{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T10:21:53Z","timestamp":1777890113998,"version":"3.51.4"},"reference-count":22,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2022,8,25]],"date-time":"2022-08-25T00:00:00Z","timestamp":1661385600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["SW"],"published-print":{"date-parts":[[2022,8,25]]},"abstract":"<jats:p>Semantic annotation of tabular data is the process of matching table elements with knowledge graphs. As a result, the table contents could be interpreted or inferred using knowledge graph concepts, enabling them to be useful in downstream applications such as data analytics and management. Nevertheless, semantic annotation tasks are challenging due to insufficient tabular data descriptions, heterogeneous schema, and vocabulary issues. This paper presents an automatic semantic annotation system for tabular data, called MTab4D, to generate annotations with DBpedia in three annotation tasks: 1) matching table cells to entities, 2) matching columns to entity types, and 3) matching pairs of columns to properties. In particular, we propose an annotation pipeline that combines multiple matching signals from different table elements to address schema heterogeneity, data ambiguity, and noisiness. Additionally, this paper provides insightful analysis and extra resources on benchmarking semantic annotation with knowledge graphs. Experimental results on the original and adapted datasets of the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching (SemTab 2019) show that our system achieves an impressive performance for the three annotation tasks. MTab4D\u2019s repository is publicly available at https:\/\/github.com\/phucty\/mtab4dbpedia.<\/jats:p>","DOI":"10.3233\/sw-223098","type":"journal-article","created":{"date-parts":[[2022,8,26]],"date-time":"2022-08-26T11:16:33Z","timestamp":1661512593000},"page":"1-25","source":"Crossref","is-referenced-by-count":6,"title":["MTab4D: Semantic annotation of tabular data with DBpedia"],"prefix":"10.1177","author":[{"given":"Phuc","family":"Nguyen","sequence":"first","affiliation":[{"name":"National Institute of Informatics, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Natthawut","family":"Kertkeidkachorn","sequence":"additional","affiliation":[{"name":"Japan Advanced Institute of Science and Technology, Ishikawa, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ryutaro","family":"Ichise","sequence":"additional","affiliation":[{"name":"National Institute of Informatics, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hideaki","family":"Takeda","sequence":"additional","affiliation":[{"name":"National Institute of Informatics, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"key":"10.3233\/SW-223098_ref1","unstructured":"Y.\u00a0Chabot, T.\u00a0Labb\u00e9, J.\u00a0Liu and R.\u00a0Troncy, DAGOBAH: An end-to-end context-free tabular data semantic annotation system, in: SemTab@ISWC 2019, CEUR Workshop Proceedings, Vol.\u00a02553, CEUR-WS.org, 2019, pp.\u00a041\u201348, http:\/\/ceur-ws.org\/Vol-2553\/paper6.pdf."},{"key":"10.3233\/SW-223098_ref2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.330129"},{"key":"10.3233\/SW-223098_ref3","unstructured":"M.\u00a0Cremaschi, R.\u00a0Avogadro and D.\u00a0Chieregato, MantisTable: An automatic approach for the semantic table interpretation, in: SemTab@ISWC 2019, CEUR Workshop Proceedings, Vol.\u00a02553, CEUR-WS.org, 2019, pp.\u00a015\u201324, http:\/\/ceur-ws.org\/Vol-2553\/paper3.pdf."},{"key":"10.3233\/SW-223098_ref4","doi-asserted-by":"publisher","first-page":"478","DOI":"10.1016\/j.future.2020.05.019","article-title":"A fully automated approach to a complete semantic table interpretation","volume":"112","author":"Cremaschi","year":"2020","journal-title":"Future Generation Computer Systems"},{"key":"10.3233\/SW-223098_ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-68288-4_16"},{"key":"10.3233\/SW-223098_ref7","doi-asserted-by":"publisher","DOI":"10.5281\/zenodo.3518539"},{"key":"10.3233\/SW-223098_ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-49461-2_30"},{"issue":"11","key":"10.3233\/SW-223098_ref10","doi-asserted-by":"publisher","first-page":"1502","DOI":"10.14778\/3137628.3137657","article-title":"Stitching web tables for improving matching quality","volume":"10","author":"Lehmberg","year":"2017","journal-title":"Proc. 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