Background Info

For more details about Rich Context and other related research, see the white paper "Rich Context in the Administrative Data Research Facility".

The first iteration of the Rich Context Competition (during late 2018-early 2019) established the potential to apply the latest machine learning research toward search and discovery of research datasets. A book now in production — Rich Search and Discovery for Research Datasets: Building the next generation of scholarly infrastructure — summarizes that initial machine learning competition and approaches taken by leading teams, plus key takeaways.

This next (ongoing) iteration of the competition has been based on “state of the art” (SOTA) leaderboards that track ML research, such as NLP-progress and PapersWithCode.

Sponsors of this research include Schmidt Futures, the Eric and Wendy Schmidt Fund for Strategic Innovation, Overdeck Family Foundation, and the Alfred P. Sloan Foundation. We are grateful for support from partners in this research, including SAGE Publications, Digital Science, and Project Jupyter. Development of the corpus has assisted by USDA and Bundesbank.