Notice

Below is a reading list for topics in Data Visualization. Some are general and apply to any type of data a few are directly related to Scientific Data. There are also some really good resources on some of the websites of visualization application creators like Visme, Venngage and Tableau. They want you to use their software and they are willing to teach you how.

A good introduction to the history of data visualization is the Chapter by Michael Friendly and the editors in the Handbook of Data Visualization (Friendly, Unwin, Chen and Hardle, 2006, ch 1). In this chapter most of the recent ,i.e. in the last 100 years, references are related to statistics. Why? Look at any chart, graph, infographic or the monthly advertising supplement for the supermarket specials, they all have a number somewhere behind the image. Someone has measured something somewhere that tells them people want to have certain information to make a decision and take an action. And in many cases that information is best conveyed using a picture. Data Visualization is mostly about turning numbers, which are difficult for people to process, into pictures, which are easy to process (reference). The picture when combined with a text explanation conveys a complete idea (wired article). 

Data Visualization is a tool for conveying complex information to people so that they can make a decision about an action. 

Where to Start?

Read the article on the history of Data visualization it can be downloaded using this Link ( https://www.researchgate.net/publication/226400313_A_Brief_History_of_Data_Visualization/link/00b7d526bc0a074119000000/download). It is an interesting read and there are more links in this article. 

The next one is the abstract by Zupanc and Romih (2017) ( https://www.researchgate.net/publication/308801956_How_to_Visually_Communicate_Complex_Scientific_Ideas) It gives a short list of five steps to take before you start preparing your visuals. These are important and taking these steps will save you a lot of time in the end. 

Read the article Death by PowerPoint: the slide that killed seven people ( https://mcdreeamiemusings.com/blog/2019/4/13/gsux1h6bnt8lqjd7w2t2mtvfg81uhx) . It highlights when poor communication of scientific data leads bad decision making and catastrophic results. What happened at NASA is NOT UNUSUAL or anomalous in any way. If you cannot access the Medium article the original is here ( https://www.edwardtufte.com/bboard/q-and-a-fetch-msg?msg_id=0001yB&topic_id=1). The Medium article is easier to read. 

The Northrop(2017) thesis is a quick read and informative as I compare the responses to different presentations of the same data. https://www.academia.edu/34243847/Converting_Complex_Scientific_Information_Into_Functional_Infographics_To_Enhance_Proposals_And_Presentations 

Then look at how and app creator sees visualization

https://visme.co/blog/examples-data-visualizations/

A good reference to book mark is the Dataviz site with it ebook of different charts and what they can represent. https://datavizcatalogue.com/ online catalogue of graphing and charting.