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A Framework for Quality Assessment of Semantic Annotations of Tabular Data

Avogadro, R., Cremaschi, M., Jimenez-Ruiz, E. ORCID: 0000-0002-9083-4599 and Rula, A. (2021). A Framework for Quality Assessment of Semantic Annotations of Tabular Data. Lecture Notes in Computer Science, 12922, doi: 10.1007/978-3-030-88361-4_31 ISSN 0302-9743


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.

Publication Type: Conference or Workshop Item (Paper)
Publisher Keywords: Data Quality; Semantic annotation; Tabular data; Semantic Table Interpretation
Subjects: P Language and Literature > P Philology. Linguistics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: School of Mathematics, Computer Science & Engineering > Computer Science
Date available in CRO: 27 Oct 2021 10:11
Date deposited: 27 October 2021
Date of acceptance: 24 June 2021
Date of first online publication: 30 September 2021
Text - Accepted Version
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