June 2nd, 2022
Freedom of the press is under threat worldwide, and the quality of information that people have access to is dangerously degraded, under the joint threat of non-democratic governments and fake information propagation. The press as an industry needs powerful data management tools to help them interpret the complex reality surrounding us.
Since 2018, I have been cooperating with journalists from Le Monde, France’s leading newspaper, in devising tools for analyzing large and heterogeneuos data sources that they are interested in. This research has been embodied in ConnectionLens, a graph ETL tool capable of ingesting heterogeneous data sources into a graph, enriched (with the help of ML methods) with entities extracted from data of any type. On such integrated graphs, we devised novel algorithms for keyword search, and combine them in more recent research with structured querying. The talk describes the architecture and main algorithmic challenges in building and exploiting ConnectionLens graphs, illustrated in particular on an application where we study conflicts of interest in the biomedical domain. This is joint work with A. Anadiotis, O. Balalau, H. Galhardas and many others. ConnectionLens Web site (papers+code): https://team.inria.fr/cedar/connectionlens/
This research has been funded by Agence Nationale de la Recherche AI Chair SourcesSay (https://sourcessay.inria.fr)
Bio:
Ioana Manolescu is a senior researcher at Inria Saclay and a part-time professor at Ecole Polytechnique, France. She is the lead of the CEDAR INRIA team focusing on rich data analytics at cloud scale. She is also the scientific director of LabIA, a program ran by the French government where AI problems raised by branches of the local and national French public administration are tackled by French research teams. She is a member of the PVLDB Endowment Board of Trustees, and has been Associate Editor for PVLDB, president of the ACM SIGMOD PhD Award Committee, chair of the IEEE ICDE conference, and a program chair of EDBT, SSDBM, ICWE among others. She has co-authored more than 150 articles in international journals and conferences and co-authored books on “Web Data Management” and on “Cloud-based RDF Data Management”. Her main research interests are algebraic and storage optimizations for semistructured data, in particular Semantic Web graphs, novel data models and languages for complex data management, data models and algorithms for fact-checking and data journalism, a topic where she is collaborating with journalists from Le Monde. She is also a recipient of the ANR AI Chair titled “SourcesSay: Intelligent Analysis and Interconnexion of Heterogeneous Data in Digital Arenas” (2020-2024).
