scholarly journals A Data Citation Roadmap for Scholarly Data Repositories

2016 ◽  
Author(s):  
Martin Fenner ◽  
Mercè Crosas ◽  
Jeffrey Grethe ◽  
David Kennedy ◽  
Henning Hermjakob ◽  
...  
Keyword(s):  
Science Policy ◽  
Expert Group ◽  
Data Repositories ◽  
Data Publication ◽  
Link Type ◽  
Joint Declaration ◽  
Data Citation ◽  
Scholarly Data ◽  
Three Phases

AbstractThis article presents a practical roadmap for scholarly data repositories to implement data citation in accordance with the Joint Declaration of Data Citation Principles, a synopsis and harmonization of the recommendations of major science policy bodies. The roadmap was developed by the Repositories Expert Group, as part of the Data Citation Implementation Pilot (DCIP) project, an initiative of FORCE11.org and the NIH BioCADDIE (https://biocaddie.org) program. The roadmap makes 11 specific recommendations, grouped into three phases of implementation: a) required steps needed to support the Joint Declaration of Data Citation Principles, b) recommended steps that facilitate article/data publication workflows, and c) optional steps that further improve data citation support provided by data repositories.

scholarly journals Achieving human and machine accessibility of cited data in scholarly publications

2015 ◽  
Author(s):  
Joan Starr ◽  
Eleni Castro ◽  
Mercè Crosas ◽  
Michel Dumontier ◽  
Robert R. Downs ◽  
...  
Keyword(s):  
Scientific Data ◽  
Primary Data ◽  
Data Repositories ◽  
Staff Members ◽  
Joint Declaration ◽  
Scholarly Publications ◽  
Comprehensive Exploitation ◽  
Data Citation ◽  
Persistent Data ◽  
Scholarly Data

Reproducibility and reusability of research results is an important concern in scientific communication and science policy. A foundational element of reproducibility and reusability is the open and persistently available presentation of research data. However, many common approaches for primary data publication in use today do not achieve sufficient long-term robustness, openness, accessibility or uniformity. Nor do they permit comprehensive exploitation by modern Web technologies. This has led to several authoritative studies recommending uniform direct citation of data archived in persistent repositories. Data are to be considered as first-class scholarly objects, and treated similarly in many ways to cited and archived scientific and scholarly literature. Here we briefly review the most current and widely agreed set of principle-based recommendations for scholarly data citation, the Joint Declaration of Data Citation Principles (JDDCP). We then present a framework for operationalizing the JDDCP; and a set of initial recommendations on identifier schemes, identifier resolution behavior, required metadata elements, and best practices for realizing programmatic machine actionability of cited data. The main target audience for the common implementation guidelines in this article consists of publishers, scholarly organizations, and persistent data repositories, including technical staff members in these organizations. But ordinary researchers can also benefit from these recommendations. The guidance provided here is intended to help achieve widespread, uniform human and machine accessibility of deposited data, in support of significantly improved verification, validation, reproducibility and re-use of scholarly/scientific data.

scholarly journals Achieving human and machine accessibility of cited data in scholarly publications

2015 ◽  
Author(s):  
Joan Starr ◽  
Eleni Castro ◽  
Mercè Crosas ◽  
Michel Dumontier ◽  
Robert R. Downs ◽  
...  
Keyword(s):  
Scientific Data ◽  
Primary Data ◽  
Data Repositories ◽  
Staff Members ◽  
Joint Declaration ◽  
Scholarly Publications ◽  
Comprehensive Exploitation ◽  
Data Citation ◽  
Persistent Data ◽  
Scholarly Data

Reproducibility and reusability of research results is an important concern in scientific communication and science policy. A foundational element of reproducibility and reusability is the open and persistently available presentation of research data. However, many common approaches for primary data publication in use today do not achieve sufficient long-term robustness, openness, accessibility or uniformity. Nor do they permit comprehensive exploitation by modern Web technologies. This has led to several authoritative studies recommending uniform direct citation of data archived in persistent repositories. Data are to be considered as first-class scholarly objects, and treated similarly in many ways to cited and archived scientific and scholarly literature. Here we briefly review the most current and widely agreed set of principle-based recommendations for scholarly data citation, the Joint Declaration of Data Citation Principles (JDDCP). We then present a framework for operationalizing the JDDCP; and a set of initial recommendations on identifier schemes, identifier resolution behavior, required metadata elements, and best practices for realizing programmatic machine actionability of cited data. The main target audience for the common implementation guidelines in this article consists of publishers, scholarly organizations, and persistent data repositories, including technical staff members in these organizations. But ordinary researchers can also benefit from these recommendations. The guidance provided here is intended to help achieve widespread, uniform human and machine accessibility of deposited data, in support of significantly improved verification, validation, reproducibility and re-use of scholarly/scientific data.

scholarly journals Achieving human and machine accessibility of cited data in scholarly publications

2015 ◽  
Author(s):  
Joan Starr ◽  
Eleni Castro ◽  
Mercè Crosas ◽  
Michel Dumontier ◽  
Robert R. Downs ◽  
...  
Keyword(s):  
Scientific Data ◽  
Primary Data ◽  
Data Repositories ◽  
Staff Members ◽  
Joint Declaration ◽  
Scholarly Publications ◽  
Comprehensive Exploitation ◽  
Data Citation ◽  
Persistent Data ◽  
Scholarly Data

Reproducibility and reusability of research results is an important concern in scientific communication and science policy. A foundational element of reproducibility and reusability is the open and persistently available presentation of research data. However, many common approaches for primary data publication in use today do not achieve sufficient long-term robustness, openness, accessibility or uniformity. Nor do they permit comprehensive exploitation by modern Web technologies. This has led to several authoritative studies recommending uniform direct citation of data archived in persistent repositories. Data are to be considered as first-class scholarly objects, and treated similarly in many ways to cited and archived scientific and scholarly literature. Here we briefly review the most current and widely agreed set of principle-based recommendations for scholarly data citation, the Joint Declaration of Data Citation Principles (JDDCP). We then present a framework for operationalizing the JDDCP; and a set of initial recommendations on identifier schemes, identifier resolution behavior, required metadata elements, and best practices for realizing programmatic machine actionability of cited data. The main target audience for the common implementation guidelines in this article consists of publishers, scholarly organizations, and persistent data repositories, including technical staff members in these organizations. But ordinary researchers can also benefit from these recommendations. The guidance provided here is intended to help achieve widespread, uniform human and machine accessibility of deposited data, in support of significantly improved verification, validation, reproducibility and re-use of scholarly/scientific data.

scholarly journals A data citation roadmap for scientific publishers

2017 ◽  
Author(s):  
Helena Cousijn ◽  
Amye Kenall ◽  
Emma Ganley ◽  
Melissa Harrison ◽  
David Kernohan ◽  
...  
Keyword(s):  
Science Policy ◽  
Expert Group ◽  
Early Adopters ◽  
Joint Declaration ◽  
Data Citation ◽  
Starting Point ◽  
Data Transparency ◽  
Scientific Publishers

AbstractThis article presents a practical roadmap for scholarly publishers to implement data citation in accordance with the Joint Declaration of Data Citation Principles (JDDCP), a synopsis and harmonization of the recommendations of major science policy bodies. It was developed by the Publishers Early Adopters Expert Group as part of the Data Citation Implementation Pilot (DCIP) project, an initiative of FORCE11.org and the NIH BioCADDIE program. The structure of the roadmap presented here follows the “life of a paper” workflow and includes the categories Pre-submission, Submission, Production, and Publication. The roadmap is intended to be publisher-agnostic so that all publishers can use this as a starting point when implementing JDDCP-compliant data citation. Authors reading this roadmap will also better know what to expect from publishers and how to enable their own data citations to gain maximum impact, as well as complying with what will become increasingly common funder mandates on data transparency.

scholarly journals Achieving human and machine accessibility of cited data in scholarly publications

2014 ◽  
Author(s):  
Joan Starr ◽  
Eleni Castro ◽  
Mercè Crosas ◽  
Michel Dumontier ◽  
Robert R. Downs ◽  
...  
Keyword(s):  
Short Article ◽  
Joint Declaration ◽  
Cross Domain ◽  
Widespread Adoption ◽  
Scholarly Publications ◽  
Data Citation ◽  
Scholarly Data ◽  
Operational Guidance

This short article provides operational guidance on implementing scholarly data citation and data deposition, in conformance with the Joint Declaration of Data Citation Principles (JDDCP, http://force11.org/datacitation) to help achieve widespread, uniform human and machine accessibility of deposited data. The JDDCP is the outcome of a cross-domain effort to establish core principles around cited data in scholarly publications. It deals with important issues in identification, deposition, description, accessibility, persistence, and evidential status of cited data. Eighty-five scholarly, governmental, and funding institutions have now endorsed the JDDCP. The purpose of this article is to provide the necessary guidance for JDDCP-endorsing organizations to implement these principles and to achieve their widespread adoption.

scholarly journals Achieving human and machine accessibility of cited data in scholarly publications

2014 ◽  
Author(s):  
Joan Starr ◽  
Eleni Castro ◽  
Mercè Crosas ◽  
Michel Dumontier ◽  
Robert R. Downs ◽  
...  
Keyword(s):  
Short Article ◽  
Joint Declaration ◽  
Cross Domain ◽  
Widespread Adoption ◽  
Scholarly Publications ◽  
Data Citation ◽  
Scholarly Data ◽  
Operational Guidance

This short article provides operational guidance on implementing scholarly data citation and data deposition, in conformance with the Joint Declaration of Data Citation Principles (JDDCP, http://force11.org/datacitation) to help achieve widespread, uniform human and machine accessibility of deposited data. The JDDCP is the outcome of a cross-domain effort to establish core principles around cited data in scholarly publications. It deals with important issues in identification, deposition, description, accessibility, persistence, and evidential status of cited data. Eighty-five scholarly, governmental, and funding institutions have now endorsed the JDDCP. The purpose of this article is to provide the necessary guidance for JDDCP-endorsing organizations to implement these principles and to achieve their widespread adoption.

scholarly journals A data citation roadmap for scholarly data repositories

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Martin Fenner ◽  
Mercè Crosas ◽  
Jeffrey S. Grethe ◽  
David Kennedy ◽  
Henning Hermjakob ◽  
...  
Keyword(s):  
Data Repositories ◽  
Data Citation ◽  
Scholarly Data

scholarly journals Connecting Data Publication to the Research Workflow: A Preliminary Analysis

2017 ◽  
Vol 12 (1) ◽  
pp. 88-105 ◽  
Author(s):  
Sünje Dallmeier-Tiessen ◽  
Varsha Khodiyar ◽  
Fiona Murphy ◽  
Amy Nurnberger ◽  
Lisa Raymond ◽  
...  
Keyword(s):  
Working Group ◽  
Research Data ◽  
Data Publishing ◽  
Data Repository ◽  
Research Activity ◽  
Data Repositories ◽  
Data Publication ◽  
Loosely Coupled ◽  
Definition Of ◽  
Data Documentation

The data curation community has long encouraged researchers to document collected research data during active stages of the research workflow, to provide robust metadata earlier, and support research data publication and preservation. Data documentation with robust metadata is one of a number of steps in effective data publication. Data publication is the process of making digital research objects ‘FAIR’, i.e. findable, accessible, interoperable, and reusable; attributes increasingly expected by research communities, funders and society. Research data publishing workflows are the means to that end. Currently, however, much published research data remains inconsistently and inadequately documented by researchers. Documentation of data closer in time to data collection would help mitigate the high cost that repositories associate with the ingest process. More effective data publication and sharing should in principle result from early interactions between researchers and their selected data repository. This paper describes a short study undertaken by members of the Research Data Alliance (RDA) and World Data System (WDS) working group on Publishing Data Workflows. We present a collection of recent examples of data publication workflows that connect data repositories and publishing platforms with research activity ‘upstream’ of the ingest process. We re-articulate previous recommendations of the working group, to account for the varied upstream service components and platforms that support the flow of contextual and provenance information downstream. These workflows should be open and loosely coupled to support interoperability, including with preservation and publication environments. Our recommendations aim to stimulate further work on researchers’ views of data publishing and the extent to which available services and infrastructure facilitate the publication of FAIR data. We also aim to stimulate further dialogue about, and definition of, the roles and responsibilities of research data services and platform providers for the ‘FAIRness’ of research data publication workflows themselves.

scholarly journals Data publication consensus and controversies

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 94 ◽  
Author(s):  
John Kratz ◽  
Carly Strasser
Keyword(s):  
Peer Review ◽  
Journal Article ◽  
Full Range ◽  
Basic Data ◽  
Descriptive Data ◽  
Data Publication ◽  
The Core ◽  
Data Citation ◽  
Core Elements

The movement to bring datasets into the scholarly record as first class research products (validated, preserved, cited, and credited) has been inching forward for some time, but now the pace is quickening. As data publication venues proliferate, significant debate continues over formats, processes, and terminology. Here, we present an overview of data publication initiatives underway and the current conversation, highlighting points of consensus and issues still in contention. Data publication implementations differ in a variety of factors, including the kind of documentation, the location of the documentation relative to the data, and how the data is validated. Publishers may present data as supplemental material to a journal article, with a descriptive “data paper,” or independently. Complicating the situation, different initiatives and communities use the same terms to refer to distinct but overlapping concepts. For instance, the term published means that the data is publicly available and citable to virtually everyone, but it may or may not imply that the data has been peer-reviewed. In turn, what is meant by data peer review is far from defined; standards and processes encompass the full range employed in reviewing the literature, plus some novel variations. Basic data citation is a point of consensus, but the general agreement on the core elements of a dataset citation frays if the data is dynamic or part of a larger set. Even as data publication is being defined, some are looking past publication to other metaphors, notably “data as software,” for solutions to the more stubborn problems.

scholarly journals Contributor Information in DataCite Metadata

2015 ◽  
Author(s):  
Martin Fenner
Keyword(s):  
Joint Declaration ◽  
Data Citation

The Force11 Joint Declaration of Data Citation Principles (Data Citation Synthesis Group, 2014) highlight the importance of giving scholarly credit to all contributors:Data citations should facilitate giving scholarly credit and normative and legal attribution to all contributors to the data, ...

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