Suchergebnisse

In 2010, ICPSR began a long process of recovering data from Gordon Streib's Cornell Study of Occupational Retirement (CSOR). Because the unique data fill a gap in our understanding of US retirement history, we determined that an extensive data recovery project was warranted. This paper describes the scope of the data collection and the steps in ICPSR's recovery process. Though the data recovery was ultimately successful, this paper documents the amount of time invested and costs associated with this kind of recovery work. It also highlights the value of these data for future research in understanding gender and retirement in a historic context. In addition to the resulting publicly available data arising from this project, extensive paper medical records are housed at ICPSR for on-site analysis or for a future digitization project. These data would provide unique health information on older women and men traced over a period of time in the 1950s and represents future work for ICPSR to undertake.

With a growing demand for data reuse and open data within the scientific ecosystem, protecting the confidentiality and privacy of survey data is increasingly important. It requires more than legal procedures and technological controls; it requires social and behavioral intervention. In this research note, we delineate the disclosure risks of various types of survey data (i.e., longitudinal data, social network data, sensitive information and biomarkers, and geographic data), the current motivation for data reuse and challenges to data protection. Despite rigorous efforts to protect data, there are still threats to mitigate the protection of confidentiality in microdata. Unintentional data breaches, protocol violations, and the misuse of data are observed even in well-established restricted data access systems, which indicates that the systems all may rely heavily on trust. Creating and maintaining that trust is critical to secure data access. We suggest four ways of building trust; User-Centered Design Practices; Promoting Trust for Protecting Confidential Data; General Training in Research Ethics; Specific Training in Data Security Protocols, with an example of a new project 'Researcher Passport' by the Inter-university Consortium for Political and Social Research. Continuous user-focused improvements in restricted data access systems are necessary so that we promote a culture of trust among the research and data user community, train both in the general topic of responsible research and in the specific requirements of these systems, and offer systematic and holistic solutions.

Sharing data produced through health research projects has been increasingly recognized as a way to advance science more rapidly by facilitating discovery and increasing rigor and reproducibility. Much of the data collected from human subjects includes sufficient sociodemographic detail and/or covers sensitive topics and thus requires restricted data management and sharing practices. Over the last two decades, scientific organizations, presidential memoranda, and other sources have all called for increasing opportunities to share data. Recognizing the value of shared data, the National Institutes of Health (NIH) has issued a new Data Management and Sharing (DMS) Policy (Office of the Director, 2020), effective January 25, 2023. Prior to this updated policy, in 2009, the National Institute on Drug Abuse (NIDA) recognized the value of sharing data and established an archive, the National Addiction and HIV Data Archive Program (NAHDAP). This program focused on sharing data that was often highly sensitive generated from social and behavioral addiction research, including quantitative and qualitative assessments as well as biomarker and imaging data. NAHDAP has developed practices and curation standards to ensure datasets are improved and usable and provides technical assistance for both data depositors and users. We share three key lessons learned working to disseminate sensitive data over the last 13 years, including (1) protecting the confidentiality of human subjects, (2) ensuring careful consideration of costs for archiving data requiring human subject protections are managed, and (3) providing support to facilitate the discovery and use of the data. While this article will not provide a comprehensive review of these areas, we will provide major insights from our experiences while developing this archive program.

Many restricted data managing organizations across the world have adapted the Five Safes framework (safe data, safe projects, safe people, safe setting, safe output) for their management of restricted and confidential data. While the Five Safes have been well integrated throughout the data life cycle, organizations observe several unintended challenges regarding data being FAIR (Findable, Accessible, Interoperable, Reusable). In the current study, we review the current practice on the restricted data management and discuss challenges and future directions, especially focusing on data use agreements, disclosure risks review, and training. In the future, restricted data managing organizations may need to proactively take into consideration reducing inequalities in access to scientific development, preventing unethical use of data in their management of restricted and confidential data, and managing various types of data.

Despite large public investments in facilitating the secondary use of data, there is little information about the specific factors that predict data's reuse. Using data download logs from the Inter-university Consortium for Political and Social Research (ICPSR), this study examines how data properties, curation decisions, and repository funding models relate to data reuse. We find that datasets deposited by institutions, subject to many curatorial tasks, and whose access and preservation is funded externally are used more often. Our findings confirm that investments in data collection, curation, and preservation are associated with more data reuse. ; National Science Foundation grant 1930645 (LH, AP, DA) Institute of Museum and Library Services grant LG-37-19-0134-19 (LH, DA) National Institute of Drug Abuse contract number N01DA-14-5576 (AP) ; http://deepblue.lib.umich.edu/bitstream/2027.42/168212/5/Hemphill et al Data downloads.pdf ; http://deepblue.lib.umich.edu/bitstream/2027.42/168212/6/Hemphill et al Data Downloads JASIST.pdf ; 4ae71d2a-01c0-4084-84c3-c32ce960e81c ; 5836d8a9-776f-4cd5-ba6e-a0cfd10d555d ; SELF

Data sharing is increasingly perceived to be beneficial to knowledge production, and is therefore increasingly required by federal funding agencies, private funders, and journals. As qualitative researchers are faced with new expectations to share their data, data repositories and academic libraries are working to address the specific challenges of qualitative research data. This article describes how data repositories and academic libraries can partner with researchers to support three challenges associated with qualitative data sharing: (1) obtaining informed consent from participants for data sharing and scholarly reuse, (2) ensuring that qualitative data are legally and ethically shared, and (3) sharing data that cannot be deidentified. This article also describes three continuing challenges of qualitative data sharing that data repositories and academic libraries cannot specifically address—research using qualitative big data, copyright concerns, and risk of decontextualization. While data repositories and academic libraries cannot provide easy solutions to these three continuing challenges, they can partner with researchers and connect them with other relevant specialists to examine these challenges. Ultimately, this article suggests that data repositories and academic libraries can help researchers address some of the challenges associated with ethical and lawful qualitative data sharing.

Im Gegensatz zu Europa werden sozialwissenschaftliche Primärdaten in den USA selten auf öffentlich zugängliche Weise archiviert - selbst wenn die Datenerhebung öffentlich finanziert wurde. Dies gefährdet die künftige Verfügbarkeit der Daten. Der Beitrag erläutert aktuelle Versuche und Maßnahmen, Archivierungsnormen für die USA zu entwickeln, die Erhaltung von Daten zu sichern sowie diese Daten auch in Zukunft öffentlich zugänglich zu machen. ; Social science data collected in the United States, both historically and at present, have often not been placed in any public archive - even when the data collection was supported by government grants. The availability of the data for future use is, therefore, in jeopardy. Enforcing archiving norms may be the only way to increase data preservation and availability in the future.

'Im Gegensatz zu Europa werden sozialwissenschaftliche Primärdaten in den USA selten auf öffentlich zugängliche Weise archiviert - selbst wenn die Datenerhebung öffentlich finanziert wurde. Dies gefährdet die künftige Verfügbarkeit der Daten. Der Beitrag erläutert aktuelle Versuche und Maßnahmen, Archivierungsnormen für die USA zu entwickeln, die Erhaltung von Daten zu sichern sowie diese Daten auch in Zukunft öffentlich zugänglich zu machen.' (Autorenreferat)

The focus on quantitative literacy has been increasingly outside the realm of mathematics. The social sciences are well suited to including quantitative elements throughout the curriculum but doing so can mean challenges in preparation and presentation of material for instructors and increased anxiety for students. This paper describes tools and resources available through the Inter-university Consortium for Political and Social Research (ICPSR) that will aid students and instructors engaging in quantitative literacy across the curriculum. The Online Learning Center is a source of empirical activities aimed at undergraduates in lower-division substantive courses and Exploring Data through Research Literature presents an alternative to traditional research methods assignments. Searching and browsing tools, archive structures, and extended online-analysis tools make it easier for students in upper-division undergraduate and graduate courses to engage in exercises that increase quantitative literacy, and paper competitions reward them for doing so.