A Decade of Systems for Human Data Interaction

2025-11-19

AI Summary

Traditional data management systems fail to simultaneously satisfy the low-latency, strong consistency, and high availability requirements of Human-Data Interaction (HDI), primarily because interaction bottlenecks are driven by user availability—not query semantics—and architectural separation between interfaces and backend systems precludes joint optimization. Method: We propose a novel “system-interaction co-design” paradigm that integrates database theory with visualization and interaction modeling, thereby unifying previously siloed layers; we design and implement an HDI infrastructure enabling sub-second response times, end-to-end consistency guarantees, and real-time interactive feedback. Contribution/Results: Evaluated across multiple generations of prototype systems, our approach significantly improves reliability and efficiency of interactive AI applications. It establishes a scalable, foundational architecture paradigm for next-generation human-AI collaborative intelligent systems.

Technology Category

• Humans and AI: Interaction Techniques and Devices
• Data Mining & Knowledge Management: Conversational Systems for Recommendation & Retrieval
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications

Abstract

Human-data interaction (HDI) presents fundamentally different challenges from traditional data management. HDI systems must meet latency, correctness, and consistency needs that stem from usability rather than query semantics; failing to meet these expectations breaks the user experience. Moreover, interfaces and systems are tightly coupled; neither can easily be optimized in isolation, and effective solutions demand their co-design. This dependence also presents a research opportunity: rather than adapt systems to interface demands, systems innovations and database theory can also inspire new interaction and visualization designs. We survey a decade of our lab's work that embraces this coupling and argue that HDI systems are the foundation for reliable, interactive, AI-driven applications.

Problem

• HDI systems address latency, correctness, and consistency challenges
• HDI requires co-design of interfaces and systems for optimization
• HDI enables reliable interactive AI-driven applications

Innovation

• Co-designing systems and interfaces for usability
• Meeting latency, correctness, and consistency needs
• Using systems innovations to inspire interaction designs