{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T21:28:54Z","timestamp":1792704534911,"version":"4.5.0"},"reference-count":7,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2025,4,28]],"date-time":"2025-04-28T00:00:00Z","timestamp":1745798400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGMOD Rec."],"published-print":{"date-parts":[[2025,4,28]]},"abstract":"<jats:p>Open science and data exchange in general rely on standardized and interoperable file formats. Comma-separated value (CSV) files are probably the most versatile, simplest, and widely-used file format for tabular data. For example, the FAIR data principles of research data management promote findable, accessible, interoperable, and reusable data and metadata. In this context, CSV files ensure accessibility and interoperability because of its simple structure and textbased format, making them amenable for long-term storage. An analysis by the Google Dataset Search team found that https:\/\/schema.org\/ contained almost 30M datasets of which 37% are tables in CSV or XLS format [1].<\/jats:p>","DOI":"10.1145\/3733620.3733638","type":"journal-article","created":{"date-parts":[[2025,4,29]],"date-time":"2025-04-29T16:20:07Z","timestamp":1745943607000},"page":"89-89","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Technical Perspective: TASHEEH: Repairing Row-Structure in Raw CSV Files"],"prefix":"10.1145","volume":"54","author":[{"given":"Matthias","family":"Boehm","sequence":"first","affiliation":[{"name":"Technische Universit\u00e4t Berlin"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,4,29]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-62466-8_41"},{"key":"e_1_2_1_2_1","volume-title":"EDBT","author":"Hameed M.","year":"2022","unstructured":"M. Hameed, G. Vitagliano, L. Jiang, and F. Naumann.SURAGH: syntactic pattern matching to identify ill-formed records. In EDBT, 2022."},{"key":"e_1_2_1_3_1","volume-title":"EDBT","author":"Hameed M.","year":"2024","unstructured":"M. Hameed, G. Vitagliano, F. Panse, and F. Naumann. TASHEEH: repairing row-structure in raw CSV files. In EDBT, 2024."},{"key":"e_1_2_1_4_1","volume-title":"SIGKDD","author":"Hulsebos M.","year":"2019","unstructured":"M. Hulsebos et al. Sherlock: A deep learning approach to semantic data type detection. In SIGKDD, 2019."},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2213836.2213860"},{"key":"e_1_2_1_6_1","first-page":"4180","author":"Shafranovich Y.","year":"2005","unstructured":"Y. Shafranovich. Common format and mime type for comma-separated values (csv) files. RFC 4180, 2005.","journal-title":"RFC"},{"key":"e_1_2_1_7_1","volume-title":"Wrangling messy CSV files by detecting row and type patterns. Data Min. Knowl. Discov., 33(6)","author":"van den Burg G. J. J.","year":"2019","unstructured":"G. J. J. van den Burg, A. Naz\u00b4abal, and C. Sutton. Wrangling messy CSV files by detecting row and type patterns. Data Min. Knowl. Discov., 33(6), 2019."}],"container-title":["ACM SIGMOD Record"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3733620.3733638","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3733620.3733638","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:56:55Z","timestamp":1750298215000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3733620.3733638"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,28]]},"references-count":7,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,4,28]]}},"alternative-id":["10.1145\/3733620.3733638"],"URL":"https:\/\/doi.org\/10.1145\/3733620.3733638","relation":{},"ISSN":["0163-5808"],"issn-type":[{"value":"0163-5808","type":"print"}],"subject":[],"published":{"date-parts":[[2025,4,28]]},"assertion":[{"value":"2025-04-29","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}