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

Anne LAURENT
Anne LAURENT
Head

 Alexandre BAZIN
Alexandre BAZIN
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 areas: Environment, Health, SHS, Finance, Digital forensic science

Staff

Nadine Jacquet, Assistant engineer, CNRS
Anne Laurent, University professor, UM
Alexandre Bazin, Senior Lecturer, UM
Arthur Michalland, engineer, CNRS
 

Associates and Students

Marwa Alali, Predimya
Deperias Kerre, CF

Regular Co-workers

Gwenaelle Donadieu, CDD Chercheur, CNRS
Bill Gates Happi Happi, Doctorant externe, IRD
Michel Sala, Invité longue durée Eméritat, UM

Regular collaborators 

Clément Jonquet (Mistea)
Pierre Larmande (IRD)