Open Data and the Danger of Sympathetic Magic
This chapter provides a minimal normative framework for discussing the desired attributes of a published dataset using Lakatos’ philosophy of science and the metaphor of sympathetic magic. When researchers publish their results, journals and granting agencies increasingly want datasets opened alongside. These datasets may vary in quality, reusability, and comprehensiveness. Yet, without a clear knowledge of how the research methodology and analysis affects the production of the raw data, any future attempts to reproduce analysis will produce the same magical results only by following the same steps. While the requirement for Open Data in government funded research can provide an excellent basis for future research, not all Open Data is created equal. Releasing the methods of analysis alongside a dataset of high quality will also allow for lower technical difficulties when reusing or remixing the data. Then data, collected once, may be reused in multiple projects for a significant research impact. And to some, we can show that data is, indeed, magic.