DIAS – A Python package and app for design informatics analysis

The Design Informatics Analysis System (DIAS) is a user-friendly statistical analysis software developed to support design research. It reorganizes and classifies 77 statistical methods according to the unique scenarios in design research. Accompanied by a comprehensive user manual, it facilitates users in effectively applying these methods in practice. DIAS enhances the analytical workflow by automating data preprocessing, automatically selecting commonly used parameter settings based on the characteristics of the data, enabling one-click analysis, and generating professional-quality reports. DIAS aids design researchers with limited statistical expertise in performing quantitative analyses, thereby progressively diminishing their dependence on solely empirical approaches.

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Publication Details

Journal
SoftwareX
Published
2026-06-12
DOI
https://doi.org/10.1016/j.softx.2026.102787
Primary Topic
Architecture and Computational Design
Type
article
Field-Weighted Citation Impact
0.00

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article

DIAS – A Python package and app for design informatics analysis

Yingrui Chi
SoftwareX
Architecture and Computational Design
article

DIAS – A Python package and app for design informatics analysis

Yingrui Chi
article en

Abstract

The Design Informatics Analysis System (DIAS) is a user-friendly statistical analysis software developed to support design research. It reorganizes and classifies 77 statistical methods according to the unique scenarios in design research. Accompanied by a comprehensive user manual, it facilitates users in effectively applying these methods in practice. DIAS enhances the analytical workflow by automating data preprocessing, automatically selecting commonly used parameter settings based on the characteristics of the data, enabling one-click analysis, and generating professional-quality reports. DIAS aids design researchers with limited statistical expertise in performing quantitative analyses, thereby progressively diminishing their dependence on solely empirical approaches.

SoftwareXVol. 35
Università di Camerino (IT)
China Scholarship Council
Openalex Percentile: Top 2%
Architecture and Computational Design
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