From the web of bibliographic data to the web of bibliographic meaning: structuring, interlinking and validating ontologies on the semantic web

Abstract

Bibliographic datasets have revealed good levels of technical interoperability observing the principles and good practices of linked data. However, they have a low level of quality from the semantic point of view, due to many factors: lack of a common conceptual framework for a diversity of standards often used together, reduced number of links between the ontologies underlying datasets, proliferation of heterogeneous vocabularies, underuse of semantic mechanisms in data structures, "ontology hijacking" (Feeney et al., 2018), point-to-point mappings, as well as limitations of Semantic Web languages for the requirements of bibliographic data interoperability. After reviewing such issues, a research direction is proposed to overcome the misalignments found by means of a reference model and a superontology, using SHACL (Shapes Constraint Language) to solve current limitations of RDF languages.

A semantic web approach to uplift decentralized household energy data

“…However, certain crucial disadvantages will endure for years. First, it requires a sufficient amount of domain knowledge in the schemas of all relevant datasets, as well as a number of acceptable ontology vocabularies for semantic enrichment [58,59]. Second, it will significantly increase the complexity of the data as the ontologies created by various parties are challenged to be united in compliance with some common protocol.…”

Study of library data models in the semantic web environment

“…Studies about library linked data projects have already identified important differences between the projects with regard to semantic interoperability issues, meaning the selected models, schemas and value vocabularies (Smith-Yoshimura, 2016Suominen & Hyvönen, 2017;Tallerås, 2018;Ullah, Khusro, Ullah, & Naeem, 2018). The existence of so many and different library linked datasets further raises the concern if the published datasets can be linked to one another, and if they can ultimately support the explore user task (H. Park & Kipp, 2019;Patrício et al, 2020;Suominen & Hyvönen, 2017;Tallerås, 2018).…”

“…Reports and studies regarding existing library linked data projects have raised concerns regarding the proliferation of bibliographic models and vocabularies (Hillmann, Coyle, Phipps, & Dunsire, 2010;Jett, Cole, Page, & Downie, 2016;Lovins & Hillmann, 2017;Patrício et al, 2020), the interoperability of bibliographic models with Linked Data principles (Dunsire, 2012;H. Park & Kipp, 2019;Peponakis, 2016;Willer & Dunsire, 2013), and the interoperability between the bibliographic models themselves (Cagnazzo, 2017;Hallo et al, 2016;Nillson, 2010;H.…”

“…Such practices will likely impact semantic interoperability, which is already affected by 1) the plethora of conversion tools from MARC21 to FRBR, BIBFRAME or to other custom-made models generating bibliographic datasets with great differences between them (H. Park & Kipp, 2015), 2) the coincidental unavailability of tools for publishing linked data (Frosterus et al, 2020;Smith-Yoshimura, 2016Taniguchi, 2017a;Ullah et al, 2018;Wahid, Warraich, & Tahira, 2018) causing the development of custom solutions and "locally developed routines" (Frosterus et al, 2020), and 3) the mixture of metadata elements (many of them are deprecated ones) used in library linked data projects to describe bibliographic resources (H. Park & Kipp, 2019). Toward the end of liberating library data from legacy silos, new models are developed and the danger of creating new linked data silos has already been expressed (H. Park & Kipp, 2019;Patrício et al, 2020;Suominen & Hyvönen, 2017;Tallerås, 2018).…”

“…Toward the creation of a Library Linked Open Data Cloud, library datasets need to be linked to one another and share common semantics that applications can use to query and inference. Concerns have already been raised about the semantic interoperability between the models used in library linked datasets (H. Park & Kipp, 2019;Patrício, Cordeiro, & Ramos, 2020;Suominen & Hyvönen, 2017;Tallerås, 2018). The question that emerges is if semantic differences between the models may be overcome, and if so, how.…”