Browsing by Subject "Data reuse"

Now showing 1 - 8 of 8
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    Building the Future of Research Together: Collaborating with a Clinical and Translational Science Award (CTSA)-Funded Translational Science Institute to Provide Data Management Training
    (2014-05-19) Coates, Heather L.
    Objectives: To explore potential collaborations between academic libraries and Clinical Translational Science Award (CTSA) - funded institutes with respect to data management training and support. Methods: The National Institutes of Health CTSAs have established a well-funded, crucial infrastructure supporting large-scale collaborative biomedical research. This infrastructure is also valuable for smaller, more localized research projects. While infrastructure and corresponding support is often available for large, well-funded projects, these services have generally not been extended to smaller projects. This is a missed opportunity on both accounts. Academic libraries providing data services can leverage CTSA-based resources, while CTSA-funded institutes can extend their reach beyond large biomedical projects to serve the long tail of research data. Results: A year-long series of conversations with the Indiana CTSI Data Management Team resulted in resource sharing, consensus building about key issues in data management, provision of expert feedback on a data management training curriculum, and several avenues for future collaborations. Conclusions: Data management training for graduate students and early career researchers is a vital area of need that would benefit from the combined infrastructure and expertise of translational science institutes and academic libraries. Such partnerships can leverage the instructional, preservation, and access expertise in academic libraries, along with the storage, security, and analytical expertise in translational science institutes to improve the management, protection, and access of valuable research data.
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    Data matters: how earth and environmental scientists determine data relevance and reusability
    (2019-05-01) Murillo, Angela
    Abstract Purpose – The purpose of this study is to examine the information needs of earth and environmental scientists regarding how they determine data reusability and relevance. Additionally, this study provides strategies for the development of data collections and recommendations for data management and curation for information professionals working alongside researchers. Design/methodology/approach – This study uses a multi-phase mixed-method approach. The test environment is the DataONE data repository. Phase 1 includes a qualitative and quantitative content analysis of deposited data. Phase 2 consists of a quasi-experiment think-aloud study. This paper reports mainly on Phase 2. Findings – This study identifies earth and environmental scientists’ information needs to determine data reusability. The findings include a need for information regarding research methods, instruments and data descriptions when determining data reusability, as well as a restructuring of data abstracts. Additional findings include reorganizing of the data record layout and data citation information. Research limitations/implications – While this study was limited to earth and environmental science data, the findings provide feedback for scientists in other disciplines, as earth and environmental science is a highly interdisciplinary scientific domain that pulls from many disciplines, including biology, ecology and geology, and additionally there has been a significant increase in interdisciplinary research in many scientific fields. Practical implications – The practical implications include concrete feedback to data librarians, data curators and repository managers, as well as other information professionals as to the information needs of scientists reusing data. The suggestions could be implemented to improve consultative practices when working alongside scientists regarding data deposition and data creation. These suggestions could improve policies for data repositories through direct feedback from scientists. These suggestions could be implemented to improve how data repositories are created and what should be considered mandatory information and secondary information to improve the reusability of data. Social implications – By examining the information needs of earth and environmental scientists reusing data, this study provides feedback that could change current practices in data deposition, which ultimately could improve the potentiality of data reuse. Originality/value – While there has been research conducted on data sharing and reuse, this study provides more detailed granularity regarding what information is needed to determine reusability. This study sets itself apart by not focusing on social motivators and demotivators, but by focusing on information provided in a data record.
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    Data reusers’ trust development.
    (2017) Yoon, Ayoung
    Data reuse refers to the secondary use of data—not for its original purpose but for studying new problems. Although reusing data might not yet be the norm in every discipline, the benefits of reusing shared data have been asserted by a number of researchers, and data reuse has been a major concern in many disciplines. Assessing data for trustworthiness becomes important in data reuse with the growth in data creation because of the lack of standards for ensuring data quality and potential harm from using poor-quality data. This research explores many facets of data reusers’ trust in data generated by other researchers focusing on the trust judgment process with influential factors that determine reusers’ trust. The author took an interpretive qualitative approach by using in-depth semistructured interviews as the primary research method. The study results suggest different stages of trust development associated with the process of data reuse. Data reusers’ trust may remain the same throughout their experiences, but it can also be formed, lost, declined, and recovered during their data reuse experiences. These various stages reflect the dynamic nature of trust.
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    Developing incentives for data stewardship and sharing: Library engagement beyond liaison relationships
    (2014-06-05) Coates, Heather L.; Polley, David E.
    Many of the obstacles slowing the adoption of more democratic dissemination of scholarly products are cultural, not technological. While libraries have extended their technological capacity to new methods of dissemination, we have been less proactive in fostering the cultural change necessary for significant adoption. Two particular groups of constituents and communities of practice have been engaged with the library profession, but the personal contact between faculty and librarians at the institutional level is inconsistent and often hinges upon liaison relationships. This poster will describe opportunities for librarians to engage with institutional units and research communities extending beyond institutional boundaries to advance incentives rewarding new forms of dissemination, including data as a valued community resource. Examples of relating changes in dissemination to various community missions will be provided.
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    Empowering communities with data: Role of data intermediaries for communities' data utilization
    (2018) Yoon, Ayoung; Copleand, Andrea; McNally, Paula
    Data have significant potential to address current societal problems not only at the federal and state levels, but also in smaller communities, in neighborhoods, and in the lives of individuals. While the proposition for this potential is that data are and will be shared with and reused by and for communities at different levels, not all data are not systematically or routinely shared for reuse with communities due to social, structural and technical infrastructure barriers. Data intermediary organizations can play a significant role in removing existing barriers while unlocking the potential of data for all, particularly for communities with limited human or financial resources, limited access to existing data infrastructures, and underserved populations. Considering the significance of the data intermediary organizations on local communities, this study aims to explore the role of intermediaries that usually facilitate community members/organizations’ data utilization. The findings of this study reveal that data intermediary organizations play four major roles that are crucial in communities’ data utilization: (1) democratizing data, (2) adding value to existing data, (3) enhancing communities’ data literacy, and (4) building communities’ data capacity. This study has several important implications to offer a solution to overcome the challenges of data reuse at the local level.
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    Improving data management in academic research: Assessment results for a pilot lab
    (2014-05-19) Coates, Heather L.
    Common practices for data collection, storage, organization, documentation, sharing, re-use, and preservation are often suboptimal. Issues often arising from common data practices include data loss, corruption, poor data integrity, and an inability to demonstrate the provenance (i.e., the origin) of the data. Ineffective data management can result in data that are unusable for re-use and re-analysis. However, effective data management practices exist to support data integrity, interoperability, and re-use. These practices maximize the value and potential impact of any particular dataset. In light of the gap between common practice and known effective strategies, we developed an intensive lab curriculum to train students and research support staff in implementing these strategies. This lab addresses the lack of formal data management training available on our campus and targets key processes in the data life cycle, promoting strategies that facilitate generation of quality data appropriate for re-use.
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    Social scientists’ data reuse behaviors: Exploring the roles of attitudinal beliefs, attitudes, norms, and data repositories.
    (Elsevier, 2017-07) Yoon, Ayoung; Kim, Youngseek
    Many disciplines within the social sciences have a dynamic culture of sharing and reusing data. Because social science data differ from data in the hard sciences, it is necessary to explicitly examine social science data reuse. This study explores the data reuse behaviors of social scientists in order to better understand both the factors that influence those social scientists' intentions to reuse data and the extent to which those factors influence actual data reuse. Using an integrated theoretical model developed from the theory of planned behavior (TPB) and the technology acceptance model (TAM), this study provides a broad explanation of the relationships among factors influencing social scientists' data reuse. A total of 292 survey responses were analyzed using structural equation modeling. Findings suggest that social scientists' data reuse intentions are directly influenced by the subjective norm of data reuse, attitudes toward data reuse, and perceived effort involved in data reuse. Attitude toward data reuse mediated social scientists' intentions to reuse data, leading to the indirect influence of the perceived usefulness and perceived concern of data reuse, as well as the indirect influence of the subjective norm of data reuse. Finally, the availability of a data repository indirectly influenced social scientists' intentions to reuse data by reducing the perceived effort involved.
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    Teaching data literacy skills in a lab environment
    (2014-06-04) Coates, Heather L.
    Equipping researchers with the skills to effectively utilize data in the global data ecosystem requires proficiency with data literacies and electronic resource management. This is a valuable opportunity for libraries to leverage existing expertise and infrastructure to address a significant gap data literacy education. This session will describe a workshop for developing core skills in data literacy. In light of the significant gap between common practice and effective strategies emerging from specific research communities, we incorporated elements of a lab format to build proficiency with specific strategies. The lab format is traditionally used for training procedural skills in a controlled setting, which is also appropriate for teaching many daily data management practices. The focus of the curriculum is to teach data management strategies that support data quality, transparency, and re-use. Given the variety of data formats and types used in health and social sciences research, we adopted a skills-based approach that transcends particular domains or methodologies. Attendees applied selected strategies using a combination of their own research projects and a carefully defined case study to build proficiency.