EDITOR'S SUMMARY
Prompted by federal requirements, academic institutions and librarians have become more involved in data management planning. An e‐research implementation group was formed at the University of Illinois to develop and promote data initiatives in a variety of ways, including updating a data management website to provide education and awareness to students and faculty. Part of the site focuses on documentation and metadata, describing traditional and nontraditional data types and sources, including lab notebooks, data files and database contents, workflow and operating procedures. The site details the importance of data documentation for the immediate research project and for the institution, explains metadata and provides links to metadata standards and resources.
Objectives: The objective of this study is to identify: (1) how many datasets are within Illinois Digital Environment for Access to Learning and Scholarship (IDEALS); (2) which types of files are deposited in the repository; (3) which research methodologies are associated with these datasets; and (4) which research discipline or research communities are associated with these datasets within IDEALS. Methods: Datasets collected in this study were found using the University of Illinois repository IDEALS website link https://www.ideals.illinois.edu. The keywords used were data or dataset. In order to facilitate analysis, datasets were analyzed using MS-Excel spreadsheets. They were coded by title, issue date, research methodology, research discipline, and community to explore patterns of use and the relationship to data management and research data services. Results: There are 507 datasets in IDEALS dating from 1905-2015. Text files are the most frequently deposited file type; bibliographies represent 34% of the datasets; and, farming inventory lists are 26% of the datasets. Various research disciplines represent 18% of the datasets and research communities are associated with 78% of the datasets. 7% of the datasets are sponsored by NSF, NIH, IMLS and DOE funding agencies. Conclusion: Understanding the file types, research methodologies, research disciplines and research communities within a university's current infrastructure, will provide a representation of the datasets and research supported within the university repository. It will enhance academic librarians and repository managers' data management conversations with researchers and provide information needed to needed to improve workflow deposit and batch loading. It will enhance research data services, meet researcher's needs, assess short-term preservation, and determine long-term preservation needs.
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