Describing cultural heritage objects from the perspective of Linked Open Data (LOD) is not a trivial task. The process often requires not only choosing pertinent ontologies, but also developing new models that preserve the most information and express the semantic power of cultural heritage data. Indeed, data managed in archives, libraries and museums are complex objects themselves, which require a deep reflection on even non-conventional conceptual models. Starting from these considerations, this paper describes a research project: to expose the vastness of one of the most important collections of European cultural heritage, the Zeri Photo Archive, as Linked Open Data. We describe here the steps we undertook to this end: firstly, we developed two ad hoc ontologies for describing all the issues not completely covered by existent models (the F Entry and the OA Entry Ontology); then we mapped into RDF the descriptive elements used in the current Zeri Photo Archive catalog, converting into CIDOC-CRM and into the two new aforementioned models the source data based on the Italian content standards Scheda F (Photography Entry, in English) and Scheda OA (Work of Art Entry, in English); and finally, we created an RDF dataset of the output of the mapping that could show a result capable of demonstrating the complexity of our scenario.

A variety of schemas and ontologies are currently used for the machine-readable description of bibliographic entities and citations. This diversity, and the reuse of the same ontology terms with different nuances, generates inconsistencies in data. Adoption of a single data model would facilitate data integration tasks regardless of the data supplier or context application. In this paper we present the OpenCitations Data Model (OCDM), a generic data model for describing bibliographic entities and citations, developed using Semantic Web technologies. We also evaluate the effective reusability of OCDM according to ontology evaluation practices, mention existing users of OCDM, and discuss the use and impact of OCDM in the wider open science community.

Semantic Web technologies are widely used for storing RDF data and making them available on the Web through SPARQL endpoints, queryable using the SPARQL query language. While the use of SPARQL endpoints is strongly supported by Semantic Web experts, it hinders broader use of RDF data by common Web users, engineers and developers unfamiliar with Semantic Web technologies, who normally rely on Web RESTful APIs for querying Web-available data and creating applications over them. To solve this problem, we have developed RAMOSE, a generic tool developed in Python to create REST APIs over SPARQL endpoints. Through the creation of source-specific textual configuration files, RAMOSE enables the querying of SPARQL endpoints via simple Web RESTful API calls that return either JSON or CSV-formatted data, thus hiding all the intrinsic complexities of SPARQL and RDF from common Web users. We provide evidence that the use of RAMOSE to provide REST API access to RDF data within OpenCitations triplestores is beneficial in terms of the number of queries made by external users of such RDF data using the RAMOSE API, compared with the direct access via the SPARQL endpoint. Our findings show the importance for suppliers of RDF data of having an alternative API access service, which enables its use by those with no (or little) experience in Semantic Web technologies and the SPARQL query language. RAMOSE can be used both to query any SPARQL endpoint and to query any other Web API, and thus it represents an easy generic technical solution for service providers who wish to create an API service to access Linked Data stored as RDF in a triplestore.

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Digital archives of memory institutions are typically concerned with the cataloguing of artefacts of artistic, historical, and cultural value. Recently, new forms of citizen participation in cultural heritage have emerged, producing a wealth of material spanning from visitors’ experiential feedback on exhibitions and cultural artefacts to digitally mediated interactions like the ones happening on social media platforms. Citizen curation is proposed in the context of the European project SPICE (Social Participation, Cohesion, and Inclusion through Cultural Engagement) as a methodology for producing, collecting, interpreting, and archiving people’s responses to cultural objects, with the aim of favouring the emergence of multiple, sometimes conflicting, viewpoints and motivating users and memory institutions to reflect upon them. We argue that citizen curation urges to rethink the nature of computational infrastructures supporting data management of memory institutions, bringing novel challenges that include issues of distribution, authoritativeness, interdependence, privacy, and rights management. To approach these issues, we survey relevant literature toward a distributed, Linked Data infrastructure, with a focus on identifying the roles and requirements involved in such an infrastructure. We show how existing research can contribute significantly in facing the challenges raised by citizen curation and discuss challenges and opportunities from the socio-technical standpoint.