Assessing the Academic Library's Role in Campus-Wide Research Data Management: A First Step at the University of Houston
| Title | Assessing the Academic Library's Role in Campus-Wide Research Data Management: A First Step at the University of Houston |
| Publication Type | Journal Article |
| Year of Publication | 2011 |
| Authors | Peters, C., & Dryden A. |
| Journal | Science & Technology Libraries |
| Volume | 30 |
| Issue | 4 |
| Pagination | 387 - 403 |
| Date Published | 2011/// |
| Keywords | sg_daf, sg_data_survey |
| Abstract | In an effort to support the University of Houston's goal of becoming a Carnegie-designated Tier One research university, several science librarians within the Department of Liaison Services have undertaken a study to assess current data management practices on campus. The goal of this study was to determine if data management needs are being met on campus and how the library might help meet those needs. We found that rather than physical storage capacity, researchers need assistance with funding agencies' data management requirements, the grant proposal process, finding campus data-related services, publication support, and targeted research assistance attendant to data management. |
| URL | http://dx.doi.org/10.1080/0194262X.2011.626340 |
Gap Area Study Type:
High-level Gap Areas:
Measurement Gap Areas:
- Context: Discipline/Department
- Context: Role (or business area)
- Culture: Sharing attitudes and practices
- Culture: Standards
- Knowledge: Amount of data
- Knowledge: Other: Funder requirements, experience with DMPs (researchers)
- Knowledge: Other: Data types and formats
- Resp: Conduct stewardship activities
- Collab: Other: Research collaboration
- HR: Lack of skills
- HR: Lack of support for data management
- IT: Lack of tools
- IT: Other: Lack of services
- CMP: Fragmented data management
- CMP: Insufficient data curation or management
- SA: Sharing and Access
Purpose:
Interviewed PIs of significant grants, to assess individuals in as many science and engineering departments as possible, and to obtain information on data management practices from both individual and group-based projects
Method:
Conducted interviews with PIs of 10 projects (14 contacted), as well as one Co-PI, one post-doctorate and one graduate student associated with one of the projects)
