The licenses developed by Creative Commons have become an essential set of tools to patch gaps in the international system of copyright, creating a parallel, opt?in intellectual property regime that doesn't require country?by?country legislative change to implement. With those licenses fairly well integrated into modern practice, Creative Commons is embarking on a year?long process of strategic planning to determine where and how they can best have an impact in new areas, including science. This grant provides partial support to Creative Commons as it undertakes this process. Funds will augment a November meeting focused on "open science" and nine months of subsequent work on three key themes: licenses for open-access scholarship, legal and technical infrastructure for open data sharing, and the role of patent licensing in science.

Funds from this grant to information scientist Christine Borgman and anthropologist Sharon Traweek at the University of California, Los Angeles support a robust, three-year ethnographic research program to study scientific data practices and develop recommendations about needed skills and relationships within scientific teams who collect and manage data. Borgman, Traweek and their research group will will carry out an ambitious "2x2" research program, comparing projects that produce large volumes of homogeneous data with those involving smaller amounts of heterogeneous data as well as projects at earlier and later stages of their life cycles. The four sites to be studied include the Dataverse Network at Harvard, the Center for Embedded Network Sensing, a new National Science Foundation (NSF)-funded center for data-driven science and the transfer of the Sloan Digital Sky Survey data from Fermilab to long-term homes at Johns Hopkins and Princeton. The research will help develop a better knowledge about existing data practices in modern science, inform future infrastructure investments, and clarify new roles around issues like data curation.

In a poll conducted by Science in 2011, scientists across disciplines were asked, "Where do you archive most of the data generated in your lab or for your research?" More than 50% responded "in our lab." While fine for short-term research needs, this "data under the desk" scenario poses real risks for the long-term utility and reproducibility of research. One way of improving this situation and getting more data under safer cover is to develop data management solutions that directly address the immediate needs of researchers while allowing the delegation of data curation functions like preservation and archiving. This grant supports a focused, iterative development process by DuraSpace to design, build, and release such a system.

Access to some datasets is justifiably restricted for legal, ethical, or business reasons. The existence of such datasets presents an opportunity for the smart application of technology that permits aggregate statistical or computational research on the data without violating the constraints that prevent full access. This grant to researcher Beth Plale at Indiana University, supports a collaborative project with the Hathi Trust, holder of over 8.5 million digitized print works, to address the immense technical and theoretical issues involved in designing digital methods for mining data from in-copyright materials that respect current legal restrictions governing access to such works. Plale's team will develop a secure computing environment that will enable researchers to bring their own algorithms and tools to bear on Hathi's full?text digitized corpus, while at the same time limiting the ability of that software (or researchers) to access the work in a way that runs afoul of copyright law.

Raw data needs preparation to be useful for research. In some cases, what is needed is cleanup and normalization; in others, tagging or categorizing dataset elements. Depending on the domain and kind of data, computers can do much of the necessary work, but some tasks, due to fuzziness or complexity in the data, are currently beyond the bounds of computation. Much data prep requires human eyes, human minds, human judgment, and human labor, a daunting demand when the size of many modern scientific datasets is measured in terabytes. The Zooniverse project, an international effort initially based at Oxford University and now housed primarily at the Adler Planetarium in Chicago, offers a straightforward solution to this problem: divide the work into very granular tasks, gather a large crowd of science enthusiasts, and let them loose on the data. "Galaxy Zoo," the first Zooniverse initiative, asked participants to view images of galaxies collected by the Sloan Digital Sky Survey and to categorize their shapes, successfully engaging 130,000 participants who performed over 100 million distinct classifications. Subsequent projects have expanded the Zooniverse strategy into other scientific domains, asking volunteers, in one case, to help reconstruct historical climate data by entering records from the digitized images of ship logbooks. Funds from this two-year grant will support the extension of the Zooniverse platform into new mechanics beyond image classification (for example, sound classification of whale songs, or tagging of species from video feeds), outreach efforts to identify scientific datasets that might be usefully improved through tapping Zooniverse volunteers, and activities to engage the large and growing community of the citizen scientists that participate in Zooniverse projects.