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resources.qmd
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---
title: "Resources & references"
description: "A list of useful resources and related initiatives."
page-layout: full
title-block-banner: true
---
## Graphical principles initiative
* A [Rstudio Rviews webinar](https://resources.rstudio.com/webinars/effective-visualizations-for-data-driven-decisions) on graphics principles and visR, and [blog post](https://blog.rstudio.com/2020/04/16/effective-visualizations-for-credible-data-driven-decision-making/)
* R in Pharma 2020 talk on [EVC](assets/EVC_Magnusson_RPharma2020.pdf), [slides](assets/EVC_Magnusson_RPharma2020.pdf) and [video](https://www.youtube.com/watch?v=TNMC-Ota29g&list=PLMtxz1fUYA5DSpVzwR7bT37IZqCT4SH5a&index=4).
* The [xGx](https://opensource.nibr.com/xgx/) initiative from Novartis PMX.
* [BBS next generation](assets/EVC-Baillie-BBS-17April2024.pptx) seminar April 2024
## Webinar resources
EVC [webinar materials](https://github.com/GraphicsPrinciples/webinar):
* For the (ASCPT Pharmacometrics & Pharmacokinetcs (PMK) Community [Webinar](https://www.ascpt.org/Member-Services/Member-Tools/Webinar-Resources) 15Jan2021 (part1) and 22Jan2021 (part2)
## Data visualization initiatives:
* PSI special interest group on [visualisation](https://www.psiweb.org/sigs-special-interest-groups/visualisation) (VIS SIG).
* The PSI VIS SIG [Wonderful Wednesdays](https://www.psiweb.org/sigs-special-interest-groups/visualisation/welcome-to-wonderful-wednesdays) webinar series, [datasets](https://github.com/VIS-SIG/Wonderful-Wednesdays) and [blog](https://vis-sig.github.io/blog/).
* The [CTSpedia](https://www.ctspedia.org/do/view/CTSpedia) initiative.
* The STRengthening Analytical Thinking for Observational Studies [(STRATOS)](https://www.stratos-initiative.org/) visualisation [panel](https://www.stratos-initiative.org/node/61)
* [Slides](assets/ROeS-SRATOS-Baillie-10Sept2021.pdf) from [ROeS 2021](http://datascience.sbg.ac.at/ROeS2021/) [STRATOS](https://www.stratos-initiative.org/) session introducing the visualisation panel.
* The [visR initiative](https://openpharma.github.io/visR).
## Online resources:
* [Trees, maps and theorems](https://www.principiae.be/book/) by Jean-luc Doumont
* [Data visualization](https://socviz.co/) by Kieran Healy - includes R code with examples.
* [Fundamwentals of data vizualisation](https://serialmentor.com/dataviz/) by Claus Wilke - also includes R code with examples.