Deigmata: A User-Centered Visualization Tool for Knowledge Graph Exploration

In the field of Information Science, Knowledge Graphs (KG) have emerged as a prominent approach to Knowledge Organization (KO) and Knowledge Representation (KR), supported by Knowledge Organization Systems (KOS) such as taxonomies and thesauri. KGs provide scalable, ontology-enriched structures for managing large volumes of data. Despite criticisms concerning limited semantic expressiveness and modeling quality, KGs remain essential in big-data contexts, where exploratory analysis and visualization are fundamental to identifying patterns and generating insights. Scientific literature indicates that many visualization approaches are algorithm-centered or tool-oriented, often neglecting user-centered design and cognitive ergonomics. To address these limitations, this study aims to identify and evaluate visualization techniques that support user-centered design, focusing on cognitive and usability needs in exploratory and interactive analysis. The methodological approach is based on Design Science Research (DSR), combining a Systematic Literature Review (SLR) and semi-structured interviews to identify user requirements and inform the design of visualization solutions. As a result, the Deigmata system was developed—a user-centered KG visualization tool that facilitates collaborative analysis across multiple user profiles. The tool integrates interactive process triggers that reduce exploration barriers, particularly for non-expert users.