The 8 do’s and don’ts of graph visualisations.
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Transcript of The 8 do’s and don’ts of graph visualisations.
The 8 do’s and don’ts of graph visualizations.
SAS founded in 2013 in Paris | http://linkurio.us | @linkurious
Introduction.
● Linkurious is a graph visualization startup.
● We help companies understand graph data.
● Linkurious Enterprise, an enterprise-ready graph visualization platform.
● Customers like NASA, French Ministry of Finances, F500s.
● Partnerships with Data to Value, Neo Technology.
Why data visualization?
“The greatest value of a picture is when it forces us to notice what we never expected to see.” John Tukey (1962)
Some data is best represented as a network of nodes and edges.
What are X's connections? What is the influence of X in the network? What's the shortest path between X and Y?
Fraud, cyber-security, intelligence, medical research.
Why graph visualization?
PERSONname: Séb
age: 29
PERSONname: Jean
age: 31
LOCATIONname: Paris
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No need to define goals and expectations.
Your graph visualization will automagically have positive results.
Administrate, understand, monitor?
Advice #1: don’t set (business) objectives.
Why understand your users, their challenges, their habits.
You know what is right, why ask other people?
Developers, data scientists, analysts, public?
Advice #2: don’t consider your users.
You’re an artist and your graph visualizations need to entertain.
3D, colored backgrounds, fancy interactions.
Colors, sizes, glyphs, icons for nodes & colors and sizes for edges.
Advice #3: treat it as an art project.
You know best, why would your users need to ask their own questions?
A static visualization means your user is passively consuming (vs answering his own questions).
Zooming, hover & tooltips, expand on demand, search, filter, select.
Advice #4: don’t add interactivity.
Preparing and modelling your (graph) data is simple and intuitive.
Data preparation is always time-consuming, there are various ways to model graph data.
Test and iterate.
Advice #5: don’t think about your data.
Software engineer preparing a graph visualization project.
No need to provide guidance to interpret your graph visualization.
Help your users correctly interpret the information you provide.
Legend, labels, tooltips.
Advice #6: let the user figure it out.
It’s a contest, you need to display as many nodes and edges as possible.
Hardware constraints and cognitive constraints, hairball.
Display what matters (10s, not 100,000s).
Advice #7: always display everything.
You can do it all, your prototype will nicely move into production and be maintained.
Security, collaboration, stability, scalability, support, training.
Are you reinventing the wheel?
Advice #8: don’t worry about operational questions.
Disclaimer.
Some* of the advice in these slides should not be followed.
* actually all of the 8 advices should not be followed if you want your graph visualization project to be successful ;)