Large catalogues are moving from the database metadata management age using specific Information Science and Libraries formats, to the Web age using Semantic Web standard languages (RDF / S, OWL). This development, bringing many advantages (better document availability, increased data exchange capabilities, creation of new search / use services for documents), raises important issues about the quality of document databases. This project aims to develop mechanisms to: • describe the quality of an existing document database; • maintain a given level of quality by controlling updates on such databases; • improve the quality of a database; • exploit these databases according to their level of quality (eg the search for documents or combination of bases). Representing data using Semantic Web standards allows for a Knowledge Representation approach to this problem. This approach will allow on one hand to give a logical semantics to the notion of quality and, on the other, to use reasoning mechanisms for dealing with various problems. This approach is rooted on the (i) formalization of knowledge found in document catalogues, (ii) the development of a quality model for the individual entities (named entities) identification problem, (iii) the definition of a trust model suitable for reconciliation and different source information fusion and (iv) the discovery of entity identification characteristics and their manipulation by different techniques (logical, numerical, probabilistic, etc.). A large part of the project is devoted to the evaluation of the proposed approach by experiments conducted on suitable test benchmarks and the development of demonstrators adapted to the two document databases owners involved in the project. The consortium brings together five complementary partners: two major national players of document catalogues and three research groups of computer scientists. The Bibliographic Agency for Higher Education (ABES) and the Institut National de l'Audiovisuel (INA) are managing very large document databases and are heavily involved, both at a national and international level, in the exposure, standardization, interconnection and use of their metadata. The teams of the LIG, LIRMM and LRI involved in this project have a strong expertise in databases, knowledge representation and semantic web. Furthermore, numerous research connections exist between the project partners. The skills of scientific partners and links forged between them as part of joint projects are very important to the success of this multidisciplinary project that involves both Information Science and Libraries as information technology, and should impact not only the field of document databases but also the Web of Data ("Linked Data").

Sharing and reuse of archaeological or historical data: a RDF-based description according to semantic web repositories and standards The HisArc-RDF project brings together a multidisciplinary consortium: archaeology, history, geography, terminology, bibliography and informatics. The pooling of experiences, based on the sharing and articulation of methods and software and semantic tools developed in each discipline, will make it possible to prototype (implementation and iterative tests) a "FAIR" operating chain on structurally and semantically heterogeneous archaeological and historical data sets: - to write a data management plan (DMP) for each dataset, based on the recommendations of the European Union and the french National Open Science Plan; - to develop two softwares : the first one operating a webservice between the OntoME tools (matching ontologies tool) designed by a community of historians and Opentheso (aligning thesauri tool) designed with a community of archaeologists; the second one creating a generic supervised automatic alignment interface between Opentheso and any semantic web repository; - to document each test set by a fine-grained processing chain, based on the use of microthesauri, descriptor concepts aligned with semantic web repositories, and then on the matching of the ontology expressed by the thesauri with the reference standards and ontologies of the documentary and scientific communities; thanks to the software developed, this phase will lead to a RDF-structured description of the test datasets; thus allowing, after online publication, the reporting and direct reuse ("calculability") of the datas; - to lead a wide network of historical and archaeological stakeholders (repository supports, multidisciplinary research groups, programmed and preventive archaeologies, European and non-European sites, academic and private stakeholders) through a training programme and experimental workshops, in order to disseminate the good practices supported and expressed by the operating chain and the tools developed during the project. The foundation of the HisArc-RDF project is threefold: a convergence of views born from the confrontation of multidisciplinary practices and experiences around the life cycle of data, from its acquisition to its publication, sharing and mediation; an acculturation of archaeological and historical communities to the practical and scientific challenge of aligning their vocabularies on semantic web core repositories; and finally the need for a processing chain capable of appropriation by these communities - i. e.i.e. as close as possible to business practices and work in the field and laboratories. The outcome of the project will be the realization and open publication of a methodology and associated tools in order to implement in our disciplines an ecosystem of "FAIR" data production, publication and sharing. It will be based on a proof of concept: the targeted user experience is the sharing and effective reuse of data extracted from recording systems (raw data), regardless of the structure specific to a particular database; it is the responsibility of each operating interface/visualization to pick them up and configure them to allow their reuse. The rapid implementation of these linked open data will be at the service of the widest possible academic audience: students, museums and research teams.