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Publication Date

2-28-2017

Article Type

EScience in Action

Abstract

Objective: Many academic and research institutions are exploring opportunities to better support researchers in sharing their data. As partners in the Data Curation Network project, our six institutions developed a comparison of the current levels of support provided for researchers to meet their data sharing goals through library-based data repository and curation services.

Methods: Each institutional lead provided a written summary of their services based on a previously developed structure, followed by group discussion and refinement of descriptions. Service areas assessed include the repository services for data, technologies used, policies, and staffing in place.

Conclusions: Through this process we aim to better define the current levels of support offered by our institutions as a first step toward meeting our project's overarching goal to develop a shared staffing model for data curation across multiple institutions.

Keywords

digital repositories, research data management (RDM) services, institutional repositories, academic libraries, scholarly communications, data curation

Acknowledgments

The Data Curation Network is funded by the Alfred P. Sloan Foundation.

Corresponding Author

Lisa R. Johnston, University of Minnesota Twin Cities, 117 Pleasant St. Minneapolis, MN, 55455. ljohnsto@umn.edu

Rights and Permissions

Copyright © 2017 Johnston et al.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.

Figure 1_1102.png (573 kB)
Figure 1: Example dataset in DRUM (left, http://dx.doi.org/10.13020/D6PK5C) and in Cornell eCommons (right, http://hdl.handle.net/1813/43783) which both use the DSpace software.

Figure 2_1102.png (372 kB)
Figure 2: Example dataset in ScholarSphere (left, https://scholarsphere.psu.edu/files/m900nt50p) and Deep Blue Data (right, https://deepblue.lib.umich.edu/data/concern/generic_works/rf55z7781) both using Hydra (https://projecthydra.org) with Fedora (http://fedorarepository.org).

Figure 3_1102.png (244 kB)
Figure 3: Example dataset in the Illinois Data Bank (left, https://doi.org/10.13012/J8PN93H8) using a custom-build Ruby on Rails application and the Digital Research Materials Repository (right, https://doi.org/10.7936/K7J67F60) using Digital Commons by BePress.

Figure 4_1102.png (462 kB)
Figure 4: University of Minnesota Data Curation Workflow Diagram

Figure 5_1102.jpg (303 kB)
Figure 5: Cornell University Data Curation Workflow Diagram

Figure 6_1102.png (289 kB)
Figure 6: University of Illinois Data Curation Workflow Diagram

Figure 7_1102.png (55 kB)
Figure 7: Washington University in St. Louis Data Curation Workflow Diagram

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