The missing millions Democratizing computation and data to bridge digital divides and increase access to science for underrepresented communities - A. Blatecky *et al*

This resource first appeared in issue #102 on 27 Nov 2021 and has tags Becoming A Manager: Diversity

The missing millions: Democratizing computation and data to bridge digital divides and increase access to science for underrepresented communities - A. Blatecky et al

Research computing and data are increasingly important for STEM fields, so if we want STEM - and R&D careers - to be available to all, we need to make sure there are as few barriers as possible to being fluent with computing and digital research infrastructure[*], and to having it accessible.

More selfishly - we readers of this newsletter are all pretty familiar with how hard it is to hire in research computing and data. So we have a pretty strong and direct interest in making sure as many people as possible have access to and build skills and understanding in research computing and data technologies.

We know, though, that research computing and data as a community is less diverse than academia or tech as a whole - and those communities are not stellar examples of diversity, equity, and inclusion.

This is a long and frankly somewhat dispiriting read. It’s not great out there. But there are some pretty solid recommendations in this report - and it’s NSF-funded, so there’s real hope the recommendations would be taken up. Recommendations we on the ground can actually engage in are things like:

• Expand investments in data and software to make sure systems are as accessible and useful as possible
• Expand into non-traditionally computing and data heavy fields, and into areas like distributed and edge technologies, for similar reasons
• Engage in long-term inclusive community building
• Improve racial, gender, and other forms of inclusion

By the way, one finding from this report stuck out, as it’s one of the tenets of this newsletter:

It is computing, and software, and data

I can not agree with this enough. Focusing on research software development, or systems, or data management, in isolation is a mistake. In 2021, those lines are so blurred as to be meaningless, and it builds silos where there ought to be none.

[*] sorry, but I just hate the NSF term “cyberinfrastructure”.