Abstract:

The study of scientific data practices provides an empirical foundation and humanistic considerations for developing effective data management, sharing, and discovery systems. Today, transformative and disruptive multidisciplinary and transdisciplinary research especially requires open and fluent data sharing, information exchange, and knowledge discovery mechanisms to address grand research challenges. To this end, it is important to investigate scientists’ scholarly communication dynamics and data information behaviors to drive humancentered design and development of data infrastructure and curation services. This paper describes three examples of empirical research on scholarly data practices and discusses their pragmatic implications for library services and infrastructure development. These examples employed a mixedmethods approach to explore domain and crossdomain scientists’ data management, sharing, discovery, use, reuse, and preservation practices. The research methods range from data landscape survey, interpersonal interviews, to focus group discussion. The results inform data repository optimization and promote open data movement through empirical evidence and practical strategies. By way of reviewing and reflecting on the study cases, this paper aims to project the future landscape of data practice research and emphasizes the significance of humanistic considerations in the design of data management systems.

Key words: Scientific data, Data practice, Data management, User information behaviors, Data repository systems; , Open data, Data reuse