Documentation evaluation model for social science data

Abstract

Information technology and data sharing policies have made more and more social science data available for secondary analysis. In secondary data analysis, documentation plays a critical role in transferring knowledge about data from data producers to secondary users. Despite its importance, documentation of social science data has rarely been the focus of existing studies. In this paper, based on an introduction of the concept of documentation and its role in secondary data analysis, the authors proposed the Documentation Evaluation Model(DEM) for social science data. In the model, two indicators are used to evaluate the documentation for social science data: sufficiency and ease-of-use. Then the authors review the sufficiency problems of documentation, identify three factors that affect the sufficiency of documentation: users, data, and the ease-of-use of documentation, and formulate hypotheses about how those factors affect the sufficiency of documentation. In future research, a survey instrument will be created based on the model and the factors affecting the sufficiency of documentation. The survey instrument will then be applied to the secondary users of social science data. Hypotheses will be tested based on the survey data.

Data reusers' trust development

“…Documentation was commonly discussed by all of the participants as a factor that enhanced (or diminished) trust. Although the importance of documentation in data reuse has been discussed by many researchers (e.g., Faniel & Jacobsen, ; Niu & Hedstrom, ), the participants said that good documentation can enhance the level of trust because they believed that documentation reflects the original study and investigators' characteristics: “You can tell from the documentation whether or not a research[er] was thorough and careful” (PS08). In addition, the participants acknowledged the efforts to prepare the documentation and said, “when [I] have stuff documented, that makes me feel more secure […] because it means […] you took the time [and] commit to it” (PS12).…”

Social scientists' data reuse behaviors: Exploring the roles of attitudinal beliefs, attitudes, norms, and data repositories

“…As Martin (1995) and Goodwin (2012) suggest, reused data might be perceived as less acceptable or less valuable in some social science disciplines. The possibility of misrepresentation arising from missing information or missing context was also a major concern, not only for data producers but also for data reusers, particularly qualitative researchers (Niu & Hedstrom, 2008;Yoon, 2014b). Perceived concern comprises potential risks involved in data reuse, and TAM was extended by later studies including a perceived risk construct (Featherman & Pavlou, 2003;Wu & Wang, 2005).…”

Social scientists' satisfaction with data reuse

“…Documentation quality refers to the degree to which written documentation about the data is suitable for use. Because research data are contextual by nature, reusers need to have details about data's context of production to decide whether the data are relevant, understandable, and trustworthy (e.g., Card et al., ; Carlson & Anderson, ; Faniel & Jacobsen, ; Niu, ). Based on three case studies in astronomy, social science, and anthropology, Carlson and Anderson () found “data were not self‐contained units that could easily be circulated, but always needed complementary external information to be understood or trusted” (p. 647).…”