{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T23:31:28Z","timestamp":1773099088065,"version":"3.50.1"},"reference-count":11,"publisher":"Association for Computing Machinery (ACM)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2022,8]]},"abstract":"<jats:p>\n            In data science problems, understanding the data is a crucial first step. However, it can be challenging and time intensive for a data scientist who is not an expert in that domain. Several downstream tasks such as feature engineering and data curation depend on the understanding of data semantics. In this demonstration, we present,\n            <jats:italic>ADE (Automated Data Explanation)<\/jats:italic>\n            , a novel system that uses\n            <jats:italic>maximum likelihood estimation approach<\/jats:italic>\n            through ensembles for automatically labeling and explaining relational data by taking advantage of openly available semantic knowledge bases, webtables and Wikipedia. It helps a user to understand concepts of various columns and their relationships, an abstract summary about the overall data, and additional context not present in the data. It reduces the need for cumbersome search queries or expert consultation and can also receive inputs or corrections from a user, making it a mixed-initiative automation system.\n          <\/jats:p>","DOI":"10.14778\/3554821.3554844","type":"journal-article","created":{"date-parts":[[2022,9,29]],"date-time":"2022-09-29T22:28:39Z","timestamp":1664490519000},"page":"3562-3565","source":"Crossref","is-referenced-by-count":6,"title":["Automated relational data explanation using external semantic knowledge"],"prefix":"10.14778","volume":"15","author":[{"given":"Sainyam","family":"Galhotra","sequence":"first","affiliation":[{"name":"The University of Chicago"}]},{"given":"Udayan","family":"Khurana","sequence":"additional","affiliation":[{"name":"IBM Research AI"}]}],"member":"320","published-online":{"date-parts":[[2022,9,29]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.14778\/3297753.3297761"},{"key":"e_1_2_1_2_1","volume-title":"Colnet: Embedding the semantics of web tables for column type prediction. In AAAI.","author":"Chen J","year":"2019","unstructured":"J Chen , E Jim\u00e9nez-Ruiz , I Horrocks , and C Sutton . 2019 . Colnet: Embedding the semantics of web tables for column type prediction. In AAAI. J Chen, E Jim\u00e9nez-Ruiz, I Horrocks, and C Sutton. 2019. Colnet: Embedding the semantics of web tables for column type prediction. In AAAI."},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/CEC.2019.8789937"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2019.00161"},{"key":"e_1_2_1_5_1","unstructured":"Kevin Hu Neil Gaikwad Michiel Bakker Madelon Hulsebos Emanuel Zgraggen C\u00e9sar Hidalgo Tim Kraska Guoliang Li Arvind Satyanarayan and \u00c7a\u011fatay Demiralp. 2019. VizNet: Towards a large-scale visualization learning and benchmarking repository. In CHI. ACM.  Kevin Hu Neil Gaikwad Michiel Bakker Madelon Hulsebos Emanuel Zgraggen C\u00e9sar Hidalgo Tim Kraska Guoliang Li Arvind Satyanarayan and \u00c7a\u011fatay Demiralp. 2019. VizNet: Towards a large-scale visualization learning and benchmarking repository. In CHI. ACM."},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330993"},{"key":"e_1_2_1_7_1","volume-title":"Proceedings of the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching. CEUR Workshop Proceedings","volume":"3103","author":"Jim\u00e9nez-Ruiz Ernesto","year":"2022","unstructured":"Ernesto Jim\u00e9nez-Ruiz , Vasilis Efthymiou , Jiaoyan Chen , Vincenzo Cutrona , Oktie Hassanzadeh , Juan Sequeda , Kavitha Srinivas , Nora Abdelmageed , Madelon Hulsebos , Daniela Oliveira , and Catia Pesquita ( Eds .). 2022 . Proceedings of the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching. CEUR Workshop Proceedings , Vol. 3103 . CEUR-WS.org. Ernesto Jim\u00e9nez-Ruiz, Vasilis Efthymiou, Jiaoyan Chen, Vincenzo Cutrona, Oktie Hassanzadeh, Juan Sequeda, Kavitha Srinivas, Nora Abdelmageed, Madelon Hulsebos, Daniela Oliveira, and Catia Pesquita (Eds.). 2022. Proceedings of the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching. CEUR Workshop Proceedings, Vol. 3103. CEUR-WS.org."},{"key":"e_1_2_1_8_1","volume-title":"Proceedings of the 29th ACM International Conference on Information and Knowledge Management","author":"Khurana Udayan","year":"2021","unstructured":"Udayan Khurana and Sainyam Galhotra . 2021 . Semantic Annotation for Tabular Data . Proceedings of the 29th ACM International Conference on Information and Knowledge Management (2021). Udayan Khurana and Sainyam Galhotra. 2021. Semantic Annotation for Tabular Data. Proceedings of the 29th ACM International Conference on Information and Knowledge Management (2021)."},{"key":"e_1_2_1_9_1","doi-asserted-by":"crossref","unstructured":"S Neumaier J Umbrich JX Parreira and A Polleres. 2016. Multi-level semantic labelling of numerical values. In ICWS.  S Neumaier J Umbrich JX Parreira and A Polleres. 2016. Multi-level semantic labelling of numerical values. In ICWS.","DOI":"10.1007\/978-3-319-46523-4_26"},{"key":"e_1_2_1_10_1","unstructured":"P Nguyen and H Takeda. 2018. Semantic labeling for quantitative data using Wikidata. (2018).  P Nguyen and H Takeda. 2018. Semantic labeling for quantitative data using Wikidata. (2018)."},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i11.21735"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/3554821.3554844","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T11:29:46Z","timestamp":1672226986000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/3554821.3554844"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8]]},"references-count":11,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2022,8]]}},"alternative-id":["10.14778\/3554821.3554844"],"URL":"https:\/\/doi.org\/10.14778\/3554821.3554844","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2022,8]]}}}