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Integrating Data Management Support Across Disciplines at MIT: Strategies and Initiatives

This presentation from the IASSIST Annual Conference 2010 outlines the MIT Libraries' efforts to enhance data management services across various disciplines. It discusses five divisional libraries' roles, formal data services, and outreach initiatives to engage faculty as data producers. Emphasizing collaborative partnerships, the session covers the development of interdisciplinary guidelines and support structures for data documentation, archiving, and dissemination. Key strategies for effective communication and coordination among library staff are also highlighted, aiming to strengthen data management practices university-wide.

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Integrating Data Management Support Across Disciplines at MIT: Strategies and Initiatives

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Presentation Transcript

  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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