Classifications as Linked Open Data. Challenges and Opportunities (Chapter 2)

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

Research output: Chapter in book/volumeChapterScientificpeer-review


Linked Data (LD) as a web-based technology enables in principle the seamless, machine-supported integration, interplay and augmentation of all kinds of knowledge, into what has been labeled a huge knowledge graph. Despite decades of web technology and, more recently, the LD approach, the task to fully exploit these new technologies in the public domain is only commencing. One specific challenge is to transfer techniques developed preweb to order our knowledge into the realm of Linked Open Data (LOD). This paper illustrates two different models in which a general analytico-synthetic classification can be published and made available as LD. In both
cases, an LD solution deals with the intricacies of a pre-coordinated indexing language. The Universal Decimal Classification (UDC) approach illustrates a more complex solution driven by the practical requirements that the LD model is expected to fulfill in the bibliographic domain, and within the constraints of copyright protection. The Basic Concepts Classification (BCC) is a new classification with a novel approach to classification structure and syntax for which LD is an important vehicle for increasing the scheme’s visibility and usability. The report on these two cases illustrate some of the challenges of the representation of knowledge organization systems as LD and the possibilities that analytico-synthetic and interdisciplinary or phenomenon-based systems present for the representation of knowledge using LD.
Original languageEnglish
Title of host publicationLinking Knowledge
Subtitle of host publicationLinked Open Data for Knowledge Organization and Visualization
EditorsRichard P. Smiraglia, Andrea Scharnhorst
PublisherErgon – ein Verlag in der Nomos Verlagsgesellschaft
ISBN (Electronic)978-3-95650-661-1
ISBN (Print)978-3-95650-660-4
Publication statusPublished - 2021


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