CIDOC2VEC: Extracting Information from Atomized CIDOC-CRM Humanities Knowledge Graphs

The development of the field of digital humanities in recent years has led to the increased use of knowledge graphs within the community. Many digital humanities projects tend to model their data based on CIDOC-CRM ontology, which offers a wide array of classes appropriate for storing humanities and cultural heritage data. The CIDOC-CRM ontology model leads to a knowledge graph structure in which many entities are often linked to each other through chains of relations, which means that relevant information often lies many hops away from their entities. In this paper, we present a method based on graph walks and text processing to extract entity information and provide semantically relevant embeddings. In the process, we were able to generate similarity recommendations as well as explore their underlying data structure. This approach was then demonstrated on the Sphaera Dataset which was modeled according to the CIDOC-CRM data structure.

DOLCE: A descriptive ontology for linguistic and cognitive engineering1

dolce, the first top-level (foundational) ontology to be axiomatized, has remained stable for twenty years and today is broadly used in a variety of domains. dolce is inspired by cognitive and linguistic considerations and aims to model a commonsense view of reality, like the one human beings exploit in everyday life in areas as diverse as socio-technical systems, manufacturing, financial transactions and cultural heritage. dolce clearly lists the ontological choices it is based upon, relies on philosophical principles, is richly formalized, and is built according to well-established ontological methodologies, e.g. OntoClean. Because of these features, it has inspired most of the existing top-level ontologies and has been used to develop or improve standards and public domain resources (e.g. CIDOC CRM, DBpedia and WordNet). Being a foundational ontology, dolce is not directly concerned with domain knowledge. Its purpose is to provide the general categories and relations needed to give a coherent view of reality, to integrate domain knowledge, and to mediate across domains. In these 20 years dolce has shown that applied ontologies can be stable and that interoperability across reference and domain ontologies is a reality. This paper briefly introduces the ontology and shows how to use it on a few modeling cases.

Representing and Validating Cultural Heritage Knowledge Graphs in CIDOC-CRM Ontology

In order to unify access to multiple heterogeneous sources of cultural heritage data, many datasets were mapped to the CIDOC-CRM ontology. CIDOC-CRM provides a formal structure and definitions for most cultural heritage concepts and their relationships. The COURAGE project includes historic data concerning people, organizations, cultural heritage collections, and collection items covering the period between 1950 and 1990. Therefore, CIDOC-CRM seemed the optimal choice for describing COURAGE entities, improving knowledge sharing, and facilitating the COURAGE dataset unification with other datasets. This paper introduces the results of translating the COURAGE dataset to CIDOC-CRM semantically. This mapping was implemented automatically according to predefined mapping rules. Several SPARQL queries were applied to validate the migration process manually. In addition, multiple SHACL shapes were conducted to validate the data and mapping models.

THE INTEGRATION OF SEMANTIC NETWORKS IN VIRTUAL EXHIBITIONS

In this article a use case is presented how a semantic network can be used to enrich the existing virtual exhibition “They Shared their Destiny. Women and the Cossacks’ Tragedy in Lienz 1945” about the fate of women during the Cossack tragedy in Lienz. By connecting via CIDOC CRM information about people, events, finds and places the goal was not only to make this information interoperable, but also to integrate the resulting knowledge graph into the exhibition, thus providing a further navigation level and enhancing the visitors’ experience.First, a short introduction to the existing exhibition and the presented project is given. In the second part, the scientific background of CIDOC CRM and its semantically enriched 3D content is outlined. In the third part the implementation and the project as a use case is described with respect to the data modelling and the integration of the semantic network into the 3-dimensional environment as well as the integration of spatial aspects and other internet resources. At the end, there is a summary with an outlook on future planned projects.

Addressing the Challenges of Interoperability and Cultural Heritage Data

One of the ongoing challenges for effective utilization of heritage science data is the lack of access to well-organized and accessible extant data sets and the need to structure data in formats that allow interrogation and integration of related data. This need for data fusion expands to both subjective and objective measurements and descriptors, as well as a long-overdue need for established guidelines for metadata and shared terminologies, or more critically, ontologies. Research into this area has shown the need for Knowledge Organization Systems (KOS) that bridge and integrate multiple ontologies that address specific needs – for example the Getty Vocabularies for cultural heritage terms, the Linked Art model for a simplified core CIDOC-CRM, as well as the OBO Foundry and other scientific ontologies for measurements and heritage science terminology.[1]

The Invisible Museum: A User-Centric Platform for Creating Virtual 3D Exhibitions with VR Support

With the ever-advancing availability of digitized museum artifacts, the question of how to make the vast collection of exhibits accessible and explorable beyond what museums traditionally offer via their websites and exposed databases has recently gained increased attention. This research work introduces the Invisible Museum: a user-centric platform that allows users to create interactive and immersive virtual 3D/VR exhibitions using a unified collaborative authoring environment. The platform itself was designed following a Human-Centered Design approach, with the active participation of museum curators and end-users. Content representation adheres to domain standards such as International Committee for Documentation of the International Council of Museums (CIDOC-CRM) and the Europeana Data Model and exploits state-of-the-art deep learning technologies to assist the curators by generating ontology bindings for textual data. The platform enables the formulation and semantic representation of narratives that guide storytelling experiences and bind the presented artifacts with their socio-historic context. Main contributions are pertinent to the fields of (a) user-designed dynamic virtual exhibitions, (b) personalized suggestions and exhibition tours, (c) visualization in web-based 3D/VR technologies, and (d) immersive navigation and interaction. The Invisible Museum has been evaluated using a combination of different methodologies, ensuring the delivery of a high-quality user experience, leading to valuable lessons learned, which are discussed in the article.

ONTOLOGY-BASED HBIM FOR HISTORIC BUILDINGS WITH TRADITIONAL WOODWORK IN TAIWAN

In recent years, the use of Historic Building Information Modeling (HBIM) has grown prevalent and thus provided a research opportunity. Differing from newly constructed buildings, structural components of historic buildings come with unique physical configurations and have amassed impressive amount of restoration data, all of which must be taken into consideration when incorporating Building Information Modeling. In terms of modelling, it is critical to determine the appropriate level of detail (LoD), level of information (LoI), especially the comprehensiveness and expandability of the database. International Committee for Documentation/Conceptual Reference Model (CIDOC CRM) is a widely accepted standard for ontology model. This study aims to integrate the HBIM and CIDOC CRM to construct a framework and comprehensive operational procedure for the modeling of traditional Minan architecture and a database with complete semantics archiving the background and restoration data. Autodesk A360 is ideal for collaborative. However, there are limitations when it comes to developing advanced models for data management or query; interactive experience; meeting model applications derived from future scenarios. Therefore, the study also offers a 3D modeling platform constructed using Unity, as well as a comparison of the platforms built with Unity, three.js and Autodesk A360 as a reference for users.

Rekomendācijas Atsauču datu semantiskās sadarbspējas veicināšanai starp Latvijas kultūras mantojuma institūcijām

Rekomendācijas ir pirmais mēģinājums aprakstīt vajadzības jaunam datu modelim datu semantiskās sadarbspējas veicināšanai starp Latvijas kultūras mantojuma institūcijām digitālā vidē. Tajās raksturoti Latvijas atmiņas institūciju atšķirīgie datu modeļi un standarti, galvenās datu elementu klases un praksē izmantotās vērtību vārdnīcas. Rekomendācijās veikts starptautisko konceptuālo arhīvu, bibliotēku un muzeju datu modeļu (RiC CM, IFLA LRM, CIDOC CRM) būtisko entīšu salīdzinājums, kā arī analizēti sešu starpnozaru kultūras mantojuma platformu (SNAC, Finto, FINNA, Wikidata, EDM, Intermi) sadarbības datu modeļi, standarti un principi. Noslēgumā apkopoti secinājumi un rekomendācijas, kā, izmantojot atvērto saistīto datu risinājumus, no ierakstiem atsevišķu institūciju slēgtās sistēmās pāriet uz vienotu kultūras mantojuma entīšu reģistra izveidi, kam jākļūst par galveno Atsauču datu risinājuma komponenti.