Extending RiC-O to Model Historical Architectural Archives: The ITDT Ontology

Historical architectural archives enjoy attention from diverse audiences, acting as a primary source of information for architects, historians, public authorities, and common citizens alike. In Italy, the interest in architectural archives has grown slowly but steadily for the last 20 years. However, architectural archives do not generally follow the trend common for museums and galleries in publishing digitized materials and providing standard metadata for individual records. The information that is available online usually includes only an archival finding aid, instead of metadata about the individual records, or fully digital versions of the records. While cataloguing standards for archival descriptions of architectural records have existed at least since the 1980s, the rise of Linked Open Data as a framework for publishing cultural heritage data has allowed archivists to enhance these archival descriptions with richer contextual information and links to external knowledge bases. In this paper we present the ITDT ontology, an extension of the Records in Contexts Ontology that facilitates the representation of architectural records and of the context related to architectural projects, its process, and participating entities. We discuss the application of the ontology to the project files of Italian architect and engineer Dino Tamburini (1924–2011), and the creation of a digital archive offering multiple perspectives over the records

Sloane Lab: Domain Vocabularies for Semantic Interoperability of Museum Collections

How do domain vocabularies and terminological resources contribute to semantic harmonisation and enrichment of siloed collections in digital infrastructures? What is the role of industry-standard and bespoke museum-owned authority files and terminologies in the process of ‘creating a unified virtual “national collection” by dissolving barriers between different collections and opening UK heritage to the world’ (Towards a National Collection, 2022)? The Sloane Lab aims to aggregate a multitude of catalogue records (both historic and current, from multiple disciplines) dispersed across the British Museum, Natural History Museum and British Library. The task of integrating these disparate records and facilitating interoperable access poses significant challenges. The competency of domain-oriented standardised, high-level ontologies such as CIDOC-CRM to act as a common application layer of data semantics and their capacity to enable innovative ways for cross-searching, contextual exploration and interrogation is well documented in the literature. However, their ability to provide a common conceptual layer of high-level semantics for the purposes of unification, alignment and harmonisation comes at the expense of the specialisation of terminological and typological definitions. This can hinder the discovery and interrogation of resources at a higher level of granularity and limit the opportunities for entity enrichment and linking to external definitions from the Linked Data Cloud. We discuss a method of specialisation of upper-level ontologies by adding an additional level of vocabulary semantics of thesauri, glossary, and authority files to supplement the CIDOC-CRM with specialised terms. In this process, we highlight the role and contribution of museum-based vocabulary resources towards the realisation of unified collections and the opportunities they offer for semantic enrichment, linking and interoperability

Semantic technologies for historical collections: A case study from the Sloane Lab Knowledge Base

The founding collection of the British Museum is a rich area to explore how we can reconnect dispersed heritage connections using state of the art technologies. In the Sloane Lab, we aim to represent this vast cultural heritage collection made up of disparate objects. At the core of the Sloane Lab resides the Knowledge Base (KB), which provides a homogeneous data environment using formal semantics to allow data integration, semantic enrichment, and knowledge discovery across a disparate environment of resources. The most fundamental challenge of the KB is the provision of a suitable semantic metadata schema for unifying the catalogues and enabling the Knowledge Graph to facilitate resourceful query, visualisation and fact-finding. The Sloane Lab approach to the modeling of the collection is record-centric, meaning that the record is the central entity that we represent. Most museum datasets are object-centric but in our case this can lead to multiple descriptions of the same object that are conflicting with each other. The semantic representation of the Sloane Lab knowledge base is based on Semantic Web standards, in particular RDF, RDFS, and OWL, and our data model is built on top of the CIDOC CRM reference ontology. The presentation will provide a rich insight to the design and development of the Sloane Lab knowledge base, the modelling choices and priorities in relation to semantics and vocabularies and the range of challenges addressed in the process of aggregation in terms of data disparity, integration facility, conflicting information and inconsistency, uncertainty and data absence

A Wikidata-Based Tool for the Creation of Narratives

This thesis presents the results of a 12-month-long internship in the Digital Libraries group of the NeMIS laboratory of ISTI-CNR. The focus of the internship was the development of a semi-automated tool for representing narratives in a digital library. This work is part of a larger research effort on the representation of narratives through Semantic Web technologies, including the development of an Ontology of Narratives based on the CIDOC CRM reference ontology. The tool which is presented in this thesis is composed of a web interface which allows the user to create a narrative starting from a specific subject, a triplification component to trasform the inserted knowledge into the OWL language, and several visualization components. The tool is based on the Ontology of Narratives, of which it is the first application, and also on Wikidata, an open collaborative knowledge base of recent development, whose entities are imported in the tool in order to facilitate the data insertion by the user. This thesis also reports the challenges that were encountered in the development of a mapping between the CIDOC CRM and Wikidata ontologies. The tool is the first application to make use of the Ontology of Narratives, and will allow an evaluation of it through the representation of a case study, the biography of Dante Alighieri, the famous Italian poet of the late Middle Ages

Steps Towards a Formal Ontology of Narratives Based on Narratology

Narrative is emerging as a notion that may enable overcoming the limitations of the discovery functionality (only ranked lists of objects) offered by information systems to their users. We present preliminary results on modelling narratives by means of formal ontology, by introducing a conceptualization of narratives and a mathematical expression of it. Our conceptualization tries to capture fundamental notions of narratives as defined in narratology, such as fabula, narration and plot. A validation of the conceptualization and of its mathematical specification is ongoing, based on the Semantic Web standards and on the CIDOC CRM ISO standard ontology

Queering Wikidata: Early insights from the Wikidata Gender Diversity project

Wikidata Gender Diversity (WiGeDi) is a one-year project funded through the Wikimedia Research Fund, aiming to study gender diversity in Wikidata in a wide and comprehensive way. In the project, we adopt an intersectional feminist and queer approach, viewing gender as a social construct and centering marginalized gender identities such as trans and non-binary people. To study gender diversity in Wikidata, we are adopting three complementary perspectives: model, data, and community. First, we are investigating how the current Wikidata ontology model represents gender, attempting to understand the extent to which this representation is fair and inclusive, and looking at how the Wikidata ontology has evolved over time to support the representation of a wider spectrum of identities. We are analysing the data stored in the knowledge base in a quantitative way, to gather insights and identify gaps. Finally, we are looking at how the community has handled the move towards the inclusion of a wider spectrum of gender identities, by analysing user discussions about the topic with computational linguistics methods; indeed, gender representation is often intrinsically connected to language, and this is especially relevant in a multilingual project such as Wikidata. We believe that only by answering all three questions it will be possible to obtain a comprehensive overview of gender diversity in Wikidata. In the presentation, we will discuss early results from the project and show a preview of the tools that we are building to explore and analyze the data

Towards a Network Analysis of Hans Sloane's Collection: A Preliminary Study

“The Sloane Lab: Looking back to build future shared collections” is a 3-year project funded by the UKRI Towards a National Collection programme. The project aims to re-establish connections between Sloane’s collections and catalogues and to mend the broken links between the past and present of the UK's founding collection in the catalogues of the British Museum (BM), Natural History Museum (NHM) and the British Library (BL). Engaging with interested communities and employing digital technology, the project will integrate a fragmented cultural heritage collection and enable its unification through a participatory lens. The collection was amassed by Sir Hans Sloane (1660–1753), who gathered and, with his amanuenses, catalogued more than 70,000 disparate objects which formed the initial nucleus of the original British Museum (the collection was then dispersed across the present-day BM, BL, and NHM). The project will integrate disparate data sources, ranging from historical catalogues to contemporary records, and will enable a wide analysis of Sloane’s extensive social network. As shown by James Delbourgo, Sloane’s collection was “not the achievement of a single individual, but rather the result of exchanges involving countless people across the globe” (Collecting the World, 2017, p. 202). Sloane’s historical catalogues contain many references to people and places, but this data has never been studied extensively through network analysis methods. Our goal is to build a graph of Sloane’s social network by analysing mentions of people in the catalogues, to further understand the connections between them. In addition, we hope to devise computational approaches that can focalize the “data absences” that affect the collection, centring the biases that affected heritage description practices, and drawing attention to people who had an important role in the collection, but whose contribution has been historically overlooked or is now lost. At present, we have access to the digital versions of five of Sloane’s historical manuscript catalogues, which have been encoded in TEI-XML format in the Enlightenment Architectures project. We have started our study from the Miscellanea manuscript, which actually contains seven separate catalogues, plus two indices. We have built a parser to extract data about people and places from the catalogues from the XML files, and gathered more information about them through VIAF and Wikidata. We have then analysed the networks of people and places in the whole dataset, visualised the data, and compared the individual catalogues to understand how their social networks are linked, how they differ from each other, and how they relate to the places and to the objects themselves. In this presentation, we will show the results of our initial analysis, which will then be expanded to other historical catalogues and data sources, laying the foundations for a more complete understanding of the social network behind Sloane’s collection

Enhancing the Computational Representation of Narrative and Its Extraction from Text

Narratives are a fundamental part of human life. Every human being encounters countless stories during their life, and these stories contribute to form a common understanding of reality. This is reflected in the current digital landscape, and especially on the Web, where narratives are published and shared everyday. However, the current digital representation of narratives is limited by the fact that each narrative is generally expressed as natural language text or other media, in an unstructured way that is neither standardized nor machine-readable. These limitations hinder the manageability of narratives by automated systems. One way to solve this problem would be to create an ontology of narrative, i.e., a formal model of what a narrative is, then develop semi-automated methods to extract narratives from natural language text, and use the extracted data to populate the ontology. This thesis attempts to investigate this research question, starting from the state of the art in the fields of Computational Narratology, Semantic Web, and Natural Language Processing. After identifying a set of requirements, we have developed an informal conceptualization of narrative and expressed it using First-Order Logic. The result of this work is the Narrative Ontology (NOnt), a formal model of narrative that also includes a representation of its textual structure and textual semantics. Based on the ontology, we have developed NarraNext, a semi-automatic tool that is able to extract the main elements of narrative from natural language text. The tool allows the user to create a complete narrative based on a text, using the extracted knowledge to populate the ontology