SKO Types: an entity-based scientific knowledge objects metadata schema

Abstract

Purpose – This paper aims to propose an entity-based scientific metadata schema, i.e. Scientific Knowledge Object (SKO) Types. During the past 50 years, many metadata schemas have been developed in a variety of disciplines. However, current scientific metadata schemas focus on describing data, but not entities. They are descriptive, but few of them are structural and administrative. Design/methodology/approach – To describe entities in scientific knowledge, the theory of SKO Types is proposed. SKO Types is an entity-based theory for representing and linking SKOs. It defines entities, relationships between entities and attributes of each entity in the scientific domain. Findings – In scientific knowledge management, SKO Types serves as the basis for relating entities, entity components, aggregated entities, relationships and attributes to various tasks, e.g. linked entity, rhetorical structuring, strategic reading, semantic annotating, etc., that users may perform when consulting ubiquitous SKOs. Originality/value – SKO Types can be widely applied in various digital libraries and scientific knowledge management systems, while for the existing legacy of scientific publications and their associated metadata schemas.