DataStaR: An Institutional Approach to Research Data Curation

Steinhart, Gail

doi:10.29173/iq187

Cited by 12 publications

(12 citation statements)

References 7 publications

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“…These needs have already emerged and there are early attempts to address them, e.g., by envisaging prepublication repositories (Steinhart, 2007), by foreseeing the use of software management practices (Schopf, 2012;Gandrud, 2013), and by completely rethinking the publishing act (Assante et al, 2015). To some extent, the act of publishing a dataset in a repository should be just the beginning of large scale collaboration.…”

Section: Conclusion and Prospectmentioning

confidence: 99%

Are Scientific Data Repositories Coping with Research Data Publishing?

Assante

Candela

Castelli

et al. 2016

Data Science Journal

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Research data publishing is intended as the release of research data to make it possible for practitioners to (re)use them according to "open science" dynamics. There are three main actors called to deal with research data publishing practices: researchers, publishers, and data repositories. This study analyses the solutions offered by generalist scientific data repositories, i.e., repositories supporting the deposition of any type of research data. These repositories cannot make any assumption on the application domain. They are actually called to face with the almost open ended typologies of data used in science. The current practices promoted by such repositories are analysed with respect to eight key aspects of data publishing, i.e., dataset formatting, documentation, licensing, publication costs, validation, availability, discovery and access, and citation. From this analysis it emerges that these repositories implement well consolidated practices and pragmatic solutions for literature repositories. These practices and solutions can not totally meet the needs of management and use of datasets resources, especially in a context where rapid technological changes continuously open new exploitation prospects.

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Section: Conclusion and Prospectmentioning

confidence: 99%

Are Scientific Data Repositories Coping with Research Data Publishing?

Assante

Candela

Castelli

et al. 2016

Data Science Journal

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“…Secondly, support for data exchange among members of small project teams or close colleagues will be of particular value for many scientists who are not involved with large-scale projects or collaboratories that have information and communication systems at hand. DataStar is an example of a 'staging repository' that may prove optimal for this kind of function, as it supports deposit, use, exchange and storage of data until it is ready to be moved to a long-term repository or discarded (Steinhart 2007). Thirdly, explicit data-citation information must be included in IR records; these references may be different from those listed to citing the related publication, and users will benefit from actual references posted with unambiguous directions on when to use them.…”

Section: Implications For Institutional Repositories and University Dmentioning

confidence: 99%

Data sharing, small science and institutional repositories

Cragin

Palmer

Carlson

et al. 2010

Phil. Trans. R. Soc. A.

242

231

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Results are presented from the Data Curation Profiles project research, on who is willing to share what data with whom and when. Emerging from scientists' discussions on sharing are several dimensions suggestive of the variation in both what it means 'to share' and how these processes are carried out. This research indicates that data curation services will need to accommodate a wide range of subdisciplinary data characteristics and sharing practices. As part of a larger set of strategies emerging across academic institutions, institutional repositories (IRs) will contribute to the stewardship and mobilization of scientific research data for e-Research and learning. There will be particular types of data that can be managed well in an IR context when characteristics and practices are well understood. Findings from this study elucidate scientists' views on 'sharable' forms of data-the particular representation that they view as most valued for reuse by others within their own research areas-and the anticipated duration for such reuse. Reported sharing incidents that provide insights into barriers to sharing and related concerns on data misuse are included.

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“…al. 2010, Johns Hopkins University (Choudhury 2008(Choudhury , 2010, and Cornell University (Steinhart 2007. More recently, a number of American universities have undertaken local studies of the needs of researchers on their campuses in order to better understand opportunities for library involvement in data management.…”

Section: Literature Reviewmentioning

confidence: 99%

Building an Online Data Management Plan Tool

Reilly

Dryden

2013

Journal of Librarianship and Scholarly Communication

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Following the 2011 announcement by the National Science Foundation (NSF) that it would begin requiring Data Management Plans with every funding application, the University of Houston Libraries explored ways to support our campus researchers in meeting this requirement. A small team of librarians built an online tool using a Drupal module. The tool includes informational content, an interactive questionnaire, and an extensive FAQ to meet diverse researcher needs. This easily accessible and locally maintained tool allows us to provide a high level of personalized service to our researchers

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DataStaR: An Institutional Approach to Research Data Curation

Abstract: DataStaR: An Institutional Approach to Research Data Curation

Cited by 12 publications

References 7 publications

Are Scientific Data Repositories Coping with Research Data Publishing?

Are Scientific Data Repositories Coping with Research Data Publishing?

Data sharing, small science and institutional repositories

Building an Online Data Management Plan Tool

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