Communication Dans Un Congrès Année : 2025

SDG-KG: A Framework to Compute SDG Indicators with Open Data

Résumé

Monitoring Sustainable Development Goal (SDG) indicators requires integrating heterogeneous open datasets from sources such as relational databases, NoSQL stores, and APIs. While SDG indicators follow standardized definitions, open data sources are often fragmented, schema-less, and inconsistent, making both integration and computation challenging. In this demonstration, we present SDG-KG , a spatio-temporal Knowledge Graph (KG) framework designed to structure metadata, guide data retrieval, and formalize indicator computation workflows. Our approach leverages graph-based modeling to construct a Metadata Graph, apply conflict resolution techniques when multiple sources provide overlapping data, and dynamically generate query-driven execution plans. Through an interactive interface, users can explore United Nations specifications, inspect data provenance and the generated KG, and visualize the computed indicators.

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hal-05264726 , version 1 (21-10-2025)

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Wissal Benjira, Nicolas Travers, Faten Atigui, Bénédicte Bucher, Malika Grim-Yefsah. SDG-KG: A Framework to Compute SDG Indicators with Open Data. Proceedings of the VLDB Endowment, Sep 2025, London, United Kingdom. pp.5367-5370, ⟨10.14778/3750601.3750673⟩. ⟨hal-05264726⟩
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