SKOS Concepts and Natural Language Concepts: an Analysis of Latent Relationships in KOSs

TL;DR

This study analyzes how SKOS concepts in Knowledge Organization Systems relate to natural language concepts, revealing that thesauri tend to represent atomic concepts suitable for reasoning, unlike other KOSs with decomposable terms.

Contribution

It provides an empirical comparison of KOSs using NLP techniques, highlighting the ontological nature of SKOS concepts across different systems.

Findings

Thesauri tend to represent atomic concepts that are less divisible.

Subject Headings and Classification Schemes include more decomposable terms.

Atomic concepts are more suitable for inference and reasoning in the Semantic Web.

Abstract

The vehicle to represent Knowledge Organization Systems (KOSs) in the environment of the Semantic Web and linked data is the Simple Knowledge Organization System (SKOS). SKOS provides a way to assign a URI to each concept, and this URI functions as a surrogate for the concept. This fact makes of main concern the need to clarify the URIs' ontological meaning. The aim of this study is to investigate the relation between the ontological substance of KOS concepts and concepts revealed through the grammatical and syntactic formalisms of natural language. For this purpose, we examined the dividableness of concepts in specific KOSs (i.e. a thesaurus, a subject headings system and a classification scheme) by applying Natural Language Processing (NLP) techniques (i.e. morphosyntactic analysis) to the lexical representations (i.e. RDF literals) of SKOS concepts. The results of the comparative analysis reveal that, despite the use of multi-word units, thesauri tend to represent concepts in a way that can hardly be further divided conceptually, while Subject Headings and Classification Schemes - to a certain extent - comprise terms that can be decomposed into more conceptual constituents. Consequently, SKOS concepts deriving from thesauri are more likely to represent atomic conceptual units and thus be more appropriate tools for inference and reasoning. Since identifiers represent the meaning of a concept, complex concepts are neither the most appropriate nor the most efficient way of modelling a KOS for the Semantic Web.