Making Data a First Class Scientific Output: Data Citation and Publication by NERCâ€™s Environmental Data Centres

Callaghan, Sarah; Donegan, Steve; Pepler, Sam; Thorley, Mark; Cunningham, Nathan; Kirsch, Peter; Ault, Linda; Bell, Patrick; Bowie, Rod; Leadbetter, Adam; Lowry, Roy; Moncoiffé, Gwenaëlle; Harrison, Kate; Smith-Haddon, Ben; Weatherby, Anita J.; Wright, D.

doi:10.2218/ijdc.v7i1.218

Cited by 65 publications

(61 citation statements)

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“…Data papers can be published to make research data or datasets public (Breure 2014, Callaghan et al 2012, 112, Chavan and Penev 2011, 3, Gray 2015. It is required that data papers and research data have a digital object identifier (Candela et al 2015, 1754, Gray 2015.…”

Section: Literature Reviewmentioning

confidence: 99%

An analysis of characteristics and structures embedded in data papers

Chen

2017

libellarium

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Research data or datasets can be regarded as a catalyst to inspire new research by repurposing or combining existing research data, and grant applicants have been requested by funding institutions to include a data management plan as part of research project proposals. In addition to the metadata approach, data papers may mirror the scientific publication model as an alternative means of description and management of research data. However, there is not a common standard for all data papers across various communities. This study aimed to build up a common structural framework to investigate the embedded characteristics and structures of the content of data papers by using a content analysis approach, and 26 data journals from 16 publishers were selected as subject in this study. This study has proposed a common framework and further embodied a concept map (Candela et al. 2015) into more concrete components for the structure of data papers.

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Section: Literature Reviewmentioning

confidence: 99%

An analysis of characteristics and structures embedded in data papers

Chen

2017

libellarium

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“…Citations to data should be presented along with citations to other works, typically in a references or "literature cited" section (Altman, 2012;Callaghan et al, 2012). The former states the principle that data citations should be first-class objects for bibliographic purposes, and the latter made the argument that data themselves should be firstclass objects for scientific purposes.…”

Section: The Status Principlementioning

confidence: 99%

Out of Cite, Out of Mind: The Current State of Practice, Policy, and Technology for the Citation of Data

Socha¹

2013

Data Sci. J.

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Edited by Yvonne M. Socha PREFACEThe growth in the capacity of the research community to collect and distribute data presents huge opportunities. It is already transforming old methods of scientific research and permitting the creation of new ones. However, the exploitation of these opportunities depends upon more than computing power, storage, and network connectivity. Among the promises of our growing universe of online digital data are the ability to integrate data into new forms of scholarly publishing to allow peer-examination and review of conclusions or analysis of experimental and observational data and the ability for subsequent researchers to make new analyses of the same data, including their combination with other data sets and uses that may have been unanticipated by the original producer or collector.The use of published digital data, like the use of digitally published literature, depends upon the ability to identify, authenticate, locate, access, and interpret them. Data citations provide necessary support for these functions, as well as other functions such as attribution of credit and establishment of provenance. References to data, however, present challenges not encountered in references to literature. For example, how can one specify a particular subset of data in the absence of familiar conventions such as page numbers or chapters? The traditions and good practices for maintaining the scholarly record by proper references to a work are well established and understood in regard to journal articles and other literature, but attributing credit by bibliographic references to data are not yet so broadly implemented.Recognizing the needs for better data referencing and citation practices and investing effort to address those needs has come at different rates in different fields and disciplines. As competing conventions and practices emerge in separate communities, inconsistencies and incompatibilities can interfere with promoting the sharing and use of research data. In order to reconcile this problem, sharing experiences across communities may be necessary, or at least helpful, to achieving the full potential of published data.Practical and consistent data citation standards and practices are thus important for providing the incentives, recognition, and rewards that foster scientific progress. New requirements from funding agencies to develop data management plans emphasize the need to develop standards and data citation practices.

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“…Data publishing and citation practices are today strongly advocated by research communities, which need datasets to become first citizens in the research production chain. Datasets should be discoverable, reusable, and scientists who produce them should be scientifically rewarded for their efforts (Callaghan et al, 2012;Parsons & Fox, 2013).…”

Section: Interlinking With Research Datamentioning

confidence: 99%

Enhanced Publications: Data Models and Information Systems

Bardi

Manghi²

2014

LIBER

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Abstract"Enhanced publications" are commonly intended as digital publications that consist of a mandatory narrative part (the description of the research conducted) plus related "parts", such as datasets, other publications, images, tables, workflows, devices. The state-of-the-art on information systems for enhanced publica tions has today reached the point where some kind of common understanding is required, in order to provide the methodology and language for scientists to com pare, analyse, or simply discuss the multitude of solutions in the field. In this paper, we thoroughly examined the literature with a two-fold aim: firstly, introducing the terminology required to describe and compare structural and semantic features of existing enhanced publication data models; secondly, proposing a classification of enhanced publication information systems based on their main functional goals.

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Making Data a First Class Scientific Output: Data Citation and Publication by NERCâ€™s Environmental Data Centres

Cited by 65 publications

References 1 publication

An analysis of characteristics and structures embedded in data papers

An analysis of characteristics and structures embedded in data papers

Out of Cite, Out of Mind: The Current State of Practice, Policy, and Technology for the Citation of Data

Enhanced Publications: Data Models and Information Systems

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