The 8 most common mistakes in 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?

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No need to define goals and expectations.

Your graph visualization will automagically have positive results.

Administrate, understand, monitor?

Mistake #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?

Mistake #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.

Mistake #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.

Mistake #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.

Mistake #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.

Mistake #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).

Mistake #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?

Mistake #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 ;)

contact@linkurio.us