EFFKG: European Fishing Fleet Knowledge Graph

EFFKG: European Fishing Fleet Knowledge Graph The European Fishing Fleet Knowledge Graph (EFFKG) is a provenance-aware semantic dataset integrating heterogeneous maritime, fisheries, and administrative data originating from international standards, European registries, and national institutional sources within a unified Wikibase-based semantic framework. All integrated resources were obtained from publicly accessible repositories. The knowledge graph is additionally deployed as a public Wikibase instance and SPARQL endpoint: Wikibase instance: https://effkg.wikibase.cloud SPARQL endpoint: https://effkg.wikibase.cloud/query Dataset scope EFFKG integrates information related to: European fishing vessels, Maritime ports and infrastructure, Administrative and territorial entities, Fishing gear classifications, Vessel classifications, FAO fishing areas, Provenance and source-specific metadata. The dataset combines international standards, supranational registries, and national administrative datasets through a unified semantic model supporting entity reconciliation, provenance preservation, and cross-source integration. The current release focuses on the European fishing fleet and incorporates enriched national-level information from Spain. Included artefacts This release includes: RDF dumps of the knowledge graph. JSON exports of the Wikibase dataset. Shape Expressions (ShEx) describing the semantic structure. Validation outputs and quality-assessment artefacts. SPARQL query examples. The dataset is distributed through compressed archives intended for offline analysis, semantic-web integration, and reproducible research workflows. Source categories The integrated sources include: International standards and global datasets International Standard Statistical Classification of Fishery Vessels by Vessel Types (ISSCFV). International Standard Statistical Classification of Fishing Gear (ISSCFG). FAO Major Fishing Areas. World Port Index (WPI). European and supranational sources European Fleet Register. Official Journal of the European Union. European port infrastructure datasets. National institutional datasets Spanish General Register of the Fishing Fleet. Boletín Oficial del Estado (Spain). Instituto Geográfico Nacional (Spain). Integrated source formats include CSV, XLSX, XML, PDF, and RDF-derived resources. Dataset statistics (v1.0.0) Vessel entities: 188,170 Port entities: 1,997 Administrative units: 269 Category entities: 73 Total entities: 190,628 Total statements: 3,707,656 Provenance-linked statements: 3,707,230 Total provenance references: 4,033,845 Integrated data sources: 10 Validation summary Validation procedures were executed through automated SPARQL-based quality assessment queries over the complete knowledge graph. Validation included: Schema conformance validation. Referential integrity validation. Provenance coverage validation. Identifier consistency validation. Domain plausibility validation. Geospatial validation. The current release achieved: 99.989% provenance coverage. 0 broken entity references. 99.975% domain plausibility compliance. 100% valid geospatial coordinates for evaluated port entities. Reproducibility and reuse The RDF and JSON dumps contained in this release correspond to the data ingested into the public EFFKG Wikibase deployment (v1.0.0). The dataset is intended to support: Blue Economy research. Fisheries governance analysis. Maritime infrastructure studies. Semantic Web and Knowledge Graph research. Cross-source data integration experiments. Geospatial and provenance-aware analyses. The source code and ingestion pipeline are maintained separately through the EFFKG GitHub repository. Licensing Dataset license: Creative Commons Attribution 4.0 International (CC BY 4.0) Users remain responsible for complying with any licensing conditions associated with the original institutional data sources. Citation If you use EFFKG in academic work, please cite: Rodriguez-Martin et al.EFFKG: European Fishing Fleet Knowledge GraphZenodo, v1.0.0. Contact EFFKG was developed by the WESO Research Group.