brown bag talk with micah altman integrating open data into open access journals

Integrating Open Data into Open Access Journals


Micah AltmanDirector of Research

MIT Libraries

Prepared for

Program on Information Science Brown Bag Series

MIT

October 2015


Roadmap

Motivation

• Reproducibility

Intervention

• Integrating journal and data publication workflow

Future• Changing policies & uses


Credits&

Disclaimers


DISCLAIMERThese opinions are my own, they are not the opinions of MIT, Brookings, any of the project funders, nor (with the exception of co-authored previously published work) my collaborators

Secondary disclaimer:

“It’s tough to make predictions, especially about the future!”

-- Attributed to Woody Allen, Yogi Berra, Niels Bohr, Vint Cerf, Winston Churchill, Confucius, Disreali [sic], Freeman Dyson, Cecil B. Demille, Albert Einstein, Enrico Fermi, Edgar R. Fiedler, Bob Fourer, Sam Goldwyn, Allan Lamport, Groucho Marx,

Dan Quayle, George Bernard Shaw, Casey Stengel, Will Rogers, M. Taub, Mark Twain, Kerr L. White, etc.


Collaborators & Co-Conspirators Collaborators and Co-conspirators

IQSS, Harvard: Eleni Castro, Mercè Crosas, Phil Durbin

PKP Project: Alex Garnett, Jenn Whitney

Research Support Supported by the Sloan Foundation


Related Work

Project Website

projects.iq.harvard.edu/ojs-dvn

Related publications:(Reprints available from: informatics.mit.edu ) Altman M, Castro E, Crosas M, Durbin P, Garnett A, Whitney J. Open

Journal Systems and Dataverse Integration-- Helping Journals to Upgrade Data Publication for Reusable Research. Code4Lib Journal. Forthcoming.

Altman M, Avery M. 2015 Information wants someone else to pay for it: laws of information economics and scholarly publishing. Information Services and Use . 2015;35(1-2):57-70.

Altman M, Borgman C, Crosas M, Martone M. An Introduction to the Joint Principles for Data Citation. Bulletin of the Association for Information Science and Technology [Internet]. 2015;41(3):43-44.

Brand A, Allen L, Altman M, Hlava M, Scott J. Beyond authorship: attribution, contribution, collaboration, and credit. Learned Publishing. 2015;28(2):151-155.

http://projects.iq.harvard.edu/ojs-dvn



http://informatics.mit.edu/


Concerns forReliable Science


New Initiatives to Improve Scientific Reliability

Retraction monitoring Data citation Clinical trial

preregistration Registered replication Open data Badges


What can go wrong?

Misconduct & Lies


Irreproducible Results


Many journals have no replication policy

Even in journals with clear policy, success rate is low

The File Drawer Problem


Daniel Schectman’s Lab Notebook

Providing Initial

Evidence of Quasi Crystals

• Null results are less likely to be published published results as a whole are biased toward positive findings

• Outliers are routinely discarded unexpected patterns of evidence across studies remain hidden


Potential Interventions

Trustworthy Science

Access to Scholarly Record

Reproducible processes

Attribution &

Provenance

Management and

Governance of the

Evidence Base

Measurement and Evaluation


The ProjectCitation to Data

Citation to

Article• Technical Integration

• Socio-Technical Intervention


Integrating Open Journals and Data Publishing Who? Address the needs of journals

publishers and editors What? Enable journals to seamlessly

manage the submission, review, citation, and publication of data associate with published articles.

How? Integrate existing technologies and workflows, promote adoption through outreach and involvement.

Why? Increase replicability of science, facilitate peer-review of data, promote long-term access to the scientific evidence base.

17

Introduction to Dataverse

Provides incentives for researchers to share:• Recognition & credit via data

citations• Control over data & branding• Fulfill journal data availability and

funder requirements.

Software framework for publishing, citing and preserving research data (open source on github for others to install)

1290 Dataverses

Harvard Dataverse (open to all; repository instance at Harvard) has:

59,346 Dataset

s 248,351 Files

> 1 Million Downloads

https://github.com/IQSS/dvn

http://thedata.harvard.edu/

http://thedata.harvard.edu/


Open Journal System (OJS)

Open source journal management and publishing systemcreated by the Public Knowledge Project (PKP) to expand & improve

access to research.


About OJS OJS Software hosts almost

10000 active journals Used in all continents Particularly popular in developing

countries OJS Model

Open Access Publication Open Software

Services Journal hosting Crossref intergration PLOS Article Level Metrics LOCKSS Integration

OJS is part of a suite of products for automating workflow: Journal Publishing Monograph Publishing Conference Hosting


Integrating Workflow Across the Lifecycle


Actor Roles The Author submits their article and research data to the journal's OJS

article submission system. (Note that the article and data do not have to be submitted at the same time. Authors can also submit data at a later time, or they can just provide a persistent link with a data citation pointing to the repository that their data is currently in.)

Editors and/or Peer Reviewers review the article and data. If the article and corresponding research data are approved for

publication, the Authors' research data and its corresponding metadata is automatically deposited from OJS into the Dataverse through the API. No redundant information need be entered. A permanent identifier (DOI) will be automatically included that allows the data to be cited and tracked. There will be a data citation included in the journal article page in OJS (and ideally within the Reference section of the article) enabling readers of the article to quickly access the data.

The Dataverse stores the dataset metadata and files (including raw data, documentation, code, etc). There will also be a permanent publication citation link within the Dataverse for researchers to access the article in OJS that corresponds to this research data.


Developing a Data Submission & Review Workflow


OJS Plugin Architecture Plugin’s Extend Back-End Functionality and User Interface Data Publication now part of OJS distribution Can target any Dataverse repository


Author Submission Extends

supplementary file submission

Can provide extended metadata

Can provide data citation


Data Publication Data published through dataverse Provides on-line exploration, reformatting,

etc. Linked through citations, DOI’s and author

ID’s Data updates managed in repository


Integration Through Sword

Full SWORD 2 deposit interface

The core supported functions:

Retrieve SWORD service document Create a dataset with an Atom Dublin Core Terms (DC Terms) Qualified

Mapping - Dataverse DB Element Crosswalk

List datasets in a dataverse Add files to a dataset with a zip file Display a dataset atom entry Display a dataset statement Delete a file by database id Replacing metadata for a dataset Delete a dataset Determine if a dataverse has been

published Publish a dataverse Publish a dataset

Complementary Dataverse API’s Search Data Access Data Analysis Native Harvesting


REST-ful-nessList datasets in a dataversecurl -u $API_TOKEN: https://$HOSTNAME/dvn/api/data-deposit/v1.1/swordv2/collection/dataverse/$DATAVERSE_ALIAS

Add files to a dataset with a zip filecurl -u $API_TOKEN: --data-binary @path/to/example.zip -H "Content-Disposition: filename=example.zip" -H "Content-Type: application/zip" -H "Packaging: http://purl.org/net/sword/package/SimpleZip" https://$HOSTNAME/dvn/api/data-deposit/v1.1/swordv2/edit-media/study/doi:TEST/12345

Display a dataset atom entry

curl -u $API_TOKEN: https://$HOSTNAME/dvn/api/data-deposit/v1.1/swordv2/edit/study/doi:TEST/12345


Results First complete journal + data publishing workflow Successful integration of two major OSS systems Leverages a standard, open protocol; plugin

architecture Released and supported by existing development

communities


The Future


Policy Changes Since we Started

Preregistration Requirements

Data Sharing Requirements

Open Access Requirements

Data Citation Requirements


Evaluating Current Open Journal Policies Self selected sample of OJS Publishers Random Samples of

OJS Journals DOAJ Journals

Coding of data sharing policy by strength


Substantial Interest(In a self-selected sample) >200 OJS Journals

95% -- Data citation is important 75% -- Data sharing is important 72% -- Replicability is important


Limited Adoption of Data Policies in Open Access Journals


Comparison to Other Fields


Future Integrations PKP

push into Archivematic(experimental)

Deposit into other SWORD endpoints Dataverse

Accept deposits from OSF Accept deposits from other SWORD suppliers


Additional References● Crosas M. "A Data Sharing Story." Journal of

eScience Librarianship. 1(3), 173-179. 2013.● Crosas, M. "The Dataverse Network™: An

Open-Source Application for Sharing, Discovering and Preserving Data," D-lib Magazine 17(1/2). 2011.

● Willinsky, J. "Open Journal Systems: An example of open source software for journal management and publishing." Library Hi-Tech 23 (4), 504-519. 2005.

Questions?E-mail: [email protected]

Web: informatics.mit.edu


mailto:[email protected]

http://informatics.mit.edu/


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