Data Visualisation & Open Source Technology

Working Group Scope 

Data Visualisation and Open Source Technology aims to support, address, and answer pertinent questions around Data Visualisation and Open Source Technology. The combination of these two subjects is natural in today’s environment given the powerful Data Visualisation tools within the Open Source languages available today. Some of the questions, amongst others, that we intend to address are:

• How do you safely use Open Source languages for analytics and submissions within a Regulatory environment?

• What are the potential uses of Open Source software within a company outside of data analysis for a submission?

• How can interactive visualisations be leveraged appropriately within a clinical environment?

• What are the best practices for creating powerful interactive visualisations?

Current Projects

Clinical Visual Analytics for Review and Submission (CVARS)

Communication of Version Metadata for Open-Source Languages

Comparing Analysis Method Implementations in Software (CAMIS)

Demonstrating Real-World Impact of Modernization of Statistical Analytics (MSA) Framework

Open Source Technology Adoption in Japan

PharmaForest: A Collaborative Repository of SAS Packages for Pharmaceutical Industry

Teal Enhancements for Cross-Industry Adoption

Open

Maya Gans is an Associate Director at Atorus Research, where she develops custom applications using R, JavaScript and Python for building software end to end, from user interface to technical implementation. She has extensive experience creating data visualisations and Shiny applications for the clinical trial space, and is a subject matter expert in htmlwidgets, package development and interactive data visualisation.

Maya holds a master of science in mycology. Her thesis explored the bacterial communities of a parasitic plant and its interactions with fungi and adjacent trees – work in ecology that provided a foundation for modelling complex, interconnected networks, and large datasets. Her special interests include data visualisation, interactive web applications, music analytics, and bridging the worlds of R and JavaScript.

Open

Peyman Eshghi is a Senior Principal Technical Lead at Johnson & Johnson, with 20 years of experience in R and data science. He is devoted to advancing R in regulated industries by promoting robust, reproducible tooling, community collaboration, and best practices in package development and visualisation. Peyman specialises in interactive data visualisation for pharmaceutical applications and is an active advocate for cross‑industry adoption of the teal framework.

Peyman earned a degree in joint mathematics and computer science and an MSc in Bioinformatics from Imperial College London. He serves on the R Consortium’s Infrastructure Steering Committee and contributes as an R package developer, currently maintaining the rAccess and uteals packages on CRAN.