A Study on Research Data Management Services of Research University Libraries in the U.S.

Abstract

This study examined the current practices of Research Data Management (RDM) services recently built and implemented at research university libraries in the U.S. by analyzing the components of the services and the contents presented in their web sites. The study then analyzed the content of web pages describing the services provided by 31 Research Universities/Very High research activity determined based on the Carnegie Classification. The analysis was based on 9 components of the services suggested by previous studies, including (1) DMP support; (2) File organization; (3) Data description; (4) Data storage; (5) Data sharing and access; (6) Data preservation; (7) Data citation; (8) Data management training; (9) Intellectual property of data. As a result, the vast majority of the universities offered the service of DMP support. More than half of the universities provided the services for describing and preserving data, as well as data management training. Specifically, RDM services focused on offering the guidance to disciplinary metadata and repositories of relevance, or training via individual consulting services. More research and discussion is necessary to better understand an intra-or inter-institutional collaboration for implementing the services and knowledge and competency of librarians in charge of the services.

User needs assessment for research data services in a research university

“…This was followed by documentation in field and lab notebooks and codebooks. Given the inconsistencies that arise when using these various techniques for documenting data, this is an area where libraries can draw upon their extensive expertise in metadata to offer assistance and training (Johnston et al, 2012; Kim, 2014; Yoon and Schultz, 2017). Johnson et al (2016) affirmed that lab books and notebooks are one of the most commonly used data types.…”

“…The challenge is educating researchers about the benefits of using metadata standards when non-standard documentation methods have long sufficed (Akers and Doty, 2013). Highlighting the importance of metadata for preservation and access functions, such as data archiving, sharing, and reuse is a good place to start (Kim, 2014). Providing an easy-to-use, self-generating metadata option when designing data management systems, such as data repositories, can also facilitate the adoption of metadata standards.…”