Visualization of typed links in Linked Data

Neubauer, Georg

doi:10.31263/voebm.v70i2.1748

Cited by 4 publications

(1 citation statement)

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“…LD interlinks are also known as typed links and the linking property used to describe the relationship between two URIs is known as a link-type (Neubauer 2017). Identity Links are a specific kind of typed-link where the subject and object URI refer to the same entity (Papaleo et al 2014).…”

Section: Linked Data Interlinkingmentioning

confidence: 99%

Using Linked Data to create provenance-rich metadata interlinks: the design and evaluation of the NAISC-L interlinking framework for libraries, archives and museums

2022

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Linked data (LD) have the capability to open up and share materials, held in libraries, archives and museums (LAMs), in ways that are restricted by many existing metadata standards. Specifically, LD interlinking can be used to enrich data and to improve data discoverability on the Web through interlinking related resources across datasets and institutions. However, there is currently a notable lack of interlinking across leading LD projects in LAMs, impacting upon the discoverability of their materials. This research describes the Novel Authoritative Interlinking for Semantic Web Cataloguing in Libraries (NAISC-L) interlinking framework. Unlike existing interlinking frameworks, NAISC-L was designed specifically with the requirements of the LAM domain in mind. The framework was evaluated by Information Professionals (IPs), including librarians, archivists and metadata cataloguers, via three user-experiments including a think-aloud test, an online interlink creation test and a field test in a music archive. Across all experiments, participants achieved a high level of interlink accuracy, and usability measures indicated that IPs found NAISC-L to be useful and user-friendly. Overall, NAISC-L was shown to be an effective framework for engaging IPs in the process of LD interlinking, and for facilitating the creation of richer and more authoritative interlinks between LAM resources. NAISC-L supports the linking of related resource across datasets and institutions, thereby enabling richer and more varied search queries, and can thus be used to improve the discoverability of materials held in LAMs.

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Section: Linked Data Interlinkingmentioning

confidence: 99%

Using Linked Data to create provenance-rich metadata interlinks: the design and evaluation of the NAISC-L interlinking framework for libraries, archives and museums

2022

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NAISC: An Authoritative Linked Data Interlinking Approach for the Library Domain

McKenna

Debruyne

O’Sullivan

2019

2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL)

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At SWIB 2018, we presented our early stage work on a Linked Data (LD) interlinking approach for the library domain called NAISC -Novel Authoritative Interlinking of Schema and Concepts. The aim of NAISC is to meet the unique interlinking requirements of the library domain and to improve LD accessibility for domain expert users. At SWIB 2019 we will present our progress in the development of NAISC including an improved graphical user-interface (GUI), user testing results, and a demonstration of NAISC's interlink provenance components.NAISC consists of an Interlinking Framework, a Provenance Model and a GUI. The Framework describes the steps of entity selection, link-type selection, and RDF generation for the creation of interlinks between entities, such as people, places, or works, stored in a library dataset to related entities held in another institution. NAISC specifically targets librarians by providing access to commonly used datasets and ontologies. NAISC incudes interlink provenance to allow data users to assess the authoritativeness of each link generated. Our provenance model adopts PROV-O as the underlying ontology which we extended to provide interlink specific data. An instantiation of NAISC is provided through a GUI which reduces the need for expert LD knowledge by guiding users in choosing suitable link-types.We will present NAISC and demonstrate the use of our GUI as a means of interlinking LD entities across libraries and other authoritative datasets. We will also discuss our user-evaluation processes and results, including a NAISC usability test, a field test/real-word application of NAISC, and a review of the interlink quality. Finally, we will demonstrate our provenance model and discuss how the provenance data could be modelled as LD develops over time.

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