# Wikidata Support in the Creation of Rich Semantic Metadata for Historical Archives
###### Abstract  
The research question this paper aims at answering is the following: In an ontology-driven annotation system, can the information extracted from external resources (namely, Wikidata) provide users with useful suggestions in the characterization of entities used for the annotation of documents from historical archives? The context of the research is the PRiSMHA project, in which the main goal is the development of a proof-of-concept prototype ontology-driven system for semantic metadata generation. The assumption behind this effort is that an effective access to historical archives needs a rich semantic knowledge, relying on a domain ontology, that describes the content of archival resources. In the paper, we present a new feature of the annotation system: when characterizing a new entity (e.g., a person), some properties describing it are automatically pre-filled in, and more complex semantic representations (e.g., events the entity is involved in) are suggested; both kinds of suggestions are based on information retrieved from Wikidata. In the paper, we describe the automatic algorithm devised to support the definition of the mappings between the Wikidata semantic model and the PRiSMHA ontology, as well as the process used to extract information from Wikidata and to generate suggestions based on the defined mappings. Finally, we discuss the results of a qualitative evaluation of the suggestions, which provides a positive answer to the initial research question and indicates possible improvements. semantic metadata generation; linked data; ontologies; digital curation; historical archives; digital cultural heritage; information exploration +
Footnote †: journal: Medical  
The digital transformation for historical archives is particularly challenging: The simple digitization of documents is not enough to offer an effective and flexible access, since the actual content of documents must be grasped. However, a completely automatic processing aimed at extracting document content can be very difficult, sometimes already at the OCR level (e.g., in case of very blurred old text with handwritten annotations--see Figure 1), sometimes when trying to apply complex NLP approaches (e.g., event-extraction [1]) to OCR-ized texts. A valid alternative to fully automatic processing is to involve users in the annotation process, by enabling them to build machine-readable information about document content while exploiting NLP (in particular, Information Extraction) to support them in this activity. This is the perspective we committed to in the PRiSMHA project. PRiSMHA (Providing Rich Semantic Metadata for Historical Archives) [2] is a three-year (2017-2020) national project, involving the Computer Science and the Historical Studies Departments of the University of Torino. The project is funded by Fondazione Compagnia di San Paolo and Universita di Torino, and it is based on the close collaboration with the Polo del '900 (www.polodel900.it, accessed on 10 May 2021), in particular with the Fondazione Istituto piemontese [PERSON] (www.gramscitorino.it, accessed on 10 May 2021), which is the major contributor of the Polo del '900 historical archive (www.polodel900.it/9 centro, accessed on 10 May 2021). The main goal of PRiSMHA is the design and implementation of an ontology-driven prototype platform supporting users in semantic metadata production. The assumption behind the approach adopted in the project, shared within the Digital Humanities community (see, for instance, [3; 4; 5]), is that an effective and engaging access to historical archives needs a rich semantic knowledge, based on a domain ontology, describing the content of archival documents. In order to demonstrate the sustainability of this approach, we focused on the Italian political and social history of the 20 th century, taking especially into account the years from the 1960s to the 1990s.