Abstract
An institution must understand its users to provide quality services, and archives are no exception. Over the years, archives have adapted to the technological world, and their users have also changed. To understand archive users' characteristics and motivations, we conducted a study in the context of the Portuguese Archives. For this purpose, we analysed a survey and complemented this analysis with information gathered in interviews with archivists. Based on the most frequent reasons for visiting the archives, we defined six main archival profiles (genealogical research, historical research, legal purposes, academic work, institutional purposes and publication purposes), later characterised using the results of the previous analysis. For each profile, we created a persona for a more visual and realistic representation of users.

Abstract
Various sectors within the heritage domain have developed linked data models to describe their cultural artefacts comprehensively. Within the archival domain, ArchOnto, a data model rooted in CIDOC CRM, uses linked data to open archival information to new uses through the prism of linked data. This paper seeks to investigate the potential to use information in archival records in a larger context. It aims to leverage classes and properties sourced from repositories deemed informal due to their crowd-sourcing nature and the possibility of inconsistencies or lack of precision in the data but rich in content, such as the cases of Wikidata and DBpedia. The anticipated outcome is attaining a more comprehensive and expressive archival description, fostering enhanced understanding and assimilation of archival information among domain specialists and lay users. To achieve this, we first analyse existing archive records currently described under the ISAD(G) standard to discern the typologies of entities involved. Subsequently, we map these entities within the ArchOnto ontology and establish correspondences with alternative models. We observed that entities associated with people, places, and events benefited the most from integrating properties sourced from Wikidata and DBpedia. This integration enhanced their comprehensibility and enriched them at a semantic level.

Abstract

Abstract