Knowledge Organization Ecosystems (KOE) constitute an analytical metaphor for understanding the growing complexity of contemporary information environments, characterized by interdependence, automation, continuous updating, and algorithmic mediation. Traditionally, Knowledge Organization has relied on relatively stable structures, such as documentary languages and ontologies. However, the incorporation of artificial intelligence and digital infrastructures has expanded this scope, requiring conceptual frameworks capable of integrating epistemological, sociotechnical, and ethical dimensions. This article critically examines KOE as ecosystems composed of people, technologies, and organizations, proposing an interpretative perspective that articulates epistemic plurality, distributed governance, and sociotechnical responsibility. Methodologically, the study is based on an analytical and conceptual review of 26 texts selected for thematic relevance, of which 10 form the theoretical core used to characterize KOE and compare them with Knowledge Organization Systems (KOS). The results indicate that KOS provide semantic stability and terminological control, whereas KOE incorporate collaborative dynamics, algorithmic mediation, and ethical governance, enabling a more comprehensive understanding of knowledge organization in artificial intelligence contexts. The article concludes that the ecosystem paradigm enhances the field’s explanatory capacity by recognizing the distributed, ethical, and adaptive nature of contemporary knowledge mediation systems, thereby establishing KOE as a necessary methodological evolution within Information Science.
Lima et al. (Mon,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: