Classifications as Linked Open Data Challenges and Opportunities

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) approach illustrates a more complex solution driven by the practical requirements that the linked data 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 linked data 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 KOSs as LD and the possibilities that analytico-synthetic and interdisciplinary/phenomenon-based systems present for the representation of knowledge using LD.