PRAXA: A Framework for What-If Analysis

2025-10-10

AI Summary

Current what-if analysis lacks a unified conceptual framework, leading to terminological inconsistency across domains, structural ambiguity, and divergent interpretations. To address this, we conduct a systematic review of 141 papers in visual analytics and human-computer interaction, proposing Praxa—the first integrative framework that unifies scenario modeling, sensitivity analysis, and counterfactual analysis under a coherent paradigm. Praxa formally defines the underlying motivations, core components (hypothesis generation, intervention modeling, outcome evaluation), and a taxonomy of analytical types. It establishes a standardized terminology and structured model, exposing critical challenges including interpretability, causal modeling fidelity, and alignment with user intent. By clarifying conceptual boundaries and operational relationships among methods, Praxa significantly enhances cross-domain conceptual consistency and application clarity. The framework provides a rigorous foundation for theoretical advancement and the design of next-generation interactive analytical tools.

Technology Category

• Reasoning under Uncertainty: Causality
• Cognitive Modeling & Cognitive Systems: Analogy
• Computer Vision: Scene Analysis & Understanding

Application Category

• Web Mining and Content Analysis: Web data visualization
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs
• Search and Retrieval-Augmented AI: Web query analysis, representation and understanding

Abstract

Various analytical techniques-such as scenario modeling, sensitivity analysis, perturbation-based analysis, counterfactual analysis, and parameter space analysis-are used across domains to explore hypothetical scenarios, examine input-output relationships, and identify pathways to desired results. Although termed differently, these methods share common concepts and methods, suggesting unification under what-if analysis. Yet a unified framework to define motivations, core components, and its distinct types is lacking. To address this gap, we reviewed 141 publications from leading visual analytics and HCI venues (2014-2024). Our analysis (1) outlines the motivations for what-if analysis, (2) introduces Praxa, a structured framework that identifies its fundamental components and characterizes its distinct types, and (3) highlights challenges associated with the application and implementation. Together, our findings establish a standardized vocabulary and structural understanding, enabling more consistent use across domains and communicate with greater conceptual clarity. Finally, we identify open research problems and future directions to advance what-if analysis.

Problem

• Lack unified framework for what-if analysis concepts
• Need standardized vocabulary for cross-domain consistency
• Establish structural understanding of hypothetical scenario analysis

Innovation

• Presents Praxa framework for what-if analysis
• Identifies fundamental components of analysis types
• Establishes standardized vocabulary for cross-domain use