This was the discussion session I chose. These are just notes of what was being said, so they might be a little disconnected.
+ Words don't necessarily mean what you think they mean. This can be a problem in collaborative model development.
+ This is why ontologies are so important.
+ How to get biologists to use these ontologies, when biologists generate terms and definitions, often without regard to what already exists?
+ Symbols in biology are not standardized.
+ Any science has joint words that mean different things. While there are advantages to having the same definitions from a computational perspective, we can just use whatever words are normal in the community, but just make clear the definition. It's could be a translation rather than unification issue.
+ Many people have problems with open access ontologies (i.e. someone else could change what you had spent ages doing).
+ Remember, open access != open editing.
+ What people should realize, if you start doing interdisciplinary work, you really need to change the way you do your research. You need to pay attention to what the other disciplines say.
+ While it is an advantage to take a subject specialism into SB, everyone needs to understand that the other disciplines are useful. Nobody will be able to be a pure SB "jack of all trades". Interdisciplinarity should be taught at an earlier level. Funding bodies are stressing the need for a group of people with different skills.
+ getting Professors and other scientists to actually work for 3, 6 or 9 months or more in other disciplines (in CISBAN, a statistician is being a wet lab biologist, for example) is very useful.
+ Allow your scientists to sit in on undergraduate lectures that allow them to learn the solid understanding of the other disciplines. People can learn that subjects don't work differently, and allows them to realize that this means that terminologies also might work differently.
+ Different disciplines allow you to train your mind in different ways.
Please note that this post is merely my notes. They are not guaranteed to be correct, and unless explicitly stated are not my opinions. They do not reflect the opinions of my employers. Any errors you can happily assume to be mine and no-one else's. I'm happy to correct any errors you may spot – just let me know!