A survey of knowledge organization systems of research fields: Resources and challenges

Abstract Knowledge organization systems (KOSs), such as term lists, thesauri, taxonomies, and ontologies, play a fundamental role in categorizing, managing, and retrieving information. In the academic domain, KOSs are often adopted for representing research areas and their relationships, primarily aiming to classify research articles, academic courses, patents, books, scientific venues, domain experts, grants, software, experiment materials, and several other relevant products and agents. These structured representations of research areas, widely embraced by many academic fields, have proven effective in empowering AI-based systems to enhance the retrievability of relevant documents, enable advanced analytic solutions to quantify the impact of academic research, and analyze and forecast research dynamics. We aim to present a comprehensive survey of the current KOS for academic disciplines. We analyzed and compared 45 KOSs according to five main dimensions: scope, structure, curation, usage, and links to other KOSs. Our results reveal a very heterogeneous scenario in terms of scope, scale, quality, and usage, highlighting the need for more integrated solutions for representing research knowledge across academic fields. We conclude by discussing the main challenges and the most promising future directions.