NEDB Day 2026

The ODIn Lab will be at NEDB_Day_2026 on Jan 16 with two posters!

"Flow-centric Query Evaluation Pipelines" (Victoria, Andrew, Krishna) presents our preliminary efforts to make a scheduler-friendly query evaluation pipeline for our #Draupnir datalog engine. The key insight behind our work is decoupling state from operators. By making operators (mostly) stateless, we can inline better, and we can expose IO to the scheduler more efficiently.

"Benchmarking Tabular Representation Models on Longitudinal Data" (Pratik) presents our work on data integration for longitudinal studies. Longitudinal studies generate a slew of datasets that are almost alike, but not quite. Coupled with the fact that attributes are identified by prose questions rather than simple identifiers, they aren't a great fit for existing data integration/unionability tools. We'll specifically be presenting a benchmark, painstakingly adapted from the American National Election Survey, which shows that we need new data integration tools.