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 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 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 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, ...

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 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
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