The unprecedented creation, use and share of data around the world has led to new applications and economic opportunities. This data is often large, complex, and heterogeneous at a schema and semantic level, and more or less structured. To bring more order, the World Wide Web consortium recommends sharing data as RDF graphs, which has been mostly adopted in the Open Data initiative, but many other formats are used in practice. In this talk, I will dive into the problem of modelling, integrating and exploring such data, with a focus on journalism and healthcare. First, I will discuss how to help non-IT users, such as journalists, to explore unknown semi-structured data they may want to work with. Next, I will discuss how to model and integrate heterogeneous healthcare data in order to facilitate their federated analysis, bringing new insights on some genetic rare diseases. I will also demonstrate the research prototypes that came out of those researches.
Bio: Nelly Barret is a postdoctoral researcher at DEIB (Information and Bioengineering department) at Politecnico di Milano (Italy) since April 2024. From 2021 to 2024, she pursued her PhD at Inria Saclay (France), under the supervision of Pr. Ioana Manolescu, on the topic “user-oriented exploration of semi-structured datasets”. She graduated from University of Lyon (France), where she obtained her Bachelor in computer science in 2018 and then her Master in 2020. Her research interests lie between heterogeneous data integration, databases and data management.
