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Article Dans Une Revue PeerJ Computer Science Année : 2020

ShExML: improving the usability of heterogeneous data mapping languages for first-time users

Résumé

Integration of heterogeneous data sources in a single representation is an active field with many different tools and techniques. In the case of text-based approaches—those that base the definition of the mappings and the integration on a DSL—there is a lack of usability studies. In this work we have conducted a usability experiment ($n$ = 17) on three different languages: ShExML (our own language), YARRRML and SPARQL-Generate. Results show that ShExML users tend to perform better than those of YARRRML and SPARQL-Generate. This study sheds light on usability aspects of these languages design and remarks some aspects of improvement.

Dates et versions

hal-03110745 , version 1 (14-01-2021)

Identifiants

Citer

Herminio García-González, Iovka Boneva, Sławek Staworko, José Emilio Labra-Gayo, Juan Manuel Cueva Lovelle. ShExML: improving the usability of heterogeneous data mapping languages for first-time users. PeerJ Computer Science, 2020, 6, pp.27. ⟨10.7717/peerj-cs.318⟩. ⟨hal-03110745⟩
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