Conceptualizing Data Curation Activities Within Two Academic Libraries

Authors: Lafferty-Hess, S., Rudder, J., Moira, D., Ivey, S., & Darragh, J.

Abstract
: A growing focus on sharing research data that meet certain standards, such as the FAIR guiding principles, has resulted in libraries increasingly developing and scaling up support for research data. As libraries consider what new data curation services they would like to provide as part of their repository programs, there are various questions that arise surrounding scalability, resource allocation, requisite expertise, and how to communicate these services to the research community. Data curation can involve a variety of tasks and activities. Some of these activities can be managed by systems, some require human intervention, and some require highly specialized domain or data type expertise.

At the 2017 Triangle Research Libraries Network Institute, staff from the University of North Carolina at Chapel Hill and Duke University used the 47 data curation activities identified by the Data Curation Network project to create conceptual groupings of data curation activities. The results of this “thought-exercise” are discussed in this white paper. The purpose of this exercise was to provide more specificity around data curation within our individual contexts as a method to consistently discuss our current service models, identify gaps we would like to fill, and determine what is currently out of scope. We hope to foster an open and productive discussion throughout the larger academic library community about how we prioritize data curation activities as we face growing demand and limited resources.

Citation: Lafferty-Hess, S., Rudder, J., Moira, D., Ivey, S., & Darragh, J. (2018, May 29). Conceptualizing Data Curation Activities Within Two Academic Libraries. http://doi.org/10.17605/OSF.IO/ZJ5PQ

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Source: LIS Scholarship Archive

Practices of research data curation in institutional repositories: A qualitative view from repository staff

Authors: Dong Joon Lee, Besiki Stvilia

Abstract: The importance of managing research data has been emphasized by the government, funding agencies, and scholarly communities. Increased access to research data increases the impact and efficiency of scientific activities and funding. Thus, many research institutions have established or plan to establish research data curation services as part of their Institutional Repositories (IRs). However, in order to design effective research data curation services in IRs, and to build active research data providers and user communities around those IRs, it is essential to study current data curation practices and provide rich descriptions of the sociotechnical factors and relationships shaping those practices. Based on 13 interviews with 15 IR staff members from 13 large research universities in the United States, this paper provides a rich, qualitative description of research data curation and use practices in IRs. In particular, the paper identifies data curation and use activities in IRs, as well as their structures, roles played, skills needed, contradictions and problems present, solutions sought, and workarounds applied. The paper can inform the development of best practice guides, infrastructure and service templates, as well as education in research data curation in Library and Information Science (LIS) schools.

Citation: Lee DJ, Stvilia B (2017) Practices of research data curation in institutional repositories: A qualitative view from repository staff. PLoS ONE 12(3): e0173987. https://doi.org/10.1371/journal.pone.0173987

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Source: PLoS ONE

Assessing Stewardship Maturity of the Global Historical Climatology Network-Monthly (GHCN-M) Dataset: Use Case Study and Lessons Learned

Authors: Ge Peng, Jay Lawrimore, Valerie Toner, Christina Lief, Richard Baldwin, Nancy Ritchey, Danny Brinegar, Stephen A. Del Greco

 

Abstract: Assessing stewardship maturity — the current state of how datasets are documented, preserved, stewarded, and made accessible publicly — is a critical step towards meeting U.S. federal regulations, organizational requirements, and user needs. The scientific data stewardship maturity matrix (DSMM), developed in partnership with NOAA’s National Centers of Environmental Information (NCEI) and the Cooperative Institute for Climate and Satellites-North Carolina (CICS-NC), provides a consistent framework for assessing stewardship maturity of individual Earth Science datasets and capturing justifications for transparency. The consolidated stewardship maturity information will allow users and decision-makers to make informed use decisions based on their unique data needs. This DSMM was applied to a widely utilized monthly-land-surface-temperature dataset derived from the Global Historical Climatology Network (GHCN-M). This paper describes the stewardship maturity ratings of GHCN-M version 3 and provides actionable recommendations for improving the maturity of the dataset. The results from the use case study show that an application of DSMM like this one is useful to people who produce or care for digital environmental datasets. Assessments can identify the strengths and weaknesses of an individual dataset or organization’s preservation and stewardship practices, including how information about the dataset is integrated into different systems.

 

Citation: Peng, G., Lawrimore, J., Toner, V., Lief, C., Baldwin, R., Ritchey, N., . . . Greco, S. A. (2016). Assessing Stewardship Maturity of the Global Historical Climatology Network-Monthly (GHCN-M) Dataset: Use Case Study and Lessons Learned. D-Lib Magazine, 22(11/12). doi.org/10.1045/november2016-peng

 

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A Data Citation Roadmap for Scholarly Data Repositories

Authors: Martin Fennera, Merce Crosasb, Jeffrey S. Grethec, David Kennedy, Henning Hermjakobe, Phillippe Rocca-Serraf, Robin Berjong, Sebastian Karcherh, Maryann Martonei, Tim Clark

 

Abstract: This article presents a practical roadmap for scholarly data repositories to implement data citation in accordance with the Joint Declaration of Data Citation Principles (Data Citation Synthesis Group, 2014), a synopsis and harmonization of the recommendations of major science policy bodies. The roadmap was developed by the Repositories Early Adopters Expert Group, part of the Data Citation Implementation Pilot (DCIP) project (FORCE11, 2015), an initiative of FORCE11.org and the NIH BioCADDIE (2016) program. The roadmap makes 11 specific recommendations, grouped into three phases of implementation: a) required steps needed to support the Joint Declaration of Data Citation Principles, b) recommended steps that facilitate article/data publication workflows, and c) optional steps that further improve data citation support provided by data repositories.

 

Citation: Fenner, M., Crosas, M., Grethe, J., Kennedy, D., Hermjakob, H., Rocca-Serra, P., … Clark, T. (2016). A Data Citation Roadmap for Scholarly Data Repositories. bioRxiv. https://doi.org/10.1101/097196

 

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Research Data Services in Academic Libraries: Data Intensive Roles for the Future?

Authors: Carol Tenopir, Dane Hughes, Suzie Allard, Mike Frame, Ben Birch, Lynn Baird, Robert Sandusky, Madison Langseth, and Andrew Lundeen

 

Abstract: Objectives: The primary objectives of this study are to gauge the various levels of Research Data Service academic libraries provide based on demographic factors, gauging RDS growth since 2011, and what obstacles may prevent expansion or growth of services.Methods: Survey of academic institutions through stratified random sample of ACRL library directors across the U.S. and Canada. Frequencies and chi-square analysis were applied, with some responses grouped into broader categories for analysis.

Results: Minimal to no change for what services were offered between survey years, and interviews with library directors were conducted to help explain this lack of change.

Conclusion: Further analysis is forthcoming for a librarians study to help explain possible discrepancies in organizational objectives and librarian sentiments of RDS.

 

Citation: Tenopir, C, Hughes, D, Allard, S, Frame, M, Birch, B, Baird, L., Sandusky, R, Langseth, M, & Lundeen, A (2015) Research Data Services in Academic Libraries: Data Intensive Roles for the FutureJournal of eScience Librarianship 4(2): e1085. http://dx.doi.org/10.7191/jeslib.2015.1085

 

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Data Curation and the Arts: How Do Musicians Curate Their Data?

Authors: Amy S. Jackson, Jonathan Wheeler, Todd Quinn

 

Abstract: Professional musicians were surveyed to determine how personal, amateur recordings of performances are shared with students and colleagues. Sharing files on social media is common, with Facebook, YouTube, and Vimeo used most frequently. Although these are popular social media platforms, they do not have enhanced format support and robust metadata. Additionally, licensing terms for each platform differ, and may be not in the best interest of the musician. Although recordings are not traditionally considered data, data curation principles can be applied to these types of files, and the library is positioned to become an active participant in this process.

 

Citation: Jackson, A. S., Wheeler, J., & Quinn, T. (2016). Data Curation and the Arts: How Do Musicians Curate Their Data? Music Reference Services Quarterly, 19(3–4), 191–207. http://digitalrepository.unm.edu/ulls_fsp/115/

 

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