The Virtual Data Center

R in social sciences, and in academia in general, increasingly rely on large quantities of numeric data. The analysis of such data appears in professional journals, scholarly books, and more and more often, popular media. For the scholar, the connection between research articles and data is natural. We analyze data and publish results. We read the results of other analyses, learn from them, and move forward with our own research. But these connections are sometimes difficult to make. Data supporting an article are often difficult to find and even more difficult to analyze. Archiving, disseminating, and sharing data is crucial to research but is often costly and difficult (Sieber, 1991). Consequently, our ability to replicate the work of others and to build on it is diminished. Researchers, university data centers, and students all face challenges when trying to find and use quantitative research data.

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