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Selected Readings on Data Collaboratives

April 14, 2017 by Andrew Young, Stefaan Verhulst

 

The term data collaborative refers to a new form of collaboration, beyond the public-private partnership model, in which participants from different sectors (including private companies, research institutions, and government agencies) exchange data to create new public value and solve public problems. Several of society’s greatest challenges — from addressing climate change to public health to job creation to improving the lives of children — require greater access to data, more collaboration between public – and private-sector entities, and an increased ability to analyze datasets. In the coming months and years, data collaboratives will be essential vehicles for harnessing the vast stores of privately held data toward the public good.

The pieces collected here examine a number of elements related to this emerging field – from the potential (or realized) societal benefits of data collaboratives, to issues of governance and incentives for corporations to participate in such arrangements, to risks and strategies for mitigating them. To learn more about data collaboratives, check out DataCollaboratives.org

Selected Readings

Big data and positive social change in the developing world: A white paper for practitioners and researchers

Collaborative Governance in Theory and Practice

Chris Ansell Alison Gash

Methodology Conceptual Framework

Data Sharing for Public Health Key Lessons from Other Sectors

Matthew Brack Tito Castillo

A Decision Model for Data Sharing

Methodology Conceptual Framework

Sea Change in Open Science and Data Sharing Leadership by Industry

Krumholz HM Gross CP Blount KL Ritchie JD Hodshon B Lehman R Ross JS

Private Data and the Public Good

Gideon Mann

Methodology Conceptual Framework

Open data partnerships between firms and universities: The role of boundary organizations

M. Perkmann H. Schildt

Objective

Sharing Data Is a Form of Corporate Philanthropy

Matt Stempeck

Methodology Conceptual Framework

The data revolution: finding the missing millions

Elizabeth Stuart Emma Samman William Avis Tom Berliner

Is bigger better? The emergence of big data as a tool for international development policy

Linnet Taylor Ralph Schroeder

Objective Big Data
Type

A systematic review of barriers to data sharing in public health

Willem G. van Panhuis Proma Paul Claudia Emerson John Grefenstette Richard Wilder Abraham J. Herbst David Heymann Donald S. Burke

Methodology Conceptual Framework
Objective

Mapping the Next Frontier of Open Data: Corporate Data Sharing

Stefaan Verhulst David Sangokoya

Methodology Case Studies

Data Collaboratives: Exchanging Data to Improve People’s Lives

Stefaan Verhulst David Sangokoya

Open Data and Beyond

F Welle Donker B. van Loenen A. K. Bregt

Methodology Case Studies

Data-driven development: pathways for progress

Methodology Conceptual Framework
Objective Big Data