[IPH19] Revealing the Conceptual Schema of RDF Datasets

Conférence Internationale avec comité de lecture : 31st International Conference on Advanced Information Systems Engineering (CAiSE), June 2019, pp.1-15, Italy,
Résumé: RDF-based datasets, thanks to their semantic richness, variety and fine granularity, are increasingly used by both researchers and business communities. However, these datasets suffers from a lack of completeness as the content evolves continuously and data contributors are loosely constrained by the vocabularies and schemes related to the data sources. Conceptual models have long been recognized as a key mechanism for understanding and coping with complex real-world systems. In the context of the Web of Data and user-generated content, the conceptual model is implicit. In fact, each data contributor has an implicit personal model that is not known by the other contributors. Consequently, revealing a meaningful conceptual model is a challenging task that should take into account the data and the intended usage. In this paper, we propose a completeness-based approach for revealing conceptual schemas of RDF data. We combine quality evaluation and data mining approaches to find, for a dataset, a conceptual schema that meets user expectations regarding data completeness constraints. To achieve that, we propose LOD-CM; a web-based completeness demonstrator for linked datasets.


@inproceedings {
title="{Revealing the Conceptual Schema of RDF Datasets}",
author=" S. Issa and P. Paris and F. Hamdi and S. Si-Said Cherfi ",
booktitle="{31st International Conference on Advanced Information Systems Engineering (CAiSE)}",
address=" Italy",