Research on Ontologies of Cultural Heritage and re- lated topicslated topics

26 Department of Computer Science

❼ Abstract, Non-representational Art

❼ Religion and Magic

❼ Nature

❼ Human being, Man in general

❼ Society, Civilization, Culture

❼ Abstract Ideas and Concepts

❼ History

❼ Bible

❼ Literature

❼ Classical Mythology and Ancient History

The Resource Description and Access (RDA)[RSC, 2020] standard is a set of el- ements, guidelines and instructions for the creation of metadata for library and cultural heritage resources according to international models, focused on linked data applications.

RDA was created as a replacement for the Anglo American Cataloguing Rules. RDA has had a mostly widespread application in the library domain. The use of RDA has a subscription cost.

3.3 Research on Ontologies of Cultural Heritage and re-

proposed in SCULPTEUR is based on CIDOC CRM, and extends it to include concepts such as digital representations of objects, feature vectors of these digital representations, algorithms used to produce and compare feature vectors, tools for query construction, digital representations for display. In this way it is possible to establish digital attribute relationships by means of feature vectors.

MUSEUMFINLAND project [Hyv¨onen et al., 2005], is a proposal for semantic integration of museums in Finland, which is based on seven domain ontologies:

❼ Artifacts, defines tangible objects such as weapons or clothing.

❼ Materials, defines artifact materials such as steel or wood.

❼ Actors, defines agents as persons or companies.

❼ Situations, defines intangible incidents, events and processes.

❼ Locations, defines areas and places.

❼ Times, defines historic periods.

❼ Colections, a taxonomy that classifies the collections included in the museum’s pa- tronage.

MUSEUMFINLAND uses the Finnish cultural content dictionary MASA ⁹ to cre- ate MAO ontology (now part of Finto service discussed in standards), from which the sub-ontologies artifacts, materials and situations are derived. Other sub-ontologies were created by first defining classes, and then instantiated using various sources. The authors report two main problems: unknown values and homonymy. For the former, the solution adopted was to map the unknown feature to a more general concept (a higher class) or to a global resource considered unknown. For homonymies, the instantiation included all potential options, and some note or warning information was added in order to allow a human editor to decide and solve the problem later.

Curate[Mulholland et al., 2012] presents an approach around curatorial narratives, therefore the exhibition is enriched by these narratives, or even form an exhibition of its own with the support of physical media. The problematic exposed by the authors is that the meaning of the narrative cannot be expressed or derived solely from the metadata of cultural heritage objects. They base their research on the hypothesis that curatorial narrative has generic characteristics and properties that can be found in other narratives such as novels or films, therefore the concepts ofStory,Plot andNarrativecan be adopted.

Curate is based on CIDOC CRM and DOLCE+DnS Ultralite (DUL).

MOM[Hajmoosaei and Skoric, 2016], is an ontology that also deals with the hetero- geneous nature of cultural heritage and is mainly based on CIDOC CRM and Europeana Data Model (EDM), in addition to ORE, FOAF, DC and SKOS. The main classes it takes from EDM are: Non-Information resource which includes, Event, Time Span, Place; In- formation Resource, which includes Web Resource and Provided CHO. On the CRM side: Actor which includes Group and Person; Physical Thing which includes: Physical Man-Made thing, Biological object and Collection; Conceptual Object which includes Ap- pelation and Information Object and this in turn includes: Procedure, Linguistic Object, Document and Visual Item. The ontology is completed with own concepts such as Role and Digital Information.

9http://id.loc.gov/vocabulary/subjectSchemes/masa.html

28 Department of Computer Science OntoMP [Araujo et al., 2016, Ara´ujo et al., 2017], is an ontology that arises from the creation of a virtual museum (Museu da Pessoa), whose purpose is to exhibit the his- tory of common people. OntoMP is mainly based on CIDOC CRM, in addition to FOAF and DBPedia. OntoMP concepts are directly related to the nature of the person (Peo- ple, Ancestry, Offspring, etc.), episodes of his life (Childhood episode, Leisure episode, Marriage, Birth, etc.), abstract concepts (Dreams, Religion, Costumes, etc.); relation- ships (Receives, Visits, Performs, etc.). Some concepts are referenced to CIDOC CRM directly, however some person-related properties cannot be described naturally, therefore concepts from FOAF are included such as: Gender, Person Names, Person-images rela- tions. From DBPedia are included properties such as Religion, Profession, Education, Party and Spouse.

Marchenkov et al.[Marchenkov et al., 2017] propose an ontology that aims to create a service-oriented digital environment for museum visitors and staff to provide personal recommendations about museum collections based on the context of the user and the exhibition, as well as collaborative management of information contained in different museums. The authors propose a layered model in which the semantic layer is responsible for providing three advanced services:

❼ Visit: consists of a personalized exhibition from a set of objects available in the museum based on the visitor’s available knowledge. This service is dynamically adapted during the visit.

❼ Exhibition: this service displays descriptions and visual information on visitors’

screens and personal devices, so physical exhibits are enhanced by digital represen- tations.

❼ Enrichment: to support the evolution of the semantic network, allowing to receive feedback from visitors and staff in order to improve the information contained.

These services are made possible through the proposed ontological model, which is based on CIDOC CRM, but is extended to host a Recommendation System, through a sub- ontology called Rank, which contains the Rank class that stores the scores of the exhibits in addition to Exhibit and Profile classes.

TOMS[Chanhom and Anutariya, 2019] is a project whose main objective is to en- able collaboration and information exchange between national museums in Thailand. It is based on the use of linked open data (LOD) and an ontology model based on CIDOC CRM. The project proposes an architecture based on three layers: data storage, data ma- nipulation and processing, and a system interface layer. The authors detail the mapping of existing information with the corresponding concept in CIDOC CRM. Finally they make a qualitative evaluation based on the user experience and their level of satisfaction. Some evaluation points are the improvement in work efficiency and the perceived usefulness of the system.

Lo Turco et al. [Turco et al., 2019], describe an investigation about the relation- ships between cultural heritage, digital technologies and visual models. To do this, they require a data structure based on an ontology called Upper-level Ontology, which for- malizes concepts and relationships. The authors make use of the CIDOC CRM classes and relationships for the available data and the CRMdig extension for mapping the docu-

28 Universidad Cat´olica San Pablo

mentation of theevaluative, analytical, deductive, interpretive and creative decisions first made in their acquisition process and then related to the computer-based visualization.