Saturday, October 08, 2005

Bettinger, Keller and Roderick

Creating Infrastructure to Facilitate Data Use in Master’s Colleges and Universities

Chris Bettinger, Alex Keller and Andrew Roderick, San Francisco State University
Thursday, September 29, 2005, 10:00-10:45 am

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Technological innovation has ushered in an unprecedented expansion of social science data collection and dissemination. Because of these innovations, research and teaching now stands at the brink of a revolution in data usage that will fundamentally change how work is done in most social science disciplines. Doctoral Granting Institutions (DGIs) have played the leading role in this expansion, producing the bulk of social science data and dissemination tools; Masters level institutions (MLIs) have, for the most part, been consumers of this data with faculty constructing subsets of data for teaching and engaging in secondary data analysis. Thus while MLIs have been at the leading edge in open education endeavors, these endeavors have rarely been supported with leading edge technology. The above mentioned innovations open new opportunities at MLIs for leveraging technology in its open education efforts but formidable barriers need to be addressed if MLIs are to take full advantage of this brave new world.

DIVA is a hardware backbone and set of software tools that faculty can use to enhance course content with real social science data and make their efforts more accessible to students and other interested parties. The software is built in PHP5, thus making both content and software open. It includes a data manager who helps faculty but, more importantly, creates a data community of faculty who can mutually support one another in their various endeavors. DIVA reshapes MLIs ability to deliver education in four ways.

Using data across the disciplines: A convergence in data use has gained momentum over the last decade; in the future social science research will employ multiple methods as a matter of course.1 Because it handles the gamut of social science data types, DIVA software stands alone as a tool capable of facilitating the totality of multi-method research.

DIVA is the only repository of social science data that houses multiple forms of data.2 This is adecisive break from the parochial division of data that kept disciplines from fully exploring all dimensions of a given problem. Scholars expanding their vision of social research and crossing disciplinary lines have been hampered in their efforts by the fact that they go against the structure of academic research.3 Most major data repositories, for reasons of coherence, provide only one form of information.4 Most research support offi ces focus on a particular mode of research. But MLIs are faced with having to use multiple forms of data without the support faculty need from such research centers. DIVA changes this by providing the infrastructure that supports a disciplinary convergence in data use and cross-faculty communication.

Reducing data management: DGIs operate the major data repositories. Without exception, these data repositories are accompanied by centers for research support. Lacking the resources of DGIs, MLIs typically leave social science faculty to operate as their own research support. The data manager and data handling tools of DIVA provide a modest level of support though much of the burden is still on individual faculty. However, DIVA’ DIVAs software platform allows for much easier cataloging of data resources and supporting documents. As faculty create subsets of data for use in research and teaching, that data can be seen and used by other faculty if the creator so chooses. UCLA’ UCLAs Department of Statistics and the Interuniversity Consortium for Political and Social Research’s Site for Instructional Materials and Information are all crude examples of this idea. DIVA is more robust and easily managed than any of these extant systems. It permanently lowers the barrier to bringing original data into the classroom by providing instructors a wide gamut of data and supporting documents created by their colleagues.

Increasing collaboration: Collaboration between faculty is ubiquitous in social science. This past year, the majority of papers in the American Economic Review, the American Political Science Review, and the American Sociological Review were coauthored pieces, most often between faculty at different institutions. As we expand beyond the data terrain familiar to each of us, collaboration will increase as faculty lean towards working with others whose expertise complements their own. DIVA facilitates such collaboration. The data manager serves as a key player in putting faculty in contact with others who share similar substantive interests but have different methodological training. In the summers, faculty have the chance to meet like-interested researchers in the multiple open training workshops hosted by DIVA. Moreover, DIVA exposes faculty users to the work of other users; searching through its holdings is a tacit invitation to make contact with others.

Beyond serving as a conduit for making contact, DIVA software facilitates collaboration. Research teams or researcher-community collaborations can use it to create a common workspace accessible only to team members. The space can contain data files, notes, drafts of papers, and anything else that would need to be shared between team members. The researchers can access this data from any computer with an internet connection. Though common at DGIs, this capacity is absent from most MLIs, a pity given that MLIs do more work with the immediate community than do DGIs. The logistical nightmare of sharing in-progress work and common files simply disappears with DIVA.

Sharing and disseminating information: MLIs are increasingly commuter campuses. At this institution, for example, faculty and students generally prefer to work from home but are often forced to come to campus to use resources. DIVA liberates users from this constraint; its data is available from any computer with an internet connection. As long as a user has appropriate permissions, they can access data wherever and whenever needed. Future versions of DIVA will also allow access to data analysis software. DIVA will utterly change faculty and student work patterns, making their efforts more efficient and convenient.

DIVA’ DIVAs software improves how researchers share information with the public. Faculty can use the software to rapidly design websites containing data, reports, accompanying photos, and so forth for public or client consumption. Since there is no need for the faculty member to learn web publishing software, DIVA can serve as the dominant public face for research.


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