The usage of densely interconnected data is rapidly proliferating in a variety of contexts, be it in the development of semantic web technologies relying on linked data, the advent of (social) network infrastructures integrating highly heterogeneous information, or the curation of scientific datasets, capturing complex models. To address the need to efficiently manage such data, graph databases -- a novel type of NoSQL stores leveraging the property graph data model -- have recently been developed. This talk will give a general overview of foundational aspects related to the scalable and reliable processing of graph-shaped data.
Stefania Dumbrava is an Associate Professor (Maître de Conférences) position at the École Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE) and at the SAMOVAR research laboratory of Institute Polytechnique de Paris. She received a Ph.D in Computer Science from Paris-Saclay University in 2016 for her work on building correct-by-construction database engines using the Coq proof assistant. Her current research targets the application of formal methods techniques to the principled design of languages, systems, and algorithms, capable of handling large-scale, interconnected, semi-structured data.