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WEB-CUBE Team: Fuzziness, Alignments, Data & Ontologies

Arnaud Castelltort
Head
Anne LAURENT
Deputy

WEB3 Team

WEB Architecture X WEB Semantic X WEB of Data = WEB-CUBE

team WEB3

The WEB³ team aims to work on the issues, scientific and technological obstacles underlying the Web. It works more particularly on the architectural issues of the web, to exploit and extend the protocols of representation and exchange of data and knowledge; to allow better understanding and better processing of information and data.

logo of LIRMM team named WEB3
The team’s work revolves around three major axes:
  • Web architectures
  • Semantic Web
  • Web of Data
The team is interested in fundamental topics (e.g., knowledge extraction, recommendation of datasets, alignment of ontologies, linking and merging of data, knowledge graphs, ontologies) but also in applications to many fields, in particular cultural heritage, health, finance, agronomy-environment and sociology. The specificity of the team is to address these three dimensions of the Web simultaneously.
Axis I: Web Architecture The objective is to take interest in architectural issues and the changes underlying the Web:
  • Challenges: those are related to modeling and data processing in the Web (graph-oriented knowledge representation & treatments), scalability, resilience, distributed processing, interoperability and the emergence of new architectures and paradigms.
  • Keywords: Web Oriented Architecture, Property Graphs, Scalability, Data Mesh, Databases & Fuzziness, D-APP/Blockchain
  • Key areas: Finance, Security, Digital forensic science, Health
  Axis II: Semantic Web The objective is to address the protocols and methods of representation and exchange of data and knowledge.
  • Challenges: those are linked to data binding, to the alignment of data and ontologies of different types (work on the entire cycle), to the extraction of knowledge (for example, in clinical data), to the challenges related to semantic annotation (relationship detection, disambiguation, use of learning methods)
  • Keywords: ontologies, knowledge graphs, ontology alignment, ontology-based services, text and graph embeddings
  • Key areas: social sciences (fact-checking, points of view, journalism), environment, agronomy, health, social networks, digital forensic science
  Axis III: Web of Data The objective of this axis is to allow a better understanding and better processing of data and information.
  • Challenges: those are related to the exploitation of web of data; approaching data lakes (data storage pending their use); the conservation of potentially relevant data, alone or in combination; interdisciplinary work (cognitive sciences, anthropology, history, law, evolution, etc.); data governance.
  • Keywords: Linked Open Data, Data Science, Data Lakes, Databases & Fuzziness, Property Graphs, NoSQL, FAIR Data, Blockchain, Applied machine learning
  • Key ares: Environment, Health, SHS, Finance, Digital forensic science

Staff
François Scharffe, Maître de conférences, UM
Arnaud Castelltort, Maître de conférences, UM
Anne Laurent, Professeur des universités, UM
Alexandre Bazin, Maître de conférences, UM
Michel Sala, Maître de conférences, UM
Konstantin Todorov, Maître de conférences, UM

Associates & Students
Anton Dolhopolov, UM
Baptiste Darnala, Elzeard
Salim Hafid, UM
Maman Sani Aboubacar Djibo, PRADEO
Gaoussou Sanou, UM

Regular Co-workers
Zohra Bellahsene, Invité longue durée Eméritat, UM
Syphax Bouazzouni, CDD Ingénieur-Technicien, UM