Envisage: Towards Expressive Visual Graph Querying

2025-07-16

AI Summary

Existing visual graph query tools support only simple, deterministic queries, failing to accommodate ambiguous or evolving user intents. To address this, we propose Envisage—the first visual graph query system enabling interactive graph-structure construction, flexible definition of parameterized rules, and a closed-loop workflow encompassing query formulation, semantic validation, progressive execution, and result analysis. Its key contributions are: (1) a fuzzy intent modeling mechanism that allows users to iteratively refine queries via an intuitive visual interface; (2) a formal graph rule verification framework coupled with parameterized instantiation to ensure semantic correctness; and (3) integration of progressive graph traversal techniques for real-time feedback during query execution. Two in-depth case studies and interviews with 14 domain-expert graph analysts demonstrate that Envisage significantly enhances expressiveness, comprehensibility, and usability for complex graph querying tasks.

Technology Category

• Data Mining & Knowledge Management: Intelligent Query Processing
• Machine Learning: Graph-based Machine Learning
• Knowledge Representation and Reasoning: Qualitative Reasoning

Application Category

• Graph Algorithms and Modeling for the Web: Querying, indexing, and retrieval in Web-related graphs
• Web Mining and Content Analysis: Web data visualization
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

Graph querying is the process of retrieving information from graph data using specialized languages (e.g., Cypher), often requiring programming expertise. Visual Graph Querying (VGQ) streamlines this process by enabling users to construct and execute queries via an interactive interface without resorting to complex coding. However, current VGQ tools only allow users to construct simple and specific query graphs, limiting users' ability to interactively express their query intent, especially for underspecified query intent. To address these limitations, we propose Envisage, an interactive visual graph querying system to enhance the expressiveness of VGQ in complex query scenarios by supporting intuitive graph structure construction and flexible parameterized rule specification. Specifically, Envisage comprises four stages: Query Expression allows users to interactively construct graph queries through intuitive operations; Query Verification enables the validation of constructed queries via rule verification and query instantiation; Progressive Query Execution can progressively execute queries to ensure meaningful querying results; and Result Analysis facilitates result exploration and interpretation. To evaluate Envisage, we conducted two case studies and in-depth user interviews with 14 graph analysts. The results demonstrate its effectiveness and usability in constructing, verifying, and executing complex graph queries.

Problem

• Enhancing expressiveness in visual graph querying for complex scenarios
• Supporting intuitive graph structure construction and flexible rule specification
• Addressing limitations of current tools in underspecified query intent

Innovation

• Interactive visual graph querying system
• Intuitive graph structure construction
• Flexible parameterized rule specification