The Journey to R4D: An institutional history of an Australian Initiative on Food Security in Africa

Internal Revie

Harnessing and Sharing the Benefits of State Sponsored Research

In recent years data-sharing has been a recurring focus of struggle within the scientific research community as improvements in information technology and digital networks have expanded the ways that data can be produced, disseminated, and used. Information technology makes it easier to share data in publicly accessible archives that aggregate data from multiple sources. Such sharing and aggregation facilitate observations that would otherwise be impossible. But data disclosure poses a dilemma for scientists. Data have long been the stock in trade of working scientists, lending credibility to their claims while highlighting new questions that are worthy of future research funding. Some disclosure is necessary in order to claim these benefits, but data disclosure may also benefit one\u27s research competitors. Scientists who share their data promptly and freely may find themselves at a competitive disadvantage relative to free riders in the race to make future observations and thereby to earn further recognition and funding. The possibility of commercial gain further raises the competitive stakes. This article discusses data sharing in California\u27s stem cell initiative against the background of other data sharing efforts and in light of the competing interests that the California Institute for Regenerative Medicine (CIRM) is directed to balance. We begin by considering how IP law affects data-sharing. We then assess the strategic considerations that guide the IP and data policies and strategies of federal, state, and private research sponsors. With this background, we discuss four specific sets of issues that public sponsors of data-rich research, including CIRM, are likely to confront: (1) how to motivate researchers to contribute data; (2) who may have access to the data and on what conditions; (3) what data get deposited and when do they get deposited; and (4) how to establish database architecture and curate and maintain the database

Research Data: Who will share what, with whom, when, and why?

The deluge of scientific research data has excited the general public, as well as the scientific community, with the possibilities for better understanding of scientific problems, from climate to culture. For data to be available, researchers must be willing and able to share them. The policies of governments, funding agencies, journals, and university tenure and promotion committees also influence how, when, and whether research data are shared. Data are complex objects. Their purposes and the methods by which they are produced vary widely across scientific fields, as do the criteria for sharing them. To address these challenges, it is necessary to examine the arguments for sharing data and how those arguments match the motivations and interests of the scientific community and the public. Four arguments are examined: to make the results of publicly funded data available to the public, to enable others to ask new questions of extant data, to advance the state of science, and to reproduce research. Libraries need to consider their role in the face of each of these arguments, and what expertise and systems they require for data curation.

Enabling Entrepreneurial Ecosystems

Inspired by research on the importance of entrepreneurship for sustained economic growth and improved wellbeing, many governments and non-governmental grantmaking organizations have sought over the past decade to implement policies and programs intended to support entrepreneurs. Over this interval, growing appreciation of the limits of strategies focused narrowly on financing or training entrepreneurs has prompted a number of such entities to shift their efforts toward more broadbased strategies aimed at enabling "entrepreneurial ecosystems" at the city or sub-national regional scale.This paper takes the metaphor of the "ecosystem" seriously, seeking to draw lessons from evolutionary biology and ecology to inform policy for entrepreneurship. In so doing, the paper provides a framework for data gathering and analysis of practical value in assessing the vibrancy of entrepreneurial ecosystems

Open Data, Grey Data, and Stewardship: Universities at the Privacy Frontier

As universities recognize the inherent value in the data they collect and hold, they encounter unforeseen challenges in stewarding those data in ways that balance accountability, transparency, and protection of privacy, academic freedom, and intellectual property. Two parallel developments in academic data collection are converging: (1) open access requirements, whereby researchers must provide access to their data as a condition of obtaining grant funding or publishing results in journals; and (2) the vast accumulation of 'grey data' about individuals in their daily activities of research, teaching, learning, services, and administration. The boundaries between research and grey data are blurring, making it more difficult to assess the risks and responsibilities associated with any data collection. Many sets of data, both research and grey, fall outside privacy regulations such as HIPAA, FERPA, and PII. Universities are exploiting these data for research, learning analytics, faculty evaluation, strategic decisions, and other sensitive matters. Commercial entities are besieging universities with requests for access to data or for partnerships to mine them. The privacy frontier facing research universities spans open access practices, uses and misuses of data, public records requests, cyber risk, and curating data for privacy protection. This paper explores the competing values inherent in data stewardship and makes recommendations for practice, drawing on the pioneering work of the University of California in privacy and information security, data governance, and cyber risk.Comment: Final published version, Sept 30, 201

Rethinking Novelty in Patent Law

The novelty requirement seeks to ensure that a patent will not issue if the public already possesses the invention. Although gauging possession is usually straightforward for simple inventions, it can be difficult for those in complex fields like biotechnology, chemistry, and pharmaceuticals. For example, if a drug company seeks to patent a promising molecule that was disclosed but never physically made in the prior art, the key possession question is whether a person having ordinary skill in the art (PHOSITA) could have made it at the time of the prior disclosure. Put differently, could the PHOSITA rely on then-existing knowledge in the field to fill in any missing technical details from the prior disclosure? This Article argues that existing novelty jurisprudence mishandles the possession question in two ways. First, it tends to overestimate the PHOSITA\u27s then-existing knowledge by failing to fully appreciate the complex nature of certain technologies. Second, the current examination framework vitiates the presumption of novelty by placing proof burdens on the would-be inventor that can thwart innovation and frustrate important objectives of the patent system. To resolve these problems and to fill a gap in patent scholarship, this Article proposes a new paradigm that reframes the novelty inquiry during patent examination. Its implementation will not only improve the quality of issued patents, but also make the patent literature a more robust source of technical information. This Article contributes to broader policy debates over patent reform and joins a larger effort to bridge the disconnect between patent law and the norms of science

Autism research : An objective quantitative review of progress and focus between 1994 and 2015

The nosology and epidemiology of Autism has undergone transformation following consolidation of once disparate disorders under the umbrella diagnostic, autism spectrum disorders. Despite this re-conceptualization, research initiatives, including the NIMH's Research Domain Criteria and Precision Medicine, highlight the need to bridge psychiatric and psychological classification methodologies with biomedical techniques. Combining traditional bibliometric co-word techniques, with tenets of graph theory and network analysis, this article provides an objective thematic review of research between 1994 and 2015 to consider evolution and focus. Results illustrate growth in Autism research since 2006, with nascent focus on physiology. However, modularity and citation analytics demonstrate dominance of subjective psychological or psychiatric constructs, which may impede progress in the identification and stratification of biomarkers as endorsed by new research initiatives.Peer reviewedFinal Published versio