Draft 3 August 2010 Jorge L

DATA SHARING, LATENCY VARIABLES AND THE SCIENCE COMMONS Draft 3 August 2010 Jorge L. Contreras* ABSTRACT Over the past decade, the rapidly decreasing cost of computer storage and the increasing prevalence of high-speed Internet connections have fundamentally altered the way in which scientific research is conducted. Led by scientists in disciplines such as genomics, the rapid sharing of data sets and cross-institutional collaboration promise to increase scientific efficiency and output dramatically. As a result, an increasing number of public “commons” of scientific data are being created: aggregations intended to be used and accessed by researchers worldwide. Yet, the sharing of scientific data presents legal, ethical and practical challenges that must be overcome before such science commons can be deployed and utilized to their greatest potential. These challenges include determining the appropriate level of intellectual property protection for data within the commons, balancing the publication priority interests of data generators and data users, ensuring a viable economic model for publishers and other intermediaries and achieving the public benefits sought by funding agencies. In this paper, I analyze scientific data sharing within the framework offered by organizational theory, expanding existing analytical approaches with a new tool termed “latency analysis.” I place latency analysis within the larger Institutional Analysis and Development (IAD) framework, as well as more recent variations of that framework. Latency analysis exploits two key variables that characterize all information commons: the rate at which information enters the commons (its knowledge latency) and the rate at which the knowledge in the commons becomes be freely utilizable (its rights latency). With these two variables in mind, one proceeds to a three-step analytical methodology that consists of (1) determining the stakeholder communities relevant to the information commons, (2) determining the policy objectives that are relevant to each stakeholder group, and (3) mediating among the differing positions of the stakeholder groups through adjustments to the latency variables of the commons. I apply latency analysis to two well-known narratives of commons formation in the sciences: the field of genomics, which developed unique modes of rapid data sharing during the Human Genome Project and continues to influence data sharing practices in the biological sciences today; and the more generalized case of open access publishing requirements imposed on publishers by the U.S. National Institutes of Health and various research universities. In each of these cases, policy designers have used timing mechanisms to achieve policy outcomes. That is, by regulating the speed at which information is released into a commons, and then by imposing time-based restrictions on its use, policy designers have addressed the concerns of * Deputy Director of Intellectual Property Programs and Senior Lecturer in Law, Washington University in St. Louis. The author wishes to thank the following for their thoughtful comments on earlier drafts of this paper: Sara Bronin, Rebecca Eisenberg, Terry Fisher, Charlotte Hess, Kimberly Kaphingst, Michael Madison, Charles McManis, Ruth Okediji, the participants in the 2009 SALT Junior Faculty Development Workshop, the 2010 Junior Scholars in Intellectual Property (JSIP) workshop and the 2010 Intellectual Property Scholars Conference (IPSC), and my research assistant Jeff Johnson. Draft – Not for citation or distribution 2 LATENCY ANALYSIS [Draft 3 August 2010] multiple stakeholders and established information commons that operate effectively and equitably. I conclude that the use of latency variables in commons policy design can, in general, reduce negotiation transaction costs, achieve efficient and equitable results for all stakeholders, and thereby facilitate the formation of socially-valuable commons of scientific information. CONTENTS INTRODUCTION I. INFORMATION AND SCIENCE COMMONS A. Commons Theory Background 1. Physical Resource Commons 2. Commons of Information B. The Temporal Dimension of Information Commons 1. Dynamic and Static Commons 2. Knowledge, Rights and Timing in Information Commons a. The Dynamic Character of Information Commons b. The Changing Bases of Knowledge and Rights in an Information Commons 3. A Proposed Latency Analysis for Information Commons. a. Knowledge Latency b. Rights Latency c. Latency Analysis d. Implementing Latency Analysis in Commons Design II. COMMONS IN THE SCIENCES A. Constructing Science Commons 1. Incentives to Share 2. Modes of Data Sharing 3. Stakeholders and Policy Considerations B. Exogenous Influences on Latencies within a Science Commons 1. Publication Delay 2. Copyright and Other Restraints on the Dissemination of Data 3. Patents and Restraints on the Use of Data a. Effect of Patents on Scientific Data b. Patents and Latency c. Patents and Anticommons Draft – Not for citation or distribution 3 LATENCY ANALYSIS [Draft 3 August 2010] III. TIMING AND DATA SHARING: TWO CASE STUDIES A. The Genome Commons 1. Development of Genomics Data Release Policies a. The Human Genome Project (HGP) b. The Bermuda Principles c. Bermuda, Data Release and Patents d. Growing Tension Between Data Generators and Users e. GWAS and Embargo Policies f. Private Sector Policies B. Scientific Publishing 1. Scientific Publishing and the Open Access Debate 2. Open Access and Government-Funded Research 3. Alternative Open Access Models IV. APPLYING THE LATENCY FRAMEWORK A. Latency in the Genome Commons 1. Stakeholders and Policy Design Considerations 2. Latency as a Policy Design Tool – Retention versus Embargo B. Latency and Scientific Publishing 1. Stakeholders and Policy Design Considerations 2. Compromises Effected Through Latency Choices C. Synthesis and Broader Applications CONCLUSION INTRODUCTION The fossilized remains of ardipithecus ramidus (“Ardi”) an early human ancestor and important evolutionary link, were unearthed in 1992 by archeologists from the University of California - Berkeley and the University of Tokyo. The scientists published their initial findings in 1994 to great acclaim,1 but did not release detailed data about the fossils until 2009,2 seventeen years after the initial discovery. The extreme length of this delay, justified by the researchers as necessary due to the fragile condition of the remains and the difficulty of 1 Tim D. White, et al., Australopithecus ramidus, a New Species of Early Hominid from Aramis, Ethiopia, 371 NATURE 306 (1994). See also John Noble Wilford, Fossil Find May Show if Prehuman Walked, N.Y. TIMES (Feb. 21, 1995) (calling a. ramidus “potentially the most significant discovery in early human studies since the Lucy fossils in 1974”). 2 Tim D. White, et al., Ardipithecus ramidus and the Paleobiology of Early Hominids, 326 SCIENCE 65 (2009). Draft – Not for citation or distribution 4 LATENCY ANALYSIS [Draft 3 August 2010] extracting and reassembling them, has nevertheless been widely criticized as contrary to the practice of “open science.”3 Data is the currency of science, and the sharing of data is fundamental to the scientific enterprise.4 Since the emergence of modern scientific practice, scientists have published their observations and experimental data to earn professional recognition, to permit verification of their theories and to further the overall progress of science.5 Today, powerful database and networking technologies have enabled the dissemination of data on a scale not imaginable just a few decades ago. Developed primarily by government-funded research projects, vast collections of publicly-accessible6 data now exist in fields such as chemistry7, meteorology8, geophysics9, astronomy,10 paleontology11 and, as will be discussed below, molecular biology and genomics.12 3 See, e.g., Editorial, Fossils for All: Science Suffers by Hoarding,SCIENTIFIC AMERICAN (Aug. 24, 2009) (“fossil hunters often block other scientists from studying their treasures, fearing assessments that could scoop or disagree with their own. In so doing, they are taking the science out of paleoanthropology”) and Joel Achenbach, Ancient Skeleton Could Rewrite the Book on Human Origins,WASH. POST (Oct. 2, 2009) (noting “impatience” in the scientific community while waiting for the Ardi data). 4 See Yochai Benkler, Commons-Based Strategies and the Problems of Patents, 305 SCIENCE 1110, 1110 (2004) and JOHN M. ZIMAN, PROMETHEUS BOUND: SCIENCE IN A DYNAMIC STEADY STATE 40 (1994). In this context, I (and most other commentators) use the term “science” to refer to “basic” research, or the investigation of fundamental natural laws and properties, rather than applied research or technology development that is directed to commercial application. See, e.g., ZIMAN, supra, at 24-26 and Richard R. Nelson, The Simple Economics of Scientific Research, 67 J. POLITICAL ECONOMY 297, 300-01 (1959) (each discussing the imprecise line between basic and applied research). The norms of openness that apply to basic research do not necessarily apply to these later categories of investigation, and many of these are, quite naturally, conducted by corporate and industrial concerns in secret. See, e.g., Arti Kaur Rai, Regulating Scientific Research: Intellectual Property Rights and the Norms of Science, 94 NW. U. L. REV. 77, 93 (1999) 5 See discussion at Part II.A, infra, and Robert K. Merton, The Normative Structure of Science (1942) in THE SOCIOLOGY OF SCIENCE 267-78 (Norman W. Storer, ed., 1973). Merton famously

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