of data in standardized formats, researchers in other disciplines that are generating large datasets, such as those resulting from brain imaging or gene and protein expression studies, have yet to agree on standards for when and how to share, format, annotate, and curate data.
The time, effort, and expense involved in generating large datasets, databases, and some research materials have been cited as arguments for restricting access to them. In the case of databases, unrestricted sharing is considered especially problematic because U.S. law does not provide intellectual property protection for databases (see Box 3–1). Any enterprise that produces large databases may be reluctant to share it without restrictions on initial publication, inasmuch as doing so may mean giving up a substantial commercial advantage and could enable the wholesale copying of databases by others for commercial purposes.
Other emerging challenges in publication-related sharing arise from practices related to software and algorithms. These are becoming more common as the subject of publications in the life sciences. Software developers have long disagreed about whether the source code needed for a published program or algorithm should be made available to everyone, and life scientists who develop software are no exception. One reason for the debate is that although software can be copyrighted, it can be difficult in practice to prevent someone else from copying and quickly modifying the source code and taking the lead in commercializing it. And some have argued that mandatory sharing of source code prevents universities from exercising their legal right to develop commercial products from federally funded research.
In the workshop’s keynote presentation, Eric Lander, director of the Whitehead Institute Center for Genome Research, reviewed some of the many contentions that are shaping the debate over sharing of data and materials associated with publications and the related topic of public-domain resources. “These are hard arguments to weigh in the absence of an intellectual framework for evaluating them,” he said. “I think our goal is to step back and ask, ‘What is the intellectual framework in which we can parse these arguments?’” The following chapter examines such a framework.