{"id":33,"date":"2023-10-17T11:24:30","date_gmt":"2023-10-17T11:24:30","guid":{"rendered":"http:\/\/vargas-solar.com\/data-curation-tutorial\/?page_id=33"},"modified":"2023-11-23T23:49:08","modified_gmt":"2023-11-23T23:49:08","slug":"bibliography","status":"publish","type":"page","link":"http:\/\/vargas-solar.com\/data-curation-tutorial\/bibliography\/","title":{"rendered":"Bibliography"},"content":{"rendered":"\n<ul class=\"wp-block-list\"><li>[CCT09] James Cheney, Laura Chiticariu, and Wang Chiew Tan. Provenance in databases: Why, how, and where. Found. Trends Databases, 1(4):379\u2013474, 2009.<\/li><li>[GGSS21] Stefan Grafberger, Shubha Guha, Julia Stoyanovich, and Sebastian Schelter. MLINSPECT: A data distribution debugger for machine learning pipelines. In Guoliang Li, Zhanhuai Li, Stratos Idreos, and Divesh Srivastava, editors, SIGMOD \u201921: International Conference on Management of Data, Virtual Event, China, June 20-25, 2021, pages 2736\u20132739. ACM, 2021<\/li><li>[LFS+23] Raoni Louren \u0327co, Juliana Freire, Eric Simon, Gabriel Weber, and Dennis E. Shasha. Bugdoc. VLDB J., 32(1):75\u2013101, 2023.<\/li><li>[ZAI19] Nan Zheng, Abdussalam Alawini, and Zachary G. Ives. Fine-grained provenance for matching &amp; ETL. In 35th IEEE International Conference on Data Engineering, ICDE 2019, Macao, China, April 8-11, 2019, pages 184\u2013195. IEEE, 20<\/li><\/ul>\n\n\n\n<pre class=\"wp-block-preformatted\">Keep in mind that for performing data analytics you are willing to make sense of data and this implies acquiring Data Literacy. Have a look at this reference for background.&nbsp;<\/pre>\n\n\n\n<p><strong>Michel Bowen, Anthony Bartley, <a href=\"https:\/\/drive.google.com\/file\/d\/117xsuTUIOtad5M6KQ66cUiUBPQ5BFJAq\/view?usp=sharing\">The Basics of Data Literacy: making your students (and you!) make sens of data<\/a>, NST Press, Arlington Virginia<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>[CCT09] James Cheney, Laura Chiticariu, and Wang Chiew Tan. Provenance in databases: Why, how, and where. Found. Trends Databases, 1(4):379&ndash;474, 2009. [GGSS21] Stefan Grafberger, Shubha Guha, Julia Stoyanovich, and Sebastian Schelter. MLINSPECT: A data distribution debugger for machine learning pipelines. In Guoliang Li, Zhanhuai Li, Stratos Idreos, and Divesh Srivastava, editors, SIGMOD &rsquo;21: International Conference [&hellip;]<\/p>\n","protected":false},"author":11,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"page-templates\/full-width.php","meta":{"footnotes":""},"class_list":["post-33","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"http:\/\/vargas-solar.com\/data-curation-tutorial\/wp-json\/wp\/v2\/pages\/33","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/vargas-solar.com\/data-curation-tutorial\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"http:\/\/vargas-solar.com\/data-curation-tutorial\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"http:\/\/vargas-solar.com\/data-curation-tutorial\/wp-json\/wp\/v2\/users\/11"}],"replies":[{"embeddable":true,"href":"http:\/\/vargas-solar.com\/data-curation-tutorial\/wp-json\/wp\/v2\/comments?post=33"}],"version-history":[{"count":3,"href":"http:\/\/vargas-solar.com\/data-curation-tutorial\/wp-json\/wp\/v2\/pages\/33\/revisions"}],"predecessor-version":[{"id":99,"href":"http:\/\/vargas-solar.com\/data-curation-tutorial\/wp-json\/wp\/v2\/pages\/33\/revisions\/99"}],"wp:attachment":[{"href":"http:\/\/vargas-solar.com\/data-curation-tutorial\/wp-json\/wp\/v2\/media?parent=33"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}