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Title:Curricula models and resources along the data continuum: Lessons learned in the development and delivery of research data management and data science education
Author(s):Bishop, Bradley; Allard, Suzie; Benedict, Karl; Greenberg, Jane; Hoebelheinrich, Nancy; Lin, Xia; Wilson, Bruce
Subject(s):Data management
Data science
Data curation
Data skills capacity building
Abstract:There continues to be a critical demand for data managers, data curators, and data scientists. This panel addresses the education that needs to be delivered to help students and practicing professionals fill these roles, explores the existing resources available to educators, and provides an interactive environment to discuss the issues. The Institute of Museum and Library Services recognized the need for LIS educators to create the conduit to advance the entire research enterprise by building capacity in data management and data science. They funded projects to develop curricular models and related materials to educate the next generation of information professionals including: LIS Education and Data Science for the National Digital Platform (1); Development of an Enhanced and Expanded Data Management Training Clearinghouse for Earth Science Information Partners (ESIP) (2); User Experience and Assessment (3), Data Curation Education in Research Centers (4), and Geographic Information Librarianship (5). Attendees will learn about existing training materials and will be encouraged to brainstorm how to infuse and integrate research data management and data science into existing LIS programs and courses. A group discussion will consider the following questions: What research data management and data science education exists in other programs? How do we get LIS students more engaged in these data careers? Do other materials exist that could be included in the ESIP Clearinghouse? What can be learned from the ESIP example? (1)RE-70-17-0094-17; (2) LG-70-18-0092-18; (3) RE-20-16-0036-16; (4) RE-02-10-0004-10; (5) RE-05-12-0052-12
Issue Date:2019-09-24
Series/Report:Data management
Data science
Data curation
Genre:Conference Paper / Presentation
Date Available in IDEALS:2019-08-23

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