Managing the domain knowledge: application to cultural patrimony

Abstract

This article presents applied research work that addresses a real need for improvement of the collection, indexing and retrieval of knowledge of cultural heritage. To facilitate the task of fieldwork and to improve the access to knowledge, we designed, prototyped and tested in a real environment a system for automating the cycle of collecting and storing information and knowledge for future processing. It contains several modules, allowing the knowledge acquisition cycle to be completed: registering artwork description using a voice interface, automatic 'translation' of the audio files to text files, linguistic analysis and extraction of information for the Inventory Descriptive System and, finally, automatic construction of a domain ontology according to a predefined conceptual model. This hybrid system combines the techniques of signal and natural language processing and of knowledge modelling. After introducing the process of the acquisition and management of information gathered in the field, we describe the nature of knowledge, the models used, the architecture and the various treatments performed by our system. Finally, we provide some perspectives on future development.

Identification of social scientifically relevant topics in an interview repository: a natural language processing experiment

“…Thus the discipline of digital curation has emerged. Data curators and researchers, possessing accumulated knowledge in their specific field and, ideally, also in other sciences, play a vital role in providing access to research data (Château et al , 2012). Digital data curation and research focuses on the interplay between the professional, academic and technical dimensions of the research process in order to ensure that information created digitally remains accessible and useable (Higgins, 2018).…”