Classifications as Linked Open Data: Challenges and Opportunities

Rick Szostak, Richard P. Smiraglia, Andrea Scharnhorst, Ronald Siebes, Aida Slavic, Daniel Martínez Ávila, Tobias Renwick

Onderzoeksoutput: Hoofdstuk in boek/boekdeelHoofdstukWetenschappelijkpeer review

Samenvatting

Linked Data (LD) as a web-based technology enables in principle the seamless, machine-supported integration, interplay and augmention of all kinds of knowledge, into what has been labeled a huge knowledge graph. Despite decades of web technology and, more recently, the Linked Data approach, the task to fully exploit these new technologies in the public domain is only commencing. One specific challenge is to transfer techniques developed pre-web to order our knowledge into the realm of Linked (Open) Data. This paper illustrates two different models in which a general analytico-synthetic classification can be published and made available as linked data. In both cases, a linked data solution deals with the intricacies of a pre-coordinated indexing language: the Universal Decimal Classification (UDC) and the Basic Concepts Classification (BCC).
Originele taal-2Engels
TitelKnowledge Organization at the Interface
SubtitelProceedings of the Sixteenth International ISKO Conference, 2020 Aalborg, Denmark
RedacteurenMarianne Lykke, Tanja Svarre, Daniel Martínez-Ávila
Pagina's436-455
Uitgave2020
ISBN van elektronische versie978-3-95650-776-2
DOI's
StatusGepubliceerd - 2020

Publicatie series

NaamAdvances in Knowledge Organization
Volume17

Vingerafdruk Duik in de onderzoeksthema's van 'Classifications as Linked Open Data: Challenges and Opportunities'. Samen vormen ze een unieke vingerafdruk.

Citeer dit