User Experience Evaluation of Visual Analytics Systems

• Grant number: 23/17681-2
• Support Opportunities: Scholarships abroad - Research Internship - Post-doctor
• Effective date (Start): April 30, 2024
• Effective date (End): July 12, 2024
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Maria Cristina Ferreira de Oliveira
• Grantee: Eliane Zambon Victorelli
• Supervisor: Petra Isenberg
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Research place: Centre Inria De Saclay, France
• Associated to the scholarship: 22/08651-0 - User experience evaluation in interaction with visual analytics systems, BP.PD

Abstract

Visual Analytics solutions are being adopted in multiple activities, taking advantage of the benefits of integrating machine learning algorithms with visual representations of data and models for user-driven data analysis. Users from diverse areas and knowledge domains interact intensively with these systems, and ensuring an effective, pleasant, and productive interaction is necessary. This study aims to propose and validate instruments to support the evaluation of the user experience with Visual Analytics systems. Instruments to guide the evaluation planning will be developed to support researchers and practitioners in selecting adequate metrics and methods. As an instrument to carry out measurements, we intend to propose a measurement scale and validate it in experimental studies with Visual Analytics users. The expected results are a guide and a catalog to facilitate evaluation planning, and a validated measurement scale to permit a quick user experience judgement. The effort of developing these instruments will hopefully contribute to improving our understanding of the metrics that convey information about the user interaction with such products. Our study will support future researchers and practitioners in conducting more effective evaluations, which in turn contributes to the development of better Visual Analytics systems concerning the user experience.