{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:17:14Z","timestamp":1750220234928,"version":"3.41.0"},"reference-count":11,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2022,1,31]],"date-time":"2022-01-31T00:00:00Z","timestamp":1643587200000},"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":[[2022,1,31]]},"abstract":"<jats:p>ACM SIGMOD, VLDB and other database organizations have committed to fostering an inclusive and diverse community, as do many other scientific organizations. Recently, different measures have been taken to advance these goals, especially for underrepresented groups. One possible measure is double-blind reviewing, which aims to hide gender, ethnicity, and other properties of the authors.<\/jats:p>\n          <jats:p>We report the preliminary results of a gender diversity analysis of publications of the database community across several peer-reviewed venues, and also compare women's authorship percentages in both single-blind and double-blind venues along the years. We also obtained a cross comparison of the obtained results in data management with other relevant areas in Computer Science.<\/jats:p>","DOI":"10.1145\/3516431.3516438","type":"journal-article","created":{"date-parts":[[2022,1,31]],"date-time":"2022-01-31T23:31:58Z","timestamp":1643671918000},"page":"30-35","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["How Inclusive are We?"],"prefix":"10.1145","volume":"50","author":[{"given":"Angela","family":"Bonifati","sequence":"first","affiliation":[{"name":"Lyon 1 University &amp; Liris CNRS, France"}]},{"given":"Michael J.","family":"Mior","sequence":"additional","affiliation":[{"name":"Rochester Institute of Technology, Rochester , NY, USA"}]},{"given":"Felix","family":"Naumann","sequence":"additional","affiliation":[{"name":"Hasso Plattner Institute University of Potsdam, Germany"}]},{"given":"Nele","family":"Sina Noack","sequence":"additional","affiliation":[{"name":"University of Potsdam, Germany"}]}],"member":"320","published-online":{"date-parts":[[2022,1,31]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/1083784.1083791"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1177\/1075547012472684"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/1147376.1147381"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3417517"},{"key":"e_1_2_1_5_1","volume-title":"Comparison and benchmark of name-to-gender inference services. PeerJ Computer Science, page 4:e156","author":"Santamar\u00b4a Luc\u00b4a","year":"2018","unstructured":"Luc\u00b4a Santamar\u00b4a and Helena Mihaljevi\u00b4c . Comparison and benchmark of name-to-gender inference services. PeerJ Computer Science, page 4:e156 , 2018 . Luc\u00b4a Santamar\u00b4a and Helena Mihaljevi\u00b4c. Comparison and benchmark of name-to-gender inference services. PeerJ Computer Science, page 4:e156, 2018."},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/1168092.1168094"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1707323114"},{"key":"e_1_2_1_8_1","volume-title":"An open review of OpenReview: A critical analysis of the machine learning conference review process. CoRR, abs\/2010.05137","author":"Tran David","year":"2020","unstructured":"David Tran , Alex Valtchanov , Keshav Ganapathy , Raymond Feng , Eric Slud , Micah Goldblum , and Tom Goldstein . An open review of OpenReview: A critical analysis of the machine learning conference review process. CoRR, abs\/2010.05137 , 2020 . David Tran, Alex Valtchanov, Keshav Ganapathy, Raymond Feng, Eric Slud, Micah Goldblum, and Tom Goldstein. An open review of OpenReview: A critical analysis of the machine learning conference review process. CoRR, abs\/2010.05137, 2020."},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/1168092.1168093"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3430803"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2018.3971359"}],"container-title":["ACM SIGMOD Record"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3516431.3516438","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3516431.3516438","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:30:21Z","timestamp":1750188621000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3516431.3516438"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,31]]},"references-count":11,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2022,1,31]]}},"alternative-id":["10.1145\/3516431.3516438"],"URL":"https:\/\/doi.org\/10.1145\/3516431.3516438","relation":{},"ISSN":["0163-5808"],"issn-type":[{"type":"print","value":"0163-5808"}],"subject":[],"published":{"date-parts":[[2022,1,31]]},"assertion":[{"value":"2022-01-31","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}