Techniques for visualising change over time in graphs

I'm looking to display a graph (network diagram, not a chart) and show its changes over time. Is there a standard or best way to do this, or any kind of 'network diff' tool?

I'm looking for an overview of the gener开发者_Go百科al layout decisions involved, i.e. a list of options and trade-offs to be made, and best-practice guidelines where these exist.

Wow. Not an easy question! I'm curious if anyone can come up with some authoritative resources for you.

I haven't found any standard or best practice documented anywhere from a design standpoint, nor do I know of any tool specifically designed for determining and displaying the changes, but I have some ideas.

First, a few technical notes. There's GraphML, which you can use (and extend) to represent your graph in a standard format, and there are some parsers available, and it works with Prefuse and probably other display libraries. It's just XML, though - nothing too special. Creating the "diff" by comparing two GraphML files should be pretty simple.

The really interesting part is how to communicate the differences to the user.

In all cases, you should have a visual indicator for nodes and edges that are added or removed. You may use color, showing existing nodes as something neutral, say gray, new nodes as green, and removed nodes as red. There are lots of options.

You might find this slideshow interesting.

It's probably obvious, but, over time, the nodes should not move more than necessary to adapt to the new state of the graph - the layout should evolve, not start from scratch for every state. This is crucial for comparing the states.

1. Side-by-side before/after comparison. Present before and after snapshots of the same graph side-by-side. If your graph is very large and complicated, a side-by-side layout may be impractical. You could try overlaying one graph over the other, though that is likely to be disorienting.

2. Side-by-side series comparison. AKA small multiples. Same as above but showing as many points in time as is useful. Even more restrictive than before-after in terms of how much space required, and difficult for.

3. Animate a single graph. I think the most intuitive method is to smoothly animate the graph changes, though a choppy slideshow could work if the changes between slides are not too drastic.

Showing details. If useful, you can spell out the change event details in a few different ways.

1. Show labels on the graph node (could be interactive if there are too many to show at once)

2. Show a list in a sidebar / legend. Nice if reading the progression of changes is useful, but harder to connect to the visual.

3. Show a timeline instead of a list. This shows the 'real' progression of events better than a simple list, which gives the impression that all the events are evenly spaced over time.

What you actually choose to do would depend largely on the nature of your dataset and your goals. A simple graph of a few dozen nodes and a few changes is a much different challenge than a huge network, like say every constellation in the night sky!

Here is an interesting study: http://publik.tuwien.ac.at/files/PubDat_198995.pdf

This paper presents a prototype, and user tests will be published soon in:

P. Federico, W. Aigner, S. Miksch, F. Windhager, M. Smuc: "Vertigo zoom: combining relational and temporal perspectives on dynamic networks"; accepted as talk for: 11th International Working Conference on Advanced Visual Interfaces (AVI2012), Capri Island; 2012-05-21 - 2012-05-25; in: "Proceedings of the 11th International Working Conference on Advanced Visual Interfaces (AVI2012)", ACM, (2012), ISBN: 978-1-4503-1287-5.

http://ieg.ifs.tuwien.ac.at/~federico/pub.php

Your question is kind of general, I'm not clear exactly what kinds of analysis you are aiming for. The are several network analysis packages that have some dynamics capacity. Gephi is one. The networkDynamic and ndtv R packages provide tools for representing and visualizing dynamics as animations and static layouts (disclaimer: I'm a maintainer)