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Supporting Data Management Across Disciplines

Supporting Data Management Across Disciplines. Katherine McNeill Massachusetts Institute of Technology IASSIST Annual Conference 2010. MIT Libraries Overview. Public Services Five divisional libraries: Architecture and urban planning Humanities Engineering Science

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Supporting Data Management Across Disciplines

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  1. Supporting Data Management Across Disciplines Katherine McNeill Massachusetts Institute of Technology IASSIST Annual Conference 2010

  2. MIT Libraries Overview • Public Services • Five divisional libraries: • Architecture and urban planning • Humanities • Engineering • Science • Management and social sciences • Role of public service librarians

  3. Data Services/Initiatives • Formal data services with dedicated staff: • Social Science Data Services • GIS Services • Interest groups on data: • Engineering and Science Data Initiatives Group (ESL-DIG) • Data Group

  4. Developing aData Management Service • New initiatives to support MIT faculty as information producers, not just consumers • Faculty as data producers • Built a set of web pages on archiving and disseminating your data • Then…

  5. Doing Outreach • Identified potential faculty: • Web sites • News stories • Word of mouth • Requests • Initiated contact via: • Email • Spontaneous encounters

  6. Initial Meetings with Faculty/Staff • Preparation • Conversation topics • Story of their data (collection, methodology, file formats, storage, documentation, rights, etc.) • Potential for secondary analysis • Guidance on data management • Options for archiving/disseminating data • Description of my support and available services • Sometimes met with research staff See also: Conducting a Data Interview, Witt and Carlson, http://docs.lib.purdue.edu/lib_research/81/

  7. Support Provided • Facilitate deposit of data in an archive or repository • Results: 3 faculty members with data in an archive, 2 in process • Advised on data documentation • Referrals to other services/training • Other needs that arise: e.g., data conversion • Ongoing support

  8. Building anInterdisciplinary Partnership • Data Group: Forum to exchange information • Members of ESL-DIG interested in developing data management guidelines for faculty • Potential overlap=opportunity for collaboration • Web guide:http://libraries.mit.edu/data-management • Workshop: Managing Research Data 101

  9. Working Together • Similarity of issues across disciplines • Learning from each other • Mutual benefit • Joint professional presentations • But still informal collaboration

  10. Reorganization • No longer discipline-based library units, but rather functional groups (as of July 1st) • Specialized Content and Services: numeric data, bioinformatics, CAD, GIS, images, maps, music, science and engineering data, & video. • My focus: numeric data • Collective planning for data management

  11. Open Questions • How much will we integrate services in our new department? What makes sense? • What services should be structured around format vs. discipline? • What is the role of the librarian subject specialist regarding data management?

  12. Conclusion • Data management issues cross disciplines • Reach out to your colleagues in other disciplines • Seek out areas of overlap or similar work • Be mindful of differences • Establish informal connections where no formal organizational structure exists • Take initiative

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