Center for Analysis and Design of Intelligent Agents

Contribution Section	Describe your idea - not how it has been evaluated. You may reference related work, but keep it to a minimum and specific (i.e. no “review of what so-and-so did” in the Contribution section!). Give it a title that describes its contents.
Method	Isolate the key ideas - make sure you give them all the space they need.
Trim off superfluous ideas.	- This can be painful: How can you trim off those interesting little things that somehow you just know the world absolutely needs to hear about? Trick: Tell yourself you'll write another paper where your shaved-off ideas will go.
Do not cross-reference too much between sections	It is a common difficulty to keep the discussion on the topic of the contribution in the Contribution section, without referencing the evaluation results. This should be avoided at all cost. The best papers are the ones where the results of the evaluation are not given away before the Results section. And each section can be read mostly without having to jump back and forth all the time.
This is your stuff	Make it look as good as it can look!

Evaluation & Results	This section proves that your idea is solid
Describe the evaluation method thoroughly but succinctly	Nothing is more annoying than long-winded discussion of the evaluation method. Just the facts, ma'am!
Evaluation method description: should have a one-to-one correspondence with the results section	This means that any table, graph, or illustration in the results should have a directly corresponding statement/motivation/ discussion in the Evaluation section. If you feel like you have to include tables whose existence are not discussed – and hence not justified – in the evaluation section, make sure they are either motivated by a surprise finding or else put them in a Discussion section.

Be clear
Always summarize what the tables/graphs/etc. say with your own words, before drawing conclusions	E.g.: Do not say “As can be seen in Graph 1, my routing algorithm works best.” Say, “As can be seen in the comparison between the three routing algorithms, A, B and C, the algorithms with partial information about network topology have an advantage in networks above a certain size (point X, Graph 1). Among these, my algorithm, C, gets the best result.”
Captions: Equally important as the graph	Make sure your graph contains all the information necessary to interpret the graphics: Title, caption and legend should be written with the same care as the title of your paper and your abstract!!
Two principles	The clearest presentation - make the job easy on the reader The biggest impact - try to make the point as strongly as you possibly can.

Scientific papers are for people	People have limited capacity processors. Make sure you direct them to the most important points through the right data/information presentation methods.
Select the right format
When not to use graphs	When the graph contains too much or too little data
Common mistakes in graphs	Equating two-dimensional space with one-dimensional space Forget to indicate that an axis does not start at zero Using pie charts for open-ended scales examples (scroll down)
9 tips to make your graphs great (based on: source)	1. decide on a clear purpose 2. convey an important message 3. draw attention to the message, not the source 4. experiment with various options and graph styles 5. use simple design for complex data 6. make the data 'speak' 7. adapt graph presentation to suit the data 8. ensure that the default visual perception process of the reader is easy and accurate 9. avoid ambiguity