We continue our series of team seminars with Dr. Christos Koutras, a Postdoctoral Research Associate at NYU. Christos will present his work on data discovery, focusing on his recent VLDB publication: “OmniMatch: Joinability Discovery in Data Products”.
The seminar will take place on Tuesday 9th of September, 10:00 – 11:00, at the Henri Poincaré room (Turing Building, RDC).
You can find a short bio of Christos and the abstract of the talk below.
Bio:
Christos Koutras is a Postdoctoral Research Associate at the Visualization and Data Analytics Research Center of the NYU Tandon School of Engineering. He has obtained his PhD from the Web Information Systems group of the Faculty of Engineering, Mathematics and Computer Science at Delft University of Technology, where he was supervised by Asterios Katsifodimos. His research focuses on data integration, and specifically schema matching, data discovery, and metadata generation.
Abstract:
A data product is a collection of data assets (e.g., tables) organized under a business context to provide structured, accessible data for specific use cases. A fundamental attribute of a well-organized data product is metadata about joinability across datasets. Joinability metadata plays a vital role in facilitating the exploration and exploitation of datasets. In this talk, I will speak about OmniMatch, a novel self-supervised approach that targets the problem of joinability discovery in data products. I will briefly describe how OmniMatch effectively addresses issues associated with existing joinability discovery methods, discuss insights, and propose future directions in the field.
Looking forward to seeing you there.
