The CrossCult Knowledge Base: A Co-inhabitant of Cultural Heritage Ontology and Vocabulary Classification

Abstract

CrossCult is an EU-funded research project aiming to spur a change in the way European citizens appraise History, fostering the re-interpretation of what they may have learnt in the light of cross-border interconnections among pieces of cultural heritage, other citizens' viewpoints and physical venues. Exploiting the expressive power, reasoning and interoperability capabilities of semantic technologies, the CrossCult Knowledge Base models and semantically links desperate pieces of Cultural Heritage information, contributing significantly to the aims of the project. This paper presents the structure, design rationale and development of the CrossCult Knowledge Base, aiming to inform researchers in Digital Heritage about the challenges and opportunities of semantically modelling Cultural Heritage data.

On How Technology-Powered Storytelling Can Contribute to Cultural Heritage Sustainability across Multiple Venues—Evidence from the CrossCult H2020 Project

“…In this final subsection, looking back to the CH datasets that we worked with and the lessons we were taught by the CrossCult experience, we discuss whether current models of CH data flows to larger aggregators is still a sustainable solution for all types of CH institutions or whether new paradigms such as aggregation of CH data across and between CH European institutions, is gaining more ground as a model to move forward for a more sustainable model within CH ecosystems. In the CrossCult project, we experimented with both approaches; we demonstrated practical implementations for sharing the CH datasets to larger collections aggregators such as Europeana but at the same time we also facilitated inter-connections of multi-institutional CH collections and multiple venues, through the selection of certain organisational patterns, data models, digital storytelling or even specific software [59,60]. We postulate that the sole and one directional aggregation and linking of CH data to larger external repositories, is not sufficient enough to provide meaningful connections between CH institutions information resources, unless it is reinforced by connections to CH data modeling standards and interconnections between CH information resources of the CH ecosystems themselves.…”

Technology-Powered Strategies to Rethink the Pedagogy of History and Cultural Heritage through Symmetries and Narratives

“…The knowledge base created in the CrossCult project (hereafter, the CrossCult knowledge base or CCKB [18]) supplements the CIDOC-CRM constructs with the semantics of SKOS (Simple Knowledge Organization System (www.w3.org/2004/02/skos/)), which are used for representing thesauri, classification schemes, subject-heading systems, or any other type of structured controlled vocabulary. We use the Dublin Core schema (dublincore.org/documents/dcmi-terms/) as standard vocabulary for describing digital resources, and FOAF (Friend of a Friend (xmlns.com/foaf/spec/)) ontology to capture user-related entities and their interests.…”

Hydria: An Online Data Lake for Multi-Faceted Analytics in the Cultural Heritage Domain

“…In the last few years Cultural Informatics (CI) has surfaced as a new promising domain that constitutes the socio-technological approach to understand, represent, communicate and re-invent cultures and cultural institutions [1]. CI may also be used in a disruptive fashion, aiming to change the way we understand and experience our cultural heritage [2], by enabling us, for example, to create personalized museum experiences [3,4], to discover facets and stories from new or existing cultural heritage data [5][6][7], or to create inter-linked cultural data repositories [8][9][10][11]. While performing these tasks, CI are creating an avalanche of data, produced by a vast number of related activities such as profiling of or feedback from museum and cultural venue visitors [12][13][14][15], social media activity (e.g., posts and comments) related to cultural events [16][17][18][19][20][21][22][23], papers and specialized conferences on the topic [24][25][26][27], and raw data on cultural objects such as artifact descriptions [28][29][30][31].…”

“…While performing these tasks, CI are creating an avalanche of data, produced by a vast number of related activities such as profiling of or feedback from museum and cultural venue visitors [12][13][14][15], social media activity (e.g., posts and comments) related to cultural events [16][17][18][19][20][21][22][23], papers and specialized conferences on the topic [24][25][26][27], and raw data on cultural objects such as artifact descriptions [28][29][30][31]. This data is typically fragmented and distributed among the different stakeholders, while the data management solutions that are involved vary greatly, ranging from simple spreadsheet files for the less tech savvy to typical data stores such as relational databases [32][33][34] or semantically richer knowledge bases [9,10,35,36].…”

“…Moreover, the asynchronous nature of the data acquisition process itself poses new challenges in the collection, organization, and processing of the relevant data [37]. Proposed solutions for data storage of cultural information (e.g., [9,10,35,41]) usually require significant computing infrastructure, which is not easy to obtain or maintain, and the constant support and active involvement of IT experts even for trivial tasks, like creating a graph from the given data, updating the produced statistics, or incorporating a new data source/set. Typically, reconfiguring an existing solution for reuse in another setup or setting one up from scratch for the specific cultural data management problem requires (i) time-consuming meetings between scientists of different disciplines trying to understand each other's needs and goals, and (ii) resource-consuming IT infrastructure that calls for outsourcing to IT specialists and regular maintenance/upgrades to keep up with technological requirements [42].…”