An introduction to the joint principles for data citation

Altman, Micah; Borgman, Christine L.; Crosas, Mercè; Matone, Maryann

doi:10.1002/bult.2015.1720410313

Cited by 38 publications

(29 citation statements)

References 10 publications

(5 reference statements)

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“…They offer three different levels of transparency, from milder/entry-level to stronger requirements for authors. For data citation in particular, both the FORCE11 Joint Declaration of Data Citation Principles (JDDCP), 34 discussed by Altman and co-authors, 35 and Data Cite 36 provide guidance on community-driven data-citation practices that are both human understandable and machine actionable, requiring both a persistent identifier for the data set and a minimum amount of metadata to allow for attribution and reuse. In addition, several of the authors behind the JDDCP are currently working on a publisher-agnostic road map (now in preprint) with detailed instructions to help with implementing JDDCP-compliant data citation.…”

mentioning

confidence: 99%

Evaluating and Promoting Open Data Practices in Open Access Journals

Castro¹,

Crosas²,

Garnett³

et al. 2017

Journal of Scholarly Publishing

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The last decade has seen a dramatic increase in attention from the scholarly communications and research community to open access (OA) and open data practices. These are potentially related because journal publication policies and practices both signal disciplinary norms and provide direct incentives for data sharing and citation. However, there is little research evaluating the data policies of OA journals. In this study we analyse the state of data policies for OA journals by employing random sampling of the Directory of Open Access Journals and Open Journal Systems journal directories and applying a coding framework that integrates both previous studies and emerging taxonomies of data sharing and citation. This study, for the first time, reveals both the low prevalence of datasharing policies and practices in OA journals, which differs from the previous studies of commercial journals in specific disciplines.

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mentioning

confidence: 99%

Evaluating and Promoting Open Data Practices in Open Access Journals

Castro¹,

Crosas²,

Garnett³

et al. 2017

Journal of Scholarly Publishing

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“…Starting 2004 as a German project, the foundation of DataCite on 1 December 2009 transformed this national effort into a successful international development (Brase et al, 2015). The FORCE11 Data Citation Synthesis Group formulated the 'Joint Declaration of Data Citation Principles' as general guidance on purpose, function and attributes of data citations (FORCE11, 2014;Altman et al, 2015; Table 1). The FORCE11 FAIR Data Publishing Group built on these the FAIR (Findable, Accessible, Interoperable, Re-usable) principles for data sharing (FORCE11, 2017).…”

Section: Citations Of Static and Evolving Datamentioning

confidence: 99%

CMIP6 Data Citation of Evolving Data

Stockhause

Lautenschlager

2017

Data Science Journal

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Data citations have become widely accepted. Technical infrastructures as well as principles and recommendations for data citation are in place but best practices or guidelines for their implementation are not yet available. On the other hand, the scientific climate community requests early citations on evolving data for credit, e.g. for CMIP6 (Coupled Model Intercomparison Project Phase 6). The data citation concept for CMIP6 is presented. The main challenges lie in limited resources, a strict project timeline and the dependency on changes of the data dissemination infrastructure ESGF (Earth System Grid Federation) to meet the data citation requirements. Therefore a pragmatic, flexible and extendible approach for the CMIP6 data citation service was developed, consisting of a citation for the full evolving data superset and a data cart approach for citing the concrete used data subset. This two citation approach can be implemented according to the RDA recommendations for evolving data. Because of resource constraints and missing project policies, the implementation of the second part of the citation concept is postponed to CMIP7.

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“…10,18–19 Data citation information is provided on individual dataset pages, in human-readable, machine-readable, and downloadable formats. The SBDG complements our AppCiter application, 20 which facilitates citation of research software.…”

Section: Supporting An Evolving Collection Of Large Biomedical Datasetsmentioning

confidence: 99%

Extension of research data repository system to support direct compute access to biomedical datasets: enhancing Dataverse to support large datasets

McKinney

Meyer

Crosas

et al. 2016

Annals of the New York Academy of Sciences

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Access to experimental X-ray diffraction image data is important for validation and reproduction of macromolecular models and indispensable for the development of structural biology processing methods. In response to the evolving needs of the structural biology community, we recently established a diffraction data publication system, the Structural Biology Data Grid (SBDG, data.sbgrid.org), to preserve primary experimental datasets supporting scientific publications. All datasets published through the SBDG are freely available to the research community under a public domain dedication license, with metadata compliant with the DataCite Schema (schema.datacite.org). A proof-of-concept study demonstrated community interest and utility. Publication of large datasets is a challenge shared by several fields, and the SBDG has begun collaborating with the Institute for Quantitative Social Science at Harvard University to extend the Dataverse (dataverse.org) open-source data repository system to structural biology datasets. Several extensions are necessary to support the size and metadata requirements for structural biology datasets. In this paper, we describe one such extension—functionality supporting preservation of filesystem structure within Dataverse—which is essential for both in-place computation and supporting non-http data transfers.

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An introduction to the joint principles for data citation

Cited by 38 publications

References 10 publications

Evaluating and Promoting Open Data Practices in Open Access Journals

Evaluating and Promoting Open Data Practices in Open Access Journals

CMIP6 Data Citation of Evolving Data

Extension of research data repository system to support direct compute access to biomedical datasets: enhancing Dataverse to support large datasets

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