Data Pools

Posted: 11 Oct 2015 Last revised: 1 Mar 2017

Michael Mattioli

Indiana University Maurer School of Law

Date Written: August 1, 2016

Abstract

American innovation policy as expressed through intellectual property law contains a curious gap: it encourages individual research investments, but does little to facilitate cooperation among inventors, which is often a necessary precondition for innovation.

This Article provides the first in-depth analysis of a policy problem caused by this gap: increasingly, public and private innovation investments depend upon the willingness of private firms to cooperatively pool industrial, commercial, and scientific data. Data holders often have powerful disincentives to cooperate with one another, however. As a result, important research that the federal government has sought to encourage through intellectual property policy and through targeted investments is being held back.

This Article addresses this problem by offering three new contributions — one theoretical, one empirical, and one prescriptive. The theoretical contribution synthesizes legal, economic, and public choice literature to explain why data- pooling is relevant to federal policies designed to promote innovation, and why theory suggests it will fail due to collective- action problems. The discussion provides a conceptual framework for scholars and policymakers to understand how data-pooling problems can subvert innovation policy goals.

This leads to the second contribution: the first ethnographic study of private efforts to pool data. Interviews with lawyers, executives, and scientists working at the vanguard of “Big Data” projects in the field of cancer research offer a detailed view of how, precisely, data-pooling problems are hindering technological progress in an important field of research. The study’s most important finding is that impediments to the pooling of patient treatment and clinical trial data are diverse, nuanced, and not neatly reducible to simple the free-rider dilemmas widely predicted by legal scholars and economists.

These findings lead to the third key contribution: a set of targeted policy recommendations designed to facilitate data-pooling through FDA and FTC regulations, amendments to federal healthcare legislation, and tax incentives. These prescriptive measures are tailored to address the sharing of health-related data, but they capture an approach that can be applied in other settings where technological progress depends upon data-pooling. Ultimately, this Article argues for a new vision of innovation policy in which cooperative exchanges of data are regarded as important preconditions for innovation that often require government support.

Keywords: big data, data pools, data pooling, data-intensive science, intellectual property, collective action, innovation policy, innovation theory, information transactions, information exchange, innovation, health data, cancer treatment

JEL Classification: O34, D45, O31, O32,

Suggested Citation

Mattioli, Michael, Data Pools (August 1, 2016). Berkeley Technology Law Journal, Vol. 32, No. 2, 2017 Forthcoming. Available at SSRN: https://ssrn.com/abstract=2671939

Michael Mattioli (Contact Author)

Indiana University Maurer School of Law ( email )

211 S. Indiana Avenue
Bloomington, IN 47405
United States

Paper statistics

Abstract Views
466