The objective of the project is to study and develop methods for managing, integrating, and analyzing heterogeneous data, drawing on semantic modeling approaches tailored to modern information systems. The research focuses on designing mechanisms for structuring, organizing, and querying complex datasets—combining structured and unstructured sources—in a variety of digital environments.

Within this framework, the research aims to define operators and tools that facilitate the formulation and processing of queries based on natural-language descriptions, in order to improve access to information and large-scale data manipulation. Particular attention is paid to the consistency of the results produced, the robustness of the proposed methods, and the efficiency of the processing, so as to enable reliable use in data analysis contexts.

The research also includes the study of techniques for integrating data from multiple sources, as well as the development of methods for effectively leveraging large collections of information. The goal is to propose generic approaches that facilitate the organization, transformation, and analysis of content, while adapting to different types of data and various usage contexts.

This research falls within the field of data management systems and information processing, with a primarily methodological and academic focus. It aims to contribute to the improvement of tools and practices related to data analysis by proposing conceptual frameworks and solutions applicable to a variety of environments, particularly in the context of scientific research and general computer applications.