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In the science realm, ML is being used for medical diagnosis, new materials development, smart agriculture, DNA classification, and many others. In this article, we describe the opportunities of using ML in the area of scientific workflow management. Scientific workflows are key to today\u2019s computational science, enabling the definition and execution of complex applications in heterogeneous and often distributed environments. We describe the challenges of composing and executing scientific workflows and identify opportunities for applying ML techniques to meet these challenges by enhancing the current workflow management system capabilities. We foresee that as the ML field progresses, the automation provided by workflow management systems will greatly increase and result in significant improvements in scientific productivity. <\/jats:p>","DOI":"10.1177\/1094342019852127","type":"journal-article","created":{"date-parts":[[2019,5,31]],"date-time":"2019-05-31T03:52:01Z","timestamp":1559274721000},"page":"1128-1139","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":28,"title":["The role of machine learning in scientific workflows"],"prefix":"10.1177","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5106-503X","authenticated-orcid":false,"given":"Ewa","family":"Deelman","sequence":"first","affiliation":[{"name":"University of Southern California Information Sciences Institute, Marina Del Rey, CA, USA"}]},{"given":"Anirban","family":"Mandal","sequence":"additional","affiliation":[{"name":"Renaissance Computing Institute, Chapel Hill, NC, USA"}]},{"given":"Ming","family":"Jiang","sequence":"additional","affiliation":[{"name":"Lawrence Livermore National Laboratory, Livermore, CA, USA"}]},{"given":"Rizos","family":"Sakellariou","sequence":"additional","affiliation":[{"name":"The University of Manchester, Manchester, UK"}]}],"member":"179","published-online":{"date-parts":[[2019,5,30]]},"reference":[{"key":"bibr1-1094342019852127","doi-asserted-by":"publisher","DOI":"10.1109\/SC.2008.5215726"},{"key":"bibr2-1094342019852127","doi-asserted-by":"publisher","DOI":"10.1145\/2443416.2443417"},{"key":"bibr3-1094342019852127","doi-asserted-by":"publisher","DOI":"10.1109\/SSDM.2004.1311241"},{"key":"bibr4-1094342019852127","first-page":"1","volume-title":"Proceeding of the 3rd RapidMiner community meeting and conference (RCOMM 2012)","author":"Amer M","year":"2012"},{"key":"bibr5-1094342019852127","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2014.09.014"},{"key":"bibr7-1094342019852127","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2011.62"},{"key":"bibr8-1094342019852127","unstructured":"Blythe J, Deelman E, Gil Y, et al. 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