Data Curation: A Study of Researcher Practices and Needs

McLure, Merinda; Level, Allison V.; Cranston, Catherine L.; Oehlerts, Beth; Culbertson, Mike

doi:10.1353/pla.2014.0009

Cited by 55 publications

(58 citation statements)

References 38 publications

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“…Almost without exception, survey and interview research exploring data management and sharing practices in academia exhibit striking homogeneity including: a general lack of data sharing through repositories and journals in favor of sharing via personal communication, researchers rarely creating metadata or other documentation for data, backup and storage practices that are of questionable efficacy and on questionable media, and concerns among researchers about the amount of time required to prepare data for sharing and the potential for misuse of data (Akers & Doty, 2013;Doty, 2012;Editorial, 2011;Parham, Bodnar, & Fuchs 2012;Steinhart, Chen, Arguillas, Dietrich, & Kramer, 2012;Cragin, Palmer, Carlson, & Witt, 2010;Peters & Dryden, 2011). On the other hand, the literature is similarly replete with survey and interview results suggesting that researchers are interested in training and guidance for research data management best practices (Akers & Doty, 2013;Parham et al, 2012;McClure, Level, Cranston, Oehlerts, & Culbertson, 2014, Wright et al, 2013.…”

Section: Literature Reviewmentioning

confidence: 99%

“…An alternative set of approaches favor in-depth interviews or focus group with researchers such as those conducted through the Data Curation Profiles Toolkit (datacurationprofiles. org; Carlson, 2012;Cragin et al, 2010;Wright et al, 2013;Zilinski & Lorenz, 2012) or through similar methods such as focus groups (McClure et al, 2014) or other interview protocols (e.g. Peters & Dryden, 2011).…”

Section: Literature Reviewmentioning

confidence: 99%

“…McClure et al (2014) and Steinhart et al (2012) asked researchers in focus groups about the types of services they would be interested in engaging with. Others, such as Wright et al 2013, asked researchers to prioritize a list of potential services.…”

Section: Literature Reviewmentioning

confidence: 99%

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Assessing Research Data Management Practices of Faculty at Carnegie Mellon University

Tuyl

Michalek

2015

Journal of Librarianship and Scholarly Communication

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INTRODUCTION Recent changes to requirements for research data management by federal granting agencies and by other funding institutions have resulted in the emergence of institutional support for these requirements. At CMU, we sought to formalize assessment of research data management practices of researchers at the institution by launching a faculty survey and conducting a number of interviews with researchers. METHODS We submitted a survey on research data management practices to a sample of faculty including questions about data production, documentation, management, and sharing practices. The survey was coupled with in-depth interviews with a subset of faculty. We also make estimates of the amount of research data produced by faculty. RESULTS Survey and interview results suggest moderate level of awareness of the regulatory environment around research data management. Results also present a clear picture of the types and quantities of data being produced at CMU and how these differ among research domains. Researchers identified a number of services that they would find valuable including assistance with data management planning and backup/storage services. We attempt to estimate the amount of data produced and shared by researchers at CMU. DISCUSSION Results suggest that researchers may need and are amenable to assistance with research data management. Our estimates of the amount of data produced and shared have implications for decisions about data storage and preservation. CONCLUSION Our survey and interview results have offered significant guidance for building a suite of services for our institution.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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Assessing Research Data Management Practices of Faculty at Carnegie Mellon University

Tuyl

Michalek

2015

Journal of Librarianship and Scholarly Communication

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“…3 Researchers also have a number of concerns about data management issues, such as data storage, integrity, and backup options. 4 Keil thus argues the researchers will need the help of a team of experts. 5 As a response to researchers' need and request for help with data management, academic libraries have been actively involved in research data services: that is, "services that address the full data lifecycle, including the data management plan, digital curation (selection, preservation, maintenance, and archiving), and metadata creation and conversion."…”

Section: Introductionmentioning

confidence: 99%

Research Data Management Services in Academic Libraries in the US: A Content Analysis of Libraries’ Websites

Yoon

Schultz

2017

CRL

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United States through a content analysis of 185 library websites, with four main areas of focus: service, information, education, and network. The results from the content analysis of these webpages reveals that libraries need to advance and engage more actively to provide services, supply information online, and develop educational services. There is also a wide variation among library data management services and programs according to their web presence. IntroductionThe importance of research data management has been emphasized over the past few decades. Tenopir et al. argue that, as science grows and moves toward more collaborative, data-intensive, and computational research, researchers are faced with various data management needs.1 Research data management is also mandated for scholarly researchers.2 Despite this, many researchers are unprepared for or lack sufficient time to handle the requirements of data management.3 Researchers also have a number of concerns about data management issues, such as data storage, integrity, and backup options. 4 Keil thus argues the researchers will need the help of a team of experts. 5As a response to researchers' need and request for help with data management, academic libraries have been actively involved in research data services: that is, "services that address the full data lifecycle, including the data management plan, digital Although libraries are aware of their potential role in and impact on research data management and curation and have started providing (or planning) data management services, not all libraries are in the same phase due to the different perceptions and needs related to data management at the institutional level, which vary with institutional capacity (and/or boundaries) and policies. Previous research reports that libraries face many challenges in data management program development (such as funding for personnel and equipment and lack of broader institutional support). Tools and recommendations have been developed by leading libraries to overcome these challenges, but other areas of support are needed, such as professional training and collaboration with other institutions to develop more skills in identifying appropriate materials.This study examined the research data (management) services in academic libraries in the United States through a content analysis of 185 library websites. Examining the current landscape of research data management services is timely and significant for both libraries that are currently planning to improve their data management services and those libraries that are already ahead in providing services. This research provides an overall understanding of where research data management programs are and where they are going; it also facilitates the understanding of current practices and data management recommendations and/or tool adoptions and reveals areas that need improvement and support. Literature ReviewMany researchers attest to the role of libraries in data management. Flore et al. argue that data management involv...

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“…They also recognize that "data must be managed with all commercial, legal and ethical obligations" [1] and that "not all data may need to be shared or preserved" [1]. Various scholarly studies have broadly reviewed aspects of academic research data including the kinds of data created, how researchers manage data, barriers to data curation, and how libraries and archives can support researchers in managing their data [2,3]. However, they do not address criteria for data that should not be kept.…”

Section: Introductionmentioning

confidence: 99%

What Not to Keep: Not All Data Has Future Research Value

Kung

Campbell

2016

J Can Health Libr Assoc

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Abstract:The rise of academic library involvement in research data management has presented numerous challenges for academic libraries. Although libraries and archives have always had collection development policies that defined what they would or would not collect, policies for selecting research data for preservation are in their infancy. This study surveyed and interviewed health sciences academic researchers. From this research an initial list of eight types of health research data were identified as data that should not be preserved and made public. These include research data that are: sensitive or confidential; proprietary; easily replicable; do not have good metadata; test, pilot, or intermediate data; bad or junk data; data that cannot be used by others for a variety of reasons; and older data that are not used and have no obvious cultural or historical value. Conclusions drawn from the study will help librarians and archivists make informed decisions about which types of research data are worth keeping.

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Data Curation: A Study of Researcher Practices and Needs

Cited by 55 publications

References 38 publications

Assessing Research Data Management Practices of Faculty at Carnegie Mellon University

Assessing Research Data Management Practices of Faculty at Carnegie Mellon University

Research Data Management Services in Academic Libraries in the US: A Content Analysis of Libraries’ Websites

What Not to Keep: Not All Data Has Future Research Value

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