Foundation for mathematical and scientific computing: Discussion Notes


- R. Bradshaw: keep revenue generation and open source parts separate. Don't have a mixed message "donate money to my right hand; buy the stuff from my left hand".

- P. Ivanov brings up the Mozilla foundation as an example that has both a foundation and a company side to it. Though Mozilla isn't really selling anything, so perhaps this helps.

- Jarrod: EC2-style setup of preconfigured services as a source of revenue?

- Dav Clark: Monetizing an EC2 image preconfigured with all the right dependencies.

- Fernando/Robert: would running a company take too much time/effort away from the foundation work?

- William: people do want to pay for images running a Sage notebook. There *is* a market for these types of services, if they provide sufficient value.

- Audience: if you monetize these products, don't you end up precisely excluding the audience you want to support with free tools?

- Robert: I don't like the idea of paying so much for training.

- Merchandise? "Whenever I see that, I think I'd rather they not make stuff and just donate money".

- Audience: Keep the boundaries between foundation and company very clear.

- Stefan: to get people to give you money, you need to earn their trust. Be very clear upfront on how you'd spend their money before they give it to you. Make financial statements open as well.

- Jarrod: large scale fundraising? No replies...

- Proprietary software in research?

- Audience: instrumentation companies provide proprietary software for post-processing.

- There are differences regarding proprietary software in research and education; the argument above does not apply equally in an educational context.

- Training? William: tons of Sage days! Teaching undergrad/grad classes in departments that don't classically do this. The foundation could help by providing course materials to make this easier.

- Audience: a revenue model providing access to supercomputing resources?

- Reproducible research. William: definition? Jarrod: the ability to reproduce any figure/table from a computational publication easily, by having access to the code and data necessary.

- Audience: training about why open source/reproducible research is important could generate revenue.

days22/schedule/discussion (last edited 2010-07-06 09:03:44 by was)