A Curated Literature Database for Monitoring More Than 30 Years of Ansys Granta Product Usage

TL;DR

This paper introduces a structured, reproducible database for monitoring over 30 years of Ansys Granta product usage, enabling analysis of adoption, impact, and application domains through semi-automated data collection and expert curation.

Contribution

It presents a novel framework and curated database that consolidates diverse evidence of Ansys Granta usage for quantitative analysis and strategic decision-making.

Findings

Database contains over 1,100 curated records as of 2025.

Enables rapid retrieval of case studies and literature reviews.

Highlights dominant application domains and key institutions.

Abstract

Engineering and materials software is increasingly difficult to track in the scholarly and technical literature because publication volume is growing rapidly and software citation practices remain inconsistent. This is particularly true for the Ansys Granta product family, which is used for materials education, materials and process selection, sustainability-driven design, and enterprise materials information management. We present a structured and reproducible framework to consolidate evidence of \emph{operational} Granta usage and to support quantitative monitoring of adoption patterns, application domains, and technical impact. The framework is implemented as a curated reference database in \textit{Ansys Granta MI Enterprise}: bibliographic metadata are ingested semi-automatically (e.g., via DOI and citation-file parsing) and complemented by expert curation of usage descriptors (product, context, application domain, and technical depth), with relational links to authors and institutions. Downstream analytics are performed with Python, dashboards, and bibliometric/network visualization tools to enable reproducible querying and reporting. As of September~2025, the database contains more than 1{,}100 curated records spanning journals, conferences, theses, books, patents, standards, and reports, and supports rapid retrieval of validated case studies, reproducible literature reviews, and technology scouting. Example analyses highlight dominant domains, key institutions, and recurring integrations with CAD/CAE/FEM environments. Overall, the approach converts heterogeneous software-usage evidence into structured, analyzable knowledge to improve visibility of engineering software impact and to support evidence-based assessment and strategic decision-making.