DATA PUBLISHING WORKFLOWS WITH DATAVERSEprojects.iq.harvard.edu/files/ojs-dvn/files/rda... · DATA...
Transcript of DATA PUBLISHING WORKFLOWS WITH DATAVERSEprojects.iq.harvard.edu/files/ojs-dvn/files/rda... · DATA...
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DATA PUBLISHING WORKFLOWS WITH DATAVERSE Eleni Castro ([email protected]) Institute for Quantitative Social Science (IQSS) Harvard University
RDA 5th Plenary WG RDA/WDS Publishing Data Workflows March 11, 2015
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An Integrated & Automated Journal / Data Publishing Workflow
Features for automatic
data citation insertion into
article.
Workflows + features for reviewing
data before article
publication.
Long term preservation +
persistent access to dataset.
New versions of a
dataset induce new research.
Automatic integration w/
data repositories
(common repository API).
Code
Submit
Review
Publish Reuse, Validate &
Extend
Prepare new submission
Features for automatic
data citation insertion into
article.
Workflows + features for reviewing
data before article
publication.
Long term preservation +
persistent access to dataset.
New versions of a
dataset induce new research.
Automatic integration w/
data repositories
(common repository API).
Code
Submit
Review
Publish Reuse, Validate &
Extend
Prepare new submission
Features for automatic
data citation insertion into
article.
Workflows + features for reviewing
data before article
publication.
Long term preservation +
persistent access to dataset.
New versions of a
dataset induce new research.
Automatic integration w/
data repositories
(common repository API).
Code
Submit
Review
Publish Reuse, Validate &
Extend
Prepare new submission
Features for automatic
data citation insertion into
article.
Workflows + features for reviewing
data before article
publication.
Long term preservation +
persistent access to dataset.
New versions of a
dataset induce new research.
Automatic integration w/
data repositories
(common repository API).
Code
Submit
Review
Publish Reuse, Validate &
Extend
Prepare new submission
Features for automatic
data citation insertion into
article.
Workflows + features for reviewing
data before article
publication.
Long term preservation +
persistent access to dataset.
New versions of a
dataset induce new research.
Automatic integration w/
data repositories
(common repository API).
Code
Submit
Review
Publish Reuse, Validate &
Extend
Prepare new submission
Features for automatic
data citation insertion into
article.
Workflows + features for reviewing
data before article
publication.
Long term preservation +
persistent access to dataset.
New versions of a
dataset induce new research.
Automatic integration w/
data repositories
(common repository API).
Code
Submit
Review
Publish Reuse, Validate &
Extend
Prepare new submission
Features for automatic
data citation insertion into
article.
Workflows + features for reviewing
data before article
publication.
Long term preservation +
persistent access to dataset.
New versions of a
dataset induce new research.
Automatic integration w/
data repositories
(common repository API).
Code
Submit
Review
Publish Reuse, Validate &
Extend
Prepare new submission
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Journal
Repository
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Current Workflows in Dataverse: To Connect Data to Journals A. Journals include Dataverse as a Recommended Repository
B. Authors Contribute Directly to a Journal’s Dataverse
C. Automated Integration of Journal + Dataverse (e.g., OJS)
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Example of Option C: Phase 1 OJS / Dataverse Integration
ü Integrating Open Journal Systems (OJS) with Dataverse ü Reference Implementation: Automated via SWORD API
ü Pilot with ~ 50 journals + expand to 1000s using OJS. ü Dataverse plugin is automatically available w/ OJS. ü Future: Embed Dataverse widgets into journal article.
http://projects.iq.harvard.edu/ojs-dvn
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Project Details: 2012-2014 Project Details: 2012-2014 Project Details: 2012-2014
Project Details: 2012-2014
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In the Backend: Technical Workflow
Client sends: ü XML file: AtomPub "entry”
with Dublin Core Terms (e.g., title, creator, isReferencedBy (article citation), …)
ü Zip file: All data files associated with that dataset.
Repository sends: ü XML file: “Deposit Receipt”
send data citation from repository to client.
Plus updates from client to server during lifecycle (CRUD): In review, reject (delete), publish first version, update new versions.
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On the Frontend: OJS Dataverse Plugin Walkthrough
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Journal Manager Sets Up Plugin in OJS 7
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Journal Manager Sets Up Data Policies
Read full Data Policies / Guidelines Template: http://bit.ly/1xkLjoZ
Including Guidelines for: 1) Authors (data citation) 2) Reviewers 3) Copyeditors
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Author Submits Manuscript + Data (1) 9
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Author Submits Manuscript + Data (2)
Option to: (a) deposit into Dataverse OR; (b) if data is already in a repository can include the data citation (w/ persistent URL/identifier).
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To-Do: Support for adding multiple datasets to a journal article.
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Editor Reviews Article + Data 11
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Approved = Data Published in Dataverse
When issue is published: 1) URL to Article displays in Dataverse. 2) Data Citation shows up in OJS Article (see next slide).
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Article in OJS: Published w/ Data Citation
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Video of OJS Dataverse Plugin Demo 14
http://bit.ly/1D1hphu
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Phase 2: Expansion of API + Workflows
Features for automatic
data citation insertion into
article.
Workflows + features for reviewing
data before article
publication.
Long term preservation +
persistent access to dataset.
New versions of a
dataset induce new research.
Automatic integration w/
data repositories
(common repository API).
Code
Submit
Review
Publish Reuse, Validate &
Extend
Prepare new submission
Features for automatic
data citation insertion into
article.
Workflows + features for reviewing
data before article
publication.
Long term preservation +
persistent access to dataset.
New versions of a
dataset induce new research.
Automatic integration w/
data repositories
(common repository API).
Code
Submit
Review
Publish Reuse, Validate &
Extend
Prepare new submission
Features for automatic
data citation insertion into
article.
Workflows + features for reviewing
data before article
publication.
Long term preservation +
persistent access to dataset.
New versions of a
dataset induce new research.
Automatic integration w/
data repositories
(common repository API).
Code
Submit
Review
Publish Reuse, Validate &
Extend
Prepare new submission
Features for automatic
data citation insertion into
article.
Workflows + features for reviewing
data before article
publication.
Long term preservation +
persistent access to dataset.
New versions of a
dataset induce new research.
Automatic integration w/
data repositories
(common repository API).
Code
Submit
Review
Publish Reuse, Validate &
Extend
Prepare new submission
Features for automatic
data citation insertion into
article.
Workflows + features for reviewing
data before article
publication.
Long term preservation +
persistent access to dataset.
New versions of a
dataset induce new research.
Automatic integration w/
data repositories
(common repository API).
Code
Submit
Review
Publish Reuse, Validate &
Extend
Prepare new submission
Features for automatic
data citation insertion into
article.
Workflows + features for reviewing
data before article
publication.
Long term preservation +
persistent access to dataset.
New versions of a
dataset induce new research.
Automatic integration w/
data repositories
(common repository API).
Code
Submit
Review
Publish Reuse, Validate &
Extend
Prepare new submission
Features for automatic
data citation insertion into
article.
Workflows + features for reviewing
data before article
publication.
Long term preservation +
persistent access to dataset.
New versions of a
dataset induce new research.
Automatic integration w/
data repositories
(common repository API).
Code
Submit
Review
Publish Reuse, Validate &
Extend
Prepare new submission
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2015-2016 (collaboration w/ Odum Institute)
1. Expand to more journals, publishing systems, & workflows 1. Expand to more journals, publishing systems, & workflows 1. Expand to more journals, publishing systems, & workflows
1. Expand to more journals, publishing systems, & workflows 2. Develop Community-Based Repository API Standard:
Work w/ RDA, WDS, Data FAIRport, FORCE11, CODATA, etc…
q Should we extend the Repository API beyond SWORD? q Support for additional Metadata Schemas & fields (non-DC)? q Support for more/which dataset review workflows?
Project Goals
Project Questions
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How Do I Get Involved?
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Sign up to Contribute: Repositories Workshop + Dataverse Community Meeting June 9-11, 2015 @ Harvard http://bit.ly/1A51atJ
Find Out More: * Visit our Collaborations page: http://bit.ly/1Bg2nkw * Dataverse Project Site: http://dataverse.org
Contact Project Coordinator: Eleni Castro ([email protected])
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