DATA PUBLISHING WORKFLOWS WITH DATAVERSEprojects.iq.harvard.edu/files/ojs-dvn/files/rda... · DATA...

DATA PUBLISHING WORKFLOWS WITH DATAVERSE Eleni Castro (ecastro@fas.harvard.edu) Institute for Quantitative Social Science (IQSS) Harvard University

RDA 5th Plenary WG RDA/WDS Publishing Data Workflows March 11, 2015

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

2

Journal

Repository

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)

3

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

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

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

8

Author Submits Manuscript + Data (1) 9

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).

10

To-Do: Support for adding multiple datasets to a journal article.

Editor Reviews Article + Data 11

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).

12

1

2

Article in OJS: Published w/ Data Citation

13

Video of OJS Dataverse Plugin Demo 14

http://bit.ly/1D1hphu

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

15

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

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 (ecastro@fas.harvard.edu)

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Thank You! Any Questions?

17

Contact Me: Eleni Castro (ecastro@fas.harvard.edu)