Research

Motivation

Our societies produce knowledge and data at an ever increasing pace. These knowledge and data are generated in an independent manner by autonomous individuals or companies. They are heterogeneous and their joint exploitation requires connecting them.

However, data and knowledge have to evolve, facing changes in what they represent, changes in the context in which they are used and connections to new data and knowledge sources. These sources are currently mostly maintained by hand. As they grow and get more interconnected, this becomes less sustainable. But if knowledge does not evolve, it will freeze leading to sure obsolescence [Euzenat2020a].

Beyond the production of knowledge on the semantic web and linked data, this problem applies to any domain in which knowledge is produced in a way usable by computers. For instance, smart cities or the internet of things produce a wealth of changing data. The knowledge about this data has to evolve continuously to remain up-to-date as new data sources are encountered and conditions are changing. Knowledge must evolve organically with the life of its users.

This problem lies in the lack of autonomous evolution of heterogeneous knowledge. No one waits for knowledge to be perfect before using it and agents and societies cannot be interrupted for upgrading their knowledge. Hence, knowledge has to be situated, i.e. considered with respect to its use (called situation), and evolve continuously, i.e. without interruption.

Summary of research results

Further readings

Initial project proposal (2016): pdf

Synthesis report: 2016-2019

Activity report 2017: pdf, html; 2018: pdf, html; 2019: pdf, html; 2020: pdf, html; 2021: pdf, html; 2022: pdf

Publications: our paper section (from which references are taken)

Courte introduction en Fran├žais: Bulletin de l'AFIA 105:40-43, 2019

mOeX is building on top of the results of the Exmo project whose pages may provide some background information on previous work.