforementioned data sources, with respect to taxonomic information (author, synonymy, vernacular names, classification, taxonomic rank), habitats, bibliographic references, species interactions and life traits.</description><identifier>ISSN: 2535-0897</identifier><identifier>EISSN: 2535-0897</identifier><identifier>DOI: 10.3897/biss.3.37421</identifier><language>eng</language><publisher>Sofia: Pensoft Publishers</publisher><subject>Application programming interface ; Biodiversity ; Biologists ; Biology ; Computer Science ; Fungi ; Graphs ; Information Retrieval ; Integration ; Life Sciences ; Linked Data ; New records ; Resource Description Framework-RDF ; Semantic web ; Semantics ; Species ; Synonymy ; Taxonomy ; Vernacular names ; Web</subject><ispartof>Biodiversity Information Science and Standards, 2019-06, Vol.3 (37421)</ispartof><rights>2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Attribution</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c1371-6fdf3563e51b5fe19078dd089c00d291acbf018183835a7758a98f601bb16553</cites><orcidid>0000-0001-9064-0463 ; 0000-0003-4868-2584 ; 0000-0001-7807-944X ; 0000-0001-5959-5561</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,310,315,782,786,887,27931,27932</link.rule.ids><backlink>$$Uhttps://hal.science/hal-02168164$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Michel, Franck</creatorcontrib><creatorcontrib>Faron-Zucker, Catherine</creatorcontrib><creatorcontrib>Tercerie, Sandrine</creatorcontrib><creatorcontrib>Ettorre, Antonia</creatorcontrib><creatorcontrib>Olivier, Gargominy</creatorcontrib><title>Assisting Biologists in Editing Taxonomic Information by Confronting Multiple Data Sources using Linked Data Standards</title><title>Biodiversity Information Science and Standards</title><description>During the last decade, Web APIs (Application Programming Interface) have gained significant traction to the extent that they have become a de-facto standard to enable HTTP-based, machine-processable data access. Despite this success, however, they still often fail in making data interoperable, insofar as they commonly rely on proprietary data models and vocabularies that lack formal semantic descriptions essential to ensure reliable data integration. In the biodiversity domain, multiple data aggregators, such as the Global Biodiversity Information Facility (GBIF) and the Encyclopedia of Life (EoL), maintain specialized Web APIs giving access to billions of records about taxonomies, occurrences, or life traits (Triebel et al. 2012). They publish data sets spanning complementary and often overlapping regions, epochs or domains, but may also report or rely on potentially conflicting perspectives, e.g. with respect to the circumscription of taxonomic concepts. It is therefore of utmost importance for biologists and collection curators to be able to confront the knowledge they have about taxa with related data coming from third-party data sources.
To tackle this issue, the French National Museum of Natural History (MNHN) has developed an application to edit TAXREF, the French taxonomic register for fauna, flora and fungus (Gargominy et al. 2018). TAXREF registers all species recorded in metropolitan France and overseas territories, accounting for 260,000+ biological taxa (200,000+ species) along with 570,000+ scientific names. The TAXREF-Web application compares data available in TAXREF with corresponding data from third-party data sources, points out disagreements and allows biologists to add, remove or amend TAXREF accordingly. This requires that TAXREF-Web developers write a specific piece of code for each considered Web API to align TAXREF representation with the Web API counterpart. This task is time-consuming and makes maintenance of the web application cumbersome.
In this presentation, we report on a new implementation of TAXREF-Web that harnesses the Linked Data standards: Resource Description Framework (RDF), the Semantic Web format to represent knowledge graphs, and SPARQL, the W3C standard to query RDF graphs. In addition, we leverage the
SPARQL Micro-Service
architecture (Michel et al. 2018)
,
a lightweight approach to query Web APIs using SPARQL. A SPARQL micro-service is a SPARQL endpoint that wraps a Web API service; it typically produces a small, resource-centric RDF graph by invoking the Web API and transforming the response into RDF triples.
We developed
SPARQL
micro-services to wrap the Web APIs of GBIF, World Register of Marine Species (WoRMS), FishBase, Index Fungorum, Pan-European Species directories Infrastructure (PESI), ZooBank, International Plant Names Index (IPNI), EoL, Tropicos and Sandre. These micro-services consistently translate Web APIs responses into RDF graphs utilizing mainly two well-adopted vocabularies: Schema.org (Guha et al. 2015) and Darwin Core (Baskauf et al. 2015). This approach brings about two major advantages. First, the large adoption of Schema.org and Darwin Core ensures that the services can be immediately understood and reused by a large audience within the biodiversity community. Second, wrapping all these Web APIs in SPARQL micro-services “suddenly” makes them technically and semantically interoperable, since they all represent resources (taxa, habitats, traits, etc.) in a common manner. Consequently, the integration task is simplified: confronting data from multiple sources essentially consists of writing the appropriate SPARQL queries, thus making easier web application development and maintenance. We present several concrete cases in which we use this approach to detect disagreements between TAXREF and the aforementioned data sources, with respect to taxonomic information (author, synonymy, vernacular names, classification, taxonomic rank), habitats, bibliographic references, species interactions and life traits.</description><subject>Application programming interface</subject><subject>Biodiversity</subject><subject>Biologists</subject><subject>Biology</subject><subject>Computer Science</subject><subject>Fungi</subject><subject>Graphs</subject><subject>Information Retrieval</subject><subject>Integration</subject><subject>Life Sciences</subject><subject>Linked Data</subject><subject>New records</subject><subject>Resource Description Framework-RDF</subject><subject>Semantic web</subject><subject>Semantics</subject><subject>Species</subject><subject>Synonymy</subject><subject>Taxonomy</subject><subject>Vernacular names</subject><subject>Web</subject><issn>2535-0897</issn><issn>2535-0897</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNpNkV1PwjAUhhujiQS58wc08crEYT_o1l0iopDMeCH3TbeuWBwtthuRf28HxHh1Pt4nJ-ecF4BbjMaU59ljaUIY0zHNJgRfgAFhlCUoCpf_8mswCmGDECI5ITzlA7CfhmBCa-waPhnXuHUsAjQWzpU5dlfyx1m3NRVcWu38VrbGWVge4MxZ7Z09Qm9d05pdU8Nn2Ur44Tpf1QF2odcKY79qdVZaaZX0KtyAKy2bUI_OcQhWL_PVbJEU76_L2bRIKkwznKRaacpSWjNcMl3jHGVcqXhJhZAiOZZVqRHmmFNOmcwyxmXOdYpwWeKUMToE96exn7IRO2-20h-Ek0YspoXoe4jglON0sseRvTuxO---uzq0YhPvsHE7EX9FaJ5RRiP1cKIq70Lwtf4bi5HofRC9D4KKow_0F_vQezg</recordid><startdate>20190626</startdate><enddate>20190626</enddate><creator>Michel, Franck</creator><creator>Faron-Zucker, Catherine</creator><creator>Tercerie, Sandrine</creator><creator>Ettorre, Antonia</creator><creator>Olivier, Gargominy</creator><general>Pensoft Publishers</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FH</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0001-9064-0463</orcidid><orcidid>https://orcid.org/0000-0003-4868-2584</orcidid><orcidid>https://orcid.org/0000-0001-7807-944X</orcidid><orcidid>https://orcid.org/0000-0001-5959-5561</orcidid></search><sort><creationdate>20190626</creationdate><title>Assisting Biologists in Editing Taxonomic Information by Confronting Multiple Data Sources using Linked Data Standards</title><author>Michel, Franck ; Faron-Zucker, Catherine ; Tercerie, Sandrine ; Ettorre, Antonia ; Olivier, Gargominy</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1371-6fdf3563e51b5fe19078dd089c00d291acbf018183835a7758a98f601bb16553</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Application programming interface</topic><topic>Biodiversity</topic><topic>Biologists</topic><topic>Biology</topic><topic>Computer Science</topic><topic>Fungi</topic><topic>Graphs</topic><topic>Information Retrieval</topic><topic>Integration</topic><topic>Life Sciences</topic><topic>Linked Data</topic><topic>New records</topic><topic>Resource Description Framework-RDF</topic><topic>Semantic web</topic><topic>Semantics</topic><topic>Species</topic><topic>Synonymy</topic><topic>Taxonomy</topic><topic>Vernacular names</topic><topic>Web</topic><toplevel>online_resources</toplevel><creatorcontrib>Michel, Franck</creatorcontrib><creatorcontrib>Faron-Zucker, Catherine</creatorcontrib><creatorcontrib>Tercerie, Sandrine</creatorcontrib><creatorcontrib>Ettorre, Antonia</creatorcontrib><creatorcontrib>Olivier, Gargominy</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection (ProQuest)</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Biological Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>Biodiversity Information Science and Standards</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Michel, Franck</au><au>Faron-Zucker, Catherine</au><au>Tercerie, Sandrine</au><au>Ettorre, Antonia</au><au>Olivier, Gargominy</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assisting Biologists in Editing Taxonomic Information by Confronting Multiple Data Sources using Linked Data Standards</atitle><jtitle>Biodiversity Information Science and Standards</jtitle><date>2019-06-26</date><risdate>2019</risdate><volume>3</volume><issue>37421</issue><issn>2535-0897</issn><eissn>2535-0897</eissn><abstract>During the last decade, Web APIs (Application Programming Interface) have gained significant traction to the extent that they have become a de-facto standard to enable HTTP-based, machine-processable data access. Despite this success, however, they still often fail in making data interoperable, insofar as they commonly rely on proprietary data models and vocabularies that lack formal semantic descriptions essential to ensure reliable data integration. In the biodiversity domain, multiple data aggregators, such as the Global Biodiversity Information Facility (GBIF) and the Encyclopedia of Life (EoL), maintain specialized Web APIs giving access to billions of records about taxonomies, occurrences, or life traits (Triebel et al. 2012). They publish data sets spanning complementary and often overlapping regions, epochs or domains, but may also report or rely on potentially conflicting perspectives, e.g. with respect to the circumscription of taxonomic concepts. It is therefore of utmost importance for biologists and collection curators to be able to confront the knowledge they have about taxa with related data coming from third-party data sources.
To tackle this issue, the French National Museum of Natural History (MNHN) has developed an application to edit TAXREF, the French taxonomic register for fauna, flora and fungus (Gargominy et al. 2018). TAXREF registers all species recorded in metropolitan France and overseas territories, accounting for 260,000+ biological taxa (200,000+ species) along with 570,000+ scientific names. The TAXREF-Web application compares data available in TAXREF with corresponding data from third-party data sources, points out disagreements and allows biologists to add, remove or amend TAXREF accordingly. This requires that TAXREF-Web developers write a specific piece of code for each considered Web API to align TAXREF representation with the Web API counterpart. This task is time-consuming and makes maintenance of the web application cumbersome.
In this presentation, we report on a new implementation of TAXREF-Web that harnesses the Linked Data standards: Resource Description Framework (RDF), the Semantic Web format to represent knowledge graphs, and SPARQL, the W3C standard to query RDF graphs. In addition, we leverage the
SPARQL Micro-Service
architecture (Michel et al. 2018)
,
a lightweight approach to query Web APIs using SPARQL. A SPARQL micro-service is a SPARQL endpoint that wraps a Web API service; it typically produces a small, resource-centric RDF graph by invoking the Web API and transforming the response into RDF triples.
We developed
SPARQL
micro-services to wrap the Web APIs of GBIF, World Register of Marine Species (WoRMS), FishBase, Index Fungorum, Pan-European Species directories Infrastructure (PESI), ZooBank, International Plant Names Index (IPNI), EoL, Tropicos and Sandre. These micro-services consistently translate Web APIs responses into RDF graphs utilizing mainly two well-adopted vocabularies: Schema.org (Guha et al. 2015) and Darwin Core (Baskauf et al. 2015). This approach brings about two major advantages. First, the large adoption of Schema.org and Darwin Core ensures that the services can be immediately understood and reused by a large audience within the biodiversity community. Second, wrapping all these Web APIs in SPARQL micro-services “suddenly” makes them technically and semantically interoperable, since they all represent resources (taxa, habitats, traits, etc.) in a common manner. Consequently, the integration task is simplified: confronting data from multiple sources essentially consists of writing the appropriate SPARQL queries, thus making easier web application development and maintenance. We present several concrete cases in which we use this approach to detect disagreements between TAXREF and the aforementioned data sources, with respect to taxonomic information (author, synonymy, vernacular names, classification, taxonomic rank), habitats, bibliographic references, species interactions and life traits.</abstract><cop>Sofia</cop><pub>Pensoft Publishers</pub><doi>10.3897/biss.3.37421</doi><orcidid>https://orcid.org/0000-0001-9064-0463</orcidid><orcidid>https://orcid.org/0000-0003-4868-2584</orcidid><orcidid>https://orcid.org/0000-0001-7807-944X</orcidid><orcidid>https://orcid.org/0000-0001-5959-5561</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Application programming interface Biodiversity Biologists Biology Computer Science Fungi Graphs Information Retrieval Integration Life Sciences Linked Data New records Resource Description Framework-RDF Semantic web Semantics Species Synonymy Taxonomy Vernacular names Web |
title | Assisting Biologists in Editing Taxonomic Information by Confronting Multiple Data Sources using Linked Data Standards |
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