An Exploratory Analysis of Social Science Graduate Education in Data Management and Data Sharing

Abstract

Effective data management and data sharing are crucial components of the research lifecycle, yet evidence suggests that many social science graduate programs are not providing training in these areas. The current exploratory study assesses how U.S. masters and doctoral programs in the social sciences include formal, nonformal, and informal training in data management and sharing. We conducted a survey of 150 graduate programs across six social science disciplines, and used a mix of closed and open-ended questions focused on the extent to which programs provide such training and exposure. Results from our survey suggested a deficit of formal training in both data management and data sharing, limited nonformal training, and cursory informal exposure to these topics. Utilizing the results of our survey, we conducted a syllabus analysis to further explore the formal and nonformal content of graduate programs beyond self-report. Our syllabus analysis drew from an expanded seven social science disciplines for a total of 140 programs. The syllabus analysis supported our prior findings that formal and nonformal inclusion of data management and data sharing training is not common practice. Overall, in both the survey and syllabi study we found a lack of both formal and nonformal training on data management and data sharing. Our findings have implications for data repository staff and data service professionals as they consider their methods for encouraging data sharing and prepare for the needs of data depositors. These results can also inform the development and structuring of graduate education in the social sciences, so that researchers are trained early in data management and sharing skills and are able to benefit from making their data available as early in their careers as possible.