The History, Advocacy and Efficacy of Data Management Plans

Smale, Nicholas; Unsworth, Kathryn; Denyer, Gareth; Barr, Daniel P.

doi:10.1101/443499

Cited by 12 publications

(19 citation statements)

References 38 publications

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“…Based on the results of this analysis, Smale et al find that the majority of the DMPs assessed in this study would be "of little to no benefit to the researcher, institution or funding body, given that they do not appear to describe a plan for data management" 15 . Limited additional research has investigated the implementation of these DMPs to evaluate how successful researchers are in carrying out the tasks they have laid out.…”

Section: Dmps Are Largely Ineffectivementioning

confidence: 86%

“…DMPs were then scored a 1 or 0 for each factor depending on whether the variables that fell within each criterion were exhibited. Results of this research show that for the majority of DMPs reviewed 88 per cent exhibited little or no information about data details or presented a poor quality of description, half of the analysed DMPs scored poorly on the attitude/effort criteria, and over 63 per cent of data described in the DMP could not be found online 15 .…”

Section: Dmps Are Largely Ineffectivementioning

confidence: 86%

“…Data management plans are considered the most effective way of asking the researcher to communicate his or her intentions for storing, using, maintaining, and making available the data resulting from a project. Data management plans are generally defined as documents that provide researchers with a mechanism for stating how they will manage data associated with a research project's data lifecycle 15 . Miksa et al use the shorthand of describing them as "awareness tools."…”

Section: Data Management Plansmentioning

confidence: 99%

See 2 more Smart Citations

Data Management Plans A Review

Hudson‐Vitale

Sandy

2019

DESIDOC Jl. Lib. Info. Technol.

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With increasing world-wide emphasis on providing access to research data, data management plans (DMPs) have emerged as the expected way for researchers to formalise and communicate their intentions to stakeholders, including to their funders. This review paper focuses on a thematic analysis and presentation of empirical research on DMPs, a literature that is surprisingly limited, likely due to the young age of the field. Research shows that, despite the benefits associated with data sharing, DMPs have potential that is not being realised to the fullest. Researchers in scholarly communication and information science primarily have evaluated DMPs using text analysis methodologies, often supplementing them with surveys or interviews. Future study, especially in areas of machine-actionable DMPs is promising; such research is needed to further explore how DMPs can best be utilised to support data sharing.

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Section: Dmps Are Largely Ineffectivementioning

confidence: 86%

Section: Dmps Are Largely Ineffectivementioning

confidence: 86%

Section: Data Management Plansmentioning

confidence: 99%

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Data Management Plans A Review

Hudson‐Vitale

Sandy

2019

DESIDOC Jl. Lib. Info. Technol.

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“…Similar mandates from funding agencies of a variety of other countries include the UK (UKRI, n.d.), Canada (Government of Canada, 2016), Australia (ARC, 2017), European Union (Shearer, 2015), Japan (JST, 2013), and India (Department of Science & Technology, Government of India, n.d.). In the UK, the first data management plan (DMP henceforth) requirement was put in place by the Medical Research Council in 2006, soon followed by the Wellcome Trust in 2007 (Smale, Unsworth, Denyer, & Barr, 2018). The NSF in 2011 was the first funder in the US to implement a DMP requirement (National Science Foundation, 2010a).…”

Section: Introductionmentioning

confidence: 99%

“…The public access plan included a requirement that "all extramural researchers receiving Federal grants and contracts for scientific research and intramural researchers develop data management plans, as appropriate" (OSTP, 2013, p. 5). In August 2017, Smale et al (2018) surveyed 16 US national funding bodies and found that 10 required DMPs as did six of seven research councils in the UK (p. 10).…”

Section: Introductionmentioning

confidence: 99%

Providing Research Data Management (RDM) Services in Libraries: Preparedness, Roles, Challenges, and Training for RDM Practice

Tang

2019

Data and Information Management

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This paper reports the results of an international survey on research data management (RDM) services in libraries. More than 240 practicing librarians responded to the survey and outlined their roles and levels of preparedness in providing RDM services, challenges their libraries face, and knowledge and skills that they deemed essential to advance the RDM practice. Findings of the study revealed not only a number of location and organizational differences in RDM services and tools provided but also the impact of the level of preparedness and degree of development in RDM roles on the types of RDM services provided. Respondents’ perceptions on both the current challenges and future roles of RDM services were also examined. With a majority of the respondents recognizing the importance of RDM and hoping to receive more training while expressing concerns of lack of bandwidth or capacity in this area, it is clear that, in order to grow RDM services, institutional commitment to resources and training opportunities is crucial. As an emergent profession, data librarians need to be nurtured, mentored, and further trained. The study makes a case for developing a global community of practice where data librarians work together, exchange information, help one another grow, and strive to advance RDM practice around the world.

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How Research Data Management Plans Can Help in Harmonizing Open Science and Approaches in the Digital Economy

Salazar

Wentzel

Schimmler

et al. 2022

Chemistry A European J

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Within this perspective article, we intend to summarise definitions and terms that are often used in the context of open science and data‐driven R&D and we discuss upcoming European regulations concerning data, data sharing and handling. With this background in hand, we take a closer look at the potential connections and permeable interfaces of open science and digital economy, in which data and resulting immaterial goods can become vital pieces as tradeable items. We believe that both science and the digital economy can profit from a seamless transition and foresee that the scientific outcomes of publicly funded research can be better exploited. To close the gap between open science and the digital economy, and to serve for a balancing of the interests of data producers, data consumers, and an economy around services and the public, we introduce the concept of generic research data management plans (RDMs), which have in part been developed through a community effort and which have been evaluated by academic and industry members of the NFDI4Cat consortium. We are of the opinion that in data‐driven research, RDMs do need to become a vital element in publicly funded projects.

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The History, Advocacy and Efficacy of Data Management Plans

Cited by 12 publications

References 38 publications

Data Management Plans A Review

Data Management Plans A Review

Providing Research Data Management (RDM) Services in Libraries: Preparedness, Roles, Challenges, and Training for RDM Practice

How Research Data Management Plans Can Help in Harmonizing Open Science and Approaches in the Digital Economy

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