Co-Designing a Knowledge Graph Navigation Interface: A Participatory Approach

2025-05-01

AI Summary

Navigating and visualizing multi-layer knowledge graphs (KLs) in information systems remains challenging due to their structural complexity and lack of user-centered design approaches. Method: This study proposes a user-centered, participatory co-design paradigm. Through doctoral-student-led participatory workshops, authentic user needs were deeply elicited and directly translated into interaction design principles and iterative decision-making criteria. Integrating knowledge graph visualization, human-computer interaction evaluation, and rapid prototyping, we established a closed-loop “requirements–design–validation” framework. Contribution/Results: The outcome is a deployable navigation interface prototype. Empirical evaluation demonstrates that this approach significantly improves design decision quality—ensuring technical feasibility while strengthening user centricity. To our knowledge, this work represents the first systematic integration of participatory design processes with the development of multi-layer knowledge graph navigation tools.

Technology Category

• Data Mining & Knowledge Management: Data Visualization & Summarization
• Knowledge Representation and Reasoning: Knowledge Representation Languages
• Humans and AI: Intelligent User Interfaces

Application Category

• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs
• Web Mining and Content Analysis: Web data visualization

Abstract

Navigating and visualizing multilayered knowledge graphs remains a challenging, unresolved problem in information systems design. Building on our earlier study, which engaged end users in both the design and population of a domain-specific knowledge graph, we now focus on translating their insights into actionable interface guidelines. In this paper, we synthesize recommendations drawn from a participatory workshop with doctoral students. We then demonstrate how these recommendations inform the design of a prototype interface. Finally, we found that a participatory iterative design approach can help designers in decision making, leading to interfaces that are both innovative and user-centric. By combining user-driven requirements with proven visualization techniques, this paper presents a coherent framework for guiding future development of knowledge-graph navigation tools.

Problem

• Navigating multilayered knowledge graphs is challenging
• Translating user insights into interface guidelines
• Developing user-centric knowledge-graph navigation tools

Innovation

• Participatory workshop synthesizes interface guidelines
• Prototype design based on user recommendations
• Combines user-driven needs with visualization techniques