Data Informaon Literacy: Mulple Paths to a Single Goal Jake Carlson, Purdue University; Jon Jeffryes, University of Minnesota; hp://datainfolit.org Brian Westra, University of Oregon; Sarah Wright, Cornell University

Objecve What skills will graduate students need to be successful in managing, working with and curang their research data? This poster reports on inial results from a two-year project funded by the Instute of Museum and Library Services (IMLS) that is centered on exploring this queson. Cornell University of University of Purdue Purdue University Minnesota Oregon University #1 University #2 Methods The project is comprised of five teams (each made up of a data services librarian, a subject or informaon literacy specialist and Discipline Electrical & a faculty researcher) from four instuons. Each team Natural Computer Ag & Bio conducted environment scans of the discipline and conducted interviews of their faculty partner and his graduate students. Resources Civil Engineering Ecology Engineering Engineering Using this knowledge each team developed an educaonal program tailored to their specific discipline and local pracces. Cultures of Document- Data Sharing Data Sharing Data Ownership Pracce aon &

Idenfied Protocols

Databases Long-term Organizaon Metadata Needs Findings Metadata Access Transfer of Metadata Note: Due to the small size and use of convenience sampling Closing Out a these findings cannot be generalized beyond this project. Responsibilty Grant

Response Readings & Embedded Workshops Mini-Course Online Course Seminar Librarianship Raised Faculty Awareness of Refine Exisng Engagement Completed DMP Awareness • All 12 competencies were seen as important by faculty and Tools, Resources, SOPs on Data Outcomes Improved Data Resources for graduate students. Applicaon of and Best Checklist for • Pracces Evaluang Lack of formal training in data management Best Pracces Pracces Enforcing SOPs • Lack of formal policies in the research team Student Work • Self-directed learning through trial and error • Focus on data mechanics and local, immediate needs over deeper concepts or applicaon outside of the lab. Data Informaon Literacy Model

Project Personnel: Jake Carlson (PI), Camille Andrews, Marianne Stowell Bracke, Image Credits: Photos: “School of Fish” by Tom Weilenmann: hp://www.flickr.com/photos/tom_weilenmann/51673288/; “Roosevelt Dam Bridge” by Al_HikesAZ: hp://www.flickr.com/photos/alanenglish/466658759/; “Sunshine Sparkling on the Prairie Grass” by Carol VanHook: /librariesrock/3613075606/; “Code Obfuscaon - Part 2: Obfuscang Data Structures” by Sonia Gupta: hp://palizine.plynt.com/issues/2005Sep/code-obfuscaon-connued/; “SEPACisco” from the Water Quality Field Staon: Michael Fosmire, Jon Jeffryes, Lisa Johnston, Megan Sapp Nelson, Dean Walton, hp://www.agry.purdue.edu/water/fieldstn/photogallery/SEPACisco.jpg. Graphics: “User Experience” stencils by Todd Zazelenchuk & Elizabeth Boling: hp://www.userfocus.co.uk/resources/omnigraffle.html Brian Westra, Sarah Wright.