A cooperative for big data in scholarly publishing

Hawkins, Kevin S.

A cooperative for big data in scholarly publishing

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Description

Presented at Data Power 2017. This presentation describes the vision for a cooperative of stakeholder institutions called the Publishing Analytics Data Alliance.

Physical Description

17 p.

Creation Information

Hawkins, Kevin S. June 22, 2017.

Context

This presentation is part of the collection entitled: UNT Scholarly Works and was provided by the UNT Libraries to the UNT Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 63 times. More information about this presentation can be viewed below.

Author

Hawkins, Kevin S. University of North Texas

Contributing Authors

Chapman, Joyce Duke University
Melton, Sarah V. Boston College
Montgomery, Lucy Curtin University
Skinner, Katherine Educopia Institute
Berkery, Peter Association of American University Presses
Eve, Martin Paul Birbeck, University of London; Open Library of Humanities
Drummond, Christina Educopia Institute
MacGregor, James Public Knowledge Project
Neylon, Cameron Curtin University
Schiff, Lisa California Digital Library

Organizer of meeting

Carleton University

Provided By

UNT Libraries

The UNT Libraries serve the university and community by providing access to physical and online collections, fostering information literacy, supporting academic research, and much, much more.

Degree Information

Department: UNT Libraries

Description

Presented at Data Power 2017. This presentation describes the vision for a cooperative of stakeholder institutions called the Publishing Analytics Data Alliance.

Physical Description

17 p.

Notes

Description: Both for-profit and not-for-profit organizations increasingly use big data not only to study what has happened (data analytics) but also to make predict future trends (predictive analytics). With certain notable exceptions (student recruitment in US institutions and compulsive evaluations of research productivity in the UK and Australia), academia has generally lagged behind other sectors in its use of big data.

One domain that has moved halfway into collecting and analyzing big data is scholarly publishing, whose stakeholders of varying size include libraries and other research institutions, learned societies, for-profit publishers, and not-for-profit publishers. These stakeholders generate and collect various types of data, especially relating content usage and sales, but often lack both resources to explore the data and ways to compare their data with that of other stakeholders. The situation is not one where a market participant tries to acquire competitive intelligence to help them compete against others; rather, because the stakeholders are so tightly related, they nearly all have some sort of data that would help all of them function more efficiently. Unfortunately, the challenges associated with gathering, integrating, interpreting, and reporting usage data limit the ability of individual publishers, libraries, and other stakeholders to identify—much less predict—important usage trends and opportunities through which these organizations might extend their impact.

At the same time, there are real concerns about ownership of, access to, and analysis of data for "predictive bibliometrics". Furthermore, while all stakeholders would like to have rich data and be able to carry out predictive analytics of some sort, the high cost of providing or purchasing data-related services risks reinforcing inequalities in the landscape of scholarly publishing.

This paper presents a vision for a cooperative of stakeholder institutions called the Publishing Analytics Data Alliance. Member institutions will contribute data that they gather about scholarly publishing to the cooperative, which will normalize and aggregate data for exploration by its members, who will be able to see their data in the context of their peers. The cooperative's members, through a system of shared governance, will also establish an ethical framework governing the functionality of the cooperative's data services and, more generally, the use of data by members.

Beyond shared governance, the pooling of resources by the cooperative offers a way for members to achieve more than they would be able to on their own—namely, to explore and analyze data about scholarly publishing. It is hoped that the cooperative will lead to increased cooperation and efficiency in the scholarly publishing ecosystem, all the while addressing ethical concerns raised by the power of data.

Subjects

Keywords

Source

Data Power 2017, June 22-23, 2017. Ottawa, Ontario, Canada.

Language

English

Item Type

Presentation

Identifier

Unique identifying numbers for this presentation in the Digital Library or other systems.

Archival Resource Key: ark:/67531/metadc987487

Relationships

"The Case for a Publishing Analytics Data Alliance," ark:/67531/metadc944385
Approaches to Tracking the Impacts of Library- and Press-published Monographs: Project Meerkat - ark:/67531/metadc1164558
A cooperative for big data in scholarly publishing - ark:/67531/metadc991052

Collections

This presentation is part of the following collection of related materials.

UNT Scholarly Works

Materials from the UNT community's research, creative, and scholarly activities and UNT's Open Access Repository. Access to some items in this collection may be restricted.

Related Items

The Case for a Publishing Analytics Data Alliance (Presentation)

This presentation discusses Project Meerkat, a project aimed “to develop guidelines and standards for digital scholarly monograph usage data and to construct a neutral organizational apparatus for the ongoing collection and aggregation of data about these scholarly publications,” and the resulting cooperative to be developed out of that project, the Publishing Analytics Data Alliance.

Relationship to this item: (Is Version Of)

"The Case for a Publishing Analytics Data Alliance," ark:/67531/metadc944385

Approaches to Tracking the Impacts of Library- and Press-published Monographs: Project Meerkat (Presentation)

Slides presented during the panel “Approaches to Tracking the Impacts of Library- and Press-published Monographs” at the Library Publishing Forum 2018. This presentation describes the impetus behind Project Meerkat, a publishing analytics data alliance.

Approaches to Tracking the Impacts of Library- and Press-published Monographs: Project Meerkat - ark:/67531/metadc1164558