Abstract Data quality issues can significantly hinder research reproducibility, data sharing, and reuse. At the forefront of addressing data quality issues are research data repositories (RDRs). This study conducted a systematic analysis of data quality assurance (DQA) practices in RDRs, guided by activity theory and data quality literature, resulting in conceptualizing a data quality assurance model (DQAM) for RDRs. DQAM outlines a DQA process comprising evaluation, intervention, and communication activities and categorizes 17 quality dimensions into intrinsic and product‐level data quality. It also details specific improvement actions for data products and identifies the essential roles, skills, standards, and tools for DQA in RDRs. By comparing DQAM with existing DQA models, the study highlights its potential to improve these models by adding a specific DQA activity structure. The theoretical implication of the study is a systematic conceptualization of DQA work in RDRs that is grounded in a comprehensive analysis of the literature and offers a refined conceptualization of DQA integration into broader frameworks of RDR evaluation. In practice, DQAM can inform the design and development of DQA workflows and tools. As a future research direction, the study suggests applying and evaluating DQAM across various domains to validate and refine this model further.

Abstract Research information management systems (RIMS) have become critical components of information technology infrastructure on university campuses. They are used not just for sharing and promoting faculty research, but also for conducting faculty evaluation and development, facilitating research collaborations, identifying mentors for student projects, and expert consultants for local businesses. This study is one of the first empirical investigations of the structure of researchers' scholarly profile maintenance activities in a nonmandatory institutional RIMS. By analyzing the RIMS's log data, we identified 11 tasks researchers performed when updating their profiles. These tasks were further grouped into three activities: (a) adding publication, (b) enhancing researcher identity, and (c) improving research discoverability. In addition, we found that junior researchers and female researchers were more engaged in maintaining their RIMS profiles than senior researchers and male researchers. The results provide insights for designing profile maintenance action templates for institutional RIMS that are tailored to researchers' characteristics and help enhance researchers' engagement in the curation of their research information. This also suggests that female and junior researchers can serve as early adopters of institutional RIMS.

Abstract Here, we report on a qualitative study that examined research information management (RIM) ecosystems on research university campuses from the perspectives of research information (RI) managers and librarians. In the study, we identified 21 RIM services offered to researchers, ranging from discovering, storing, and sharing authored content to identifying expertise, recruiting faculty, and ensuring the diversity of committee assignments. In addition, we identified 15 types of RIM service provision and adoption problems, analyzed their activity structures, and connected them to strategies for their resolution. Finally, we report on skills that the study participants reported as being needed in their work. These findings can inform the development of best practice guides for RIM on university campuses. The study also advances the state of the art of RIM research by applying the typology of contradictions from activity theory to categorize the problems of RIM service provision and connect their resolution to theories and findings of prior studies in the literature. In this way, the research expands the theoretical base used to study RIM in general and RIM at research universities in particular.

This study examined how researchers used research information systems (RIMSs) and the relationships among researchers' seniority, discipline, and types and extent of RIMS use. Most researchers used RIMSs to discover research content. Fewer used RIMSs for sharing and promoting their research. Early career researchers were more frequent users of RIMSs than were associate and full professors. Likewise, assistant professors and postdocs exhibited a higher probability of using RIMSs to promote their research than did students and full professors. Humanities researchers were the least frequent users of RIMSs. Moreover, humanities scholars used RIMSs to evaluate research less than did scholars in other disciplines. The tasks of discovering papers, monitoring the literature, identifying potential collaborators, and promoting research were predictors of higher RIMS use. Researchers who engaged in promoting their research, evaluating research, or monitoring the literature showed a greater propensity to have a public RIMS profile. Furthermore, researchers mostly agreed that not being required, having no effect on their status, not being useful, or not being a norm were reasons for not having a public RIMS profile. Humanities scholars were also more likely than social scientists to agree that having a RIMS profile was not a norm in their fields.

To be effective and at the same time sustainable, a community data curation model needs to be aligned with the community's current data practices, including research project activities, data types, and perceptions of data quality. Based on a survey of members of the condensed matter physics (CMP) community gathered around the National High Magnetic Field Laboratory, a large national laboratory, this article defines a model of CMP research project tasks consisting of 10 task constructs. In addition, the study develops a model of data quality perceptions by CMP scientists consisting of four data quality constructs. The paper also discusses relationships among the data quality perceptions, project roles, and demographic characteristics of CMP scientists. The findings of the study can inform the design of a CMP data curation model that is aligned and harmonized with the community's research work structure and data practices.