Much information is conveyed within tables, which can be semantically annotated by humans or (semi)automatic approaches. Nevertheless, many applications cannot take full advantage of semantic annotations because of the low quality. A few methodologies exist for the quality assessment of semantic annotation of tabular data, but they do not automatically assess the quality as a multidimensional concept through different quality dimensions. The quality dimensions are implemented in STILTool 2, a web application to automate the quality assessment of the annotations. The evaluation is carried out by comparing the quality of semantic annotations with gold standards. The work presented here has been applied to at least three use cases. The results show that our approach can give us hints about the quality issues and how to address them.
Avogadro, R., Cremaschi, M., Jimenez-Ruiz, E., Rula, A. (2021). A Framework for Quality Assessment of Semantic Annotations of Tabular Data. In The Semantic Web – ISWC 2021 - 20th International Semantic Web Conference, ISWC 2021, Virtual Event, October 24–28, 2021, Proceedings (pp.528-545). GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND : Springer, Cham [10.1007/978-3-030-88361-4_31].
A Framework for Quality Assessment of Semantic Annotations of Tabular Data
Avogadro R.;Cremaschi M.
;Rula A.
2021
Abstract
Much information is conveyed within tables, which can be semantically annotated by humans or (semi)automatic approaches. Nevertheless, many applications cannot take full advantage of semantic annotations because of the low quality. A few methodologies exist for the quality assessment of semantic annotation of tabular data, but they do not automatically assess the quality as a multidimensional concept through different quality dimensions. The quality dimensions are implemented in STILTool 2, a web application to automate the quality assessment of the annotations. The evaluation is carried out by comparing the quality of semantic annotations with gold standards. The work presented here has been applied to at least three use cases. The results show that our approach can give us hints about the quality issues and how to address them.
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