The data that is generated during research is important, but sadly it is often hard to unearth, and there are many challenges around getting the appropriate credit to go to the researchers who make data available.
Another key issue with research data is that it is often expensive to produce, and without good visibility on data as an output it can often end up unloved and can be lost over time. (If even just one research group reuses a data set, the effective utility to the research community of that data set doubles).
On September 4 New York University’s Coleridge Initiative announced a ‘Rich Text Competition’ that has the potential to really make a positive of some of these problems: a competition for researchers to build tools to help automate the discovery of data sets in the social sciences.
The competition comes with prizes of $2,000 to each of the finalists, with up to $20,000 to be awarded to the winning team. The Schmidt Family Foundation, Overdeck Family Foundation, and Alfred P. Sloan Foundation are funding the effort.
Participants should use any combination of machine learning and data analysis methods to identify the datasets used in a corpus of social science publications and infer both the scientific methods and fields used in the analysis and the research fields.
The deadline for initial applications is September 30. For more information, click here.