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Cross-Querying LOD Datasets Using Complex Alignments: An Application to Agronomic Taxa

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Metadata and Semantic Research (MTSR 2017)

Abstract

Farmers have new information needs to change their agricultural practices. The Linked Open Data is a considerable source of knowledge, separated into several heterogeneous and complementary datasets. This paper presents a process to query LOD datasets from a known ontology using complex alignments. The approach was applied on AgronomicTaxon, a taxonomic classification ontology, to query Agrovoc and DBpedia.

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Notes

  1. 1.

    Ontologies are defined as semantic web data schema.

  2. 2.

    The W3C recommandationhttps://www.w3.org/TR/sparql11-query/ for a query and update language for the Semantic Web.

  3. 3.

    http://www.ncbi.nlm.nih.gov/taxonomy.

  4. 4.

    https://inpn.mnhn.fr/programme/referentiel-taxonomique-taxref.

  5. 5.

    http://eol.org/.

  6. 6.

    We will use the prefix agro for the reference of this ontology.

  7. 7.

    http://dbpedia.org/prefixes: dbo (\(\mathcal {T}box\)), dbr (\(\mathcal {A}box\)).

  8. 8.

    https://fr.wikipedia.org/.

  9. 9.

    http://aims.fao.org/aos/agrovoc/, prefixes: agronto (\(\mathcal {T}box\)), agrovoc (\(\mathcal {A}box\)).

  10. 10.

    http://www.w3.org/TR/skos-reference/skos-xl.html.

  11. 11.

    https://framagit.org/IRIT_UT2J/sparql-translator-complex-alignment.

  12. 12.

    http://alignapi.gforge.inria.fr/edoal.html.

  13. 13.

    https://framagit.org/IRIT_UT2J/sparql-translator-complex-alignment/tree/master/mtsr2017/.

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Acknowledgements

This work is partially supported by the French FUI SparkinData project.

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Correspondence to Elodie Thiéblin .

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Thiéblin, E., Amarger, F., Hernandez, N., Roussey, C., Trojahn Dos Santos, C. (2017). Cross-Querying LOD Datasets Using Complex Alignments: An Application to Agronomic Taxa. In: Garoufallou, E., Virkus, S., Siatri, R., Koutsomiha, D. (eds) Metadata and Semantic Research. MTSR 2017. Communications in Computer and Information Science, vol 755. Springer, Cham. https://doi.org/10.1007/978-3-319-70863-8_3

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  • DOI: https://doi.org/10.1007/978-3-319-70863-8_3

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