Libraries at University of Nebraska-Lincoln



Background. With the evolution of information technology, library classification schemes have transformed to effectively manage the information in electronic environment. The availability of library data on the web makes it challenging to devise a classification scheme that meet the need of Linked Data (LD) technologies. Objectives. This study aims to survey the library classification system along with automated classification system. It also highlights the links between the library classification systems and web of document classification system as a joint venture of LD.

Methods. For achieving the objectives of the study, available literature related to the traditional classification schemes, automated classification schemes and Linked Data classification systems were consulted. Different classification formats at different ages, Components of traditional classification, and components of Linked data RDF triples are described through figures. Comparison for the principles of library classification and linked Data and the types of classification are given through tables. Results. The results of this study show that Linked Data classification methods such as subject, predicate and object have the foundations on the traditional and machine readable classification systems. It is found that LD technologies for linking and sharing structured data on the web like, Uniform Resource identifier (URI) and Resource Description Framework (RDF) are based upon previous classification schemes.

Contributions. This study provides a precise picture of renowned traditional, online and LD classification schemes. This will be helpful to develop new RDF triple based ontologies for library LD organization.

Key Words: Linked Data, Classification, Data classification, Resource Description Framework