[Numpy-discussion] grant proposal for core scientific Python projects (rejected)
ralf.gommers at gmail.com
Sat Apr 20 06:41:42 EDT 2019
On Thu, Apr 18, 2019 at 10:03 PM Joe Harrington <jh at physics.ucf.edu> wrote:
> Hi Ralf,
> The rejection is disappointing, for sure. Some good ammo for next time
> might be the recommendations in this report from the US National
> Academies of Science, Engineering, and Medicine:
Thanks, very useful!
> You can download a free PDF if you click around and give them an email
> address. There is some code on the cover that might raise a smile.
> Lorena Barba, Kelle Cruz, and many other community members contributed,
> both as committee members and as white-paper authors. While it's a
> report for NASA, the conclusions are strong and there is explicit
> support of investment in community resources like numpy, scipy, astropy,
> matplotlib, etc. Other agencies are asking similar questions, so I
> expect the report to get somewhat of a look at NSF, etc.
> A note on the Academies' process: A consensus study report must only
> include statements that no single member of the committee objects to,
> and the committee generally only includes senior members or people with
> a lot of relevant experience. There were stakeholders from some large
> modeling shops for whom openness might be a threat to their business
> model, in their eyes, and some of the senior members had never
> experienced the open-source environment and had bad experiences sharing
> software. This made for an interesting social dynamic, and prevented an
> all-out recommendation to forcibly open everything immediately. Given
> all that, I was ultimately pleased that we got full agreement on the
> recommendations we did make.
> So, some general thoughts on fundraising, not specific to this proposal:
> 1. Try NASA. The Administrator for Space Science, Thomas Zurbuchen, is
> pushing "open" very hard, given the success of open data in NASA Earth
> Science, and its positive impact on the economy in fields like
> agriculture and weather forecasting. He paid for the study above. Many
> grant programs specifically solicit proposals for open-source tools.
> There are also technology development programs in other parts of NASA
> than the Science Mission Directorate. Try contacting Dr. Michael New,
> who is Zurbuchen's deputy, and could direct you to appropriate programs.
> (Please, let's be coordinated and not all deluge the guy.)
I agree. NASA is the agency that probably understands our importance and
needs the best of any agency, and we have a lot of things to point to that
are important to them.
> 2. As suggested in another message, it's often easier to get support for
> a specific, targeted item as part of a big project or institute using
> that item, such as LSST or the black-hole group. There's a certain way
> to wend into those projects, usually originating from within. STScI has
> long devoted programmer resources, for example.
Maybe that is indeed the way to go. The real goal is maintenance/evolution
though, so it's a bit of a stretch. The strategy does work, see Dask &
Pangeo, however it would be nicer not to have to spend 80-90% of a budget
on things we can sell to get the 10-20% of funding for the things we think
are most important to do ....
> 3. There's such a thing as a share-in-savings contract at NASA, in which
> you calculate a savings, such as from avoided costs of licensing IDL or
> Matlab, and say you'll develop a replacement for that product that costs
> less, in exchange for a portion of the savings. These are rare and few
> people know about them, but one presenter to the committee did discuss
> them and thought they'd be appropriate. I've always felt that we could
> get a chunk of change this way, and was surprised to find that the
> approach exists and has a name. About 3 of 4 people I talk to at NASA
> have no idea this even exists, though, and I haven't pursued it to its
> logical end to see if it's viable.
I've heard of these. Definitely worth looking into.
> 4. I mostly lurk here, since being more actively involved in the early
> days of numpy docs,
I remember, that's what got me involved in the first place - thanks again
so maybe this one has been tried already, or is in
> the works. My apologies if so.
No we haven't tried it, perhaps we should.
> Think of development as a product to buy. You could put chunks of
> development up for sale, advertise them, and coordinate one or more
> groups buying them together. For something like an efficiency boost,
> you could price it according to the avoided cost of CPU resources for a
> project of a given size (e.g., somewhat below the net present value of
> avoided future AWS cycles for the projects buying it). It would be like
> buying a custom-built data pipeline, except that once you buy it,
> everyone gets it. This might mean scoping out a roadmap of
> improvements, packaging them into fundable projects with teams ready to
> go, pricing them, advertising them to specific customers and in trade
> media and shows, and making sales pitches.
This sounds good. It's what I hope places like Quansight Labs (where I just
started working) can help with. Same for Ursa Labs (focuses on Apache
Arrow, may connect back to Pandas) and Quantstack (xtensor numpy-like C++
lib, a faster conda solver, ...).
And with our roadmaps maturing and all projects now being under the
NumFOCUS umbrella (except scikit-learn, which has its own nonprofit), this
may become a way of the future. Jupyter is already further along this path.
We still have some growing up to do though:)
> This sounds really weird to us scientists, but it would work just like a
> regular purchase for services, which the government and industry are
> much more used to doing than donations to open-source projects.
> Don't just sell what the customer is buying, sell in the manner that the
> customer likes to buy.
Thanks for the feedback Joe!
> 5. And, keep trying grant proposals to NSF!
-------------- next part --------------
An HTML attachment was scrubbed...
More information about the NumPy-Discussion