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Supporting NASA Earth science research teams’ migration to the cloud

NSIDC User Working Group, September 16, 2021

GES DISC User Working Group, September 8, 2021

Slides: https://nasa-openscapes.github.io/about.html#slides

All artwork by Allison Horst; @allison_horst

OPENSCAPES: BETTER SCIENCE FOR FUTURE US

Julia Stewart Lowndes

Co-Director, Openscapes

National Center for Ecological Analysis and Synthesis (NCEAS), UC Santa Barbara (UCSB)

lowndes@nceas.ucsb.edu; @juliesquid

Erin Robinson

Co-Director, Openscapes

Metadata Game Changers

erin@metadatagamechangers.com

@connector_erin

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Important mindset for (environmental and Earth) science

A real investment, particularly for data-intensive research

Better Science

more open, reproducible, efficient
more diverse, equitable, inclusive, kind

Future Us

ourselves, teams, communities
next hour, week, decades

Better science is science that is more open and reproducible, it's more diverse, equitable, inclusive, and just, and it is for Future Us: the ideas of our teams, and communities, and who will be joining and continuing our work, whether that is next week or next century. Future Us is an important mindset for science and society at large, and particularly important in environmental science.

it's particularly important for us in data-intensive science. Open science and collaboration is really critical

“Future Us” builds from the idea of “Future You/Future Self” being your most important collaborator (see Wilson et al 2017) but with a team science mindset promoting diversity, equity, inclusion, and belonging. How can you work today so that someone other than yourself could reproduce/contribute tomorrow? We describe this more in Lowndes et al. 2019

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Open science as part of the climate movement

www.allwecansave.earth

www.ipcc.ch

“ ‘We’ speaks to the collective, to collaboration, to community, to the relational work at hand. Addressing the climate crisis...will take everyone.

‘We’ speaks to justice, to how we do the work that needs doing and whose contributions are valued. We cannot, we must not, go it alone”

Ayana Elizabeth Johnson & Katharine Wilkinson, All We Can Save

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Openscapes helps research groups reimagine data-intensive research, develop modern skills that are of immediate value to them, and cultivate collaborative and inclusive research communities.

Engage • Empower • Amplify

openscapes.org

@openscapes

Supercharge your research (Lowndes et al. 2019, Nature)

Open software means kinder science (Lowndes 2019, Scientific American)

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Openscapes Champions

A mentorship program that helps researchers move from lonely science by exploring the open science landscape with their teams

We think about open science like a landscape. Our flagship program is Openscapes Champions, which is an open data science mentorship program for teams. We help researchers move from sad and lonely science like the animals on the bottom left to team science as they identify their common needs and start navigating the landscape together with a cohort of their peers. We help them orient to existing pathways in the landscape created by open science communities, and we also build new trails when there is a need. We think a lot about safety. How to make it safe to participate in open science for more people

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Openscapes Champions is our flagship program: a remote-by-design, cohort-based mentorship program that guides teams through the open data science landscape, empowers them as leaders, and welcomes them as part of the growing open science movement.

Designed to onboard teams to open data science community tooling & practices:

Participants: Cohort of 7-10 teams (team leads & members) with diverse skill sets and needs
Duration: 2-4 months (4 hr/months)
Deliberate focus on empathy, inclusion & kindness
Mentored-coached Mozilla-style: remote-by-design
Lesson series focus on tooling, norms, and leadership for better science in less time

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Normalize talking about data

creating place and space

Identify and address shared needs

learn existing tooling, practices

Think ahead for Future Us

reproducibility, inclusion, role-modeling

Openscapes Champions Program

Focus on the common:

People <> Process <> Technology

Lowndes et al . 2019, Nature

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Create space for data discussions

[Sea]side Chats

Individual teams

2x/month

Champions Cohort Calls

~7 research teams

2x/month

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Create place for collaboration

Lab GitHub Organizations

Code, practices, resources, conversations

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Focus on the common

Identify and address shared needs

Prioritize inclusion throughout

Example:

Growth Mindset & GitHub

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Biggest impact: research teams work more openly & effectively together.

Teams reframe analysis as collaborative effort not an individual burden, and use open source tools to streamline work/life for Future Us.

less reinventing & loneliness • grant money goes further • co-creating norms promoting diversity, equity & inclusion • new folks onboard to projects faster

Reimagining the way we work, share, think

“This isn’t just about coding & GitHub, it’s about changing the way we do science.”

- Dr. Malin Pinsky, Rutgers

“Openscapes has created a new way of thinking about merging empathy and science. That's an invaluable gift to me.” - Dr. Halley Froehlich, UCSB

“This program has honestly completely re-made how I think about my science. [It is] a supportive training course for moving your lab towards open science, that meets you where you are.”

- Dr. Chelsea Wood, U Washington

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LP DAAC User Working Group, August 2021: https://wiki.earthdata.nasa.gov/pages/viewpage.action?pageId=214140156

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NASA EarthData & Openscapes

Supporting NASA Earth science research teams’ migration to the cloud

https://nasa-openscapes.github.io

The overarching vision is to support scientific researcher teams using NASA EOSDIS data as they migrate their workflows to the cloud. We are doing this working with NASA Distributed Active Archive Centers (DAACs) over three years by:

Develop a cross-DAAC Mentor community of collaborative cloud data instructors, that co-create, curate, and use shared resources (“make once, use often”)
Empower science teams through the Champions program to migrate their download- intensive data analysis workflows to the cloud and open, kinder science
Scale the Openscapes Champions program with DAAC Mentors to support more teams transforming their workflows towards open, kinder science and the cloud

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NASA Openscapes Mentors

Aaron Friesz

Catalina Oaida

Jack McNelis

Makhan Virdi

Matt Tisdale

Vishal Bagadia

Amy Steiker

Luis Lopez

Andy Barrett

Christine Smit

Jennifer Adams

Alexis Hunzinger

Kumar Ramasubramanian

Shubhankar Ghalot

Iksha Gurung

Create space:

Mentors Cohort Calls & Co-Working

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Mentor Cohort activities

Spring 2021

Build a DAAC community of practice through twice monthly Openscapes Cohort Calls, a Carpentries Intro Python/Git Workshop, and Carpentries Instructor Training
Practice teaching in a style to prepare them for the Openscapes Champions cohort (~early 2022) and upcoming workshops
Support Mentors towards establishing a common set of tutorials that they can then build off their DAAC-specific and science examples. 2i2c.

Summer/Fall 2021

https://nasa-openscapes.github.io/mentors.html#mentor-cohort-2021

Focus on growing momentum with Mentors to continue Cookbook development and workshop prep
Continue to build relationships with Early Adopters to help incorporate feedback

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Identifying common parts of research with NASA EarthData on the cloud

Catalina Oaida, PO.DAAC

The first was stepping back and thinking about the common parts of our data analysis.

This is HW’s conceptual diagram for data science where he illustrates the importance of tidying data first before beginning to ask your research question. this was criticatl for us to separate out the common parts we were all reinventing so we could collab on those common parts and then give more creative energy and time for the science.

Less reinventing

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This is probably the most impactful figure in my science-life. The idea that no matter your question, your study system, etc, you will need to go through these deliberate steps if you’re working with data. And it’s really in this grey box of Understanding where the Science starts. So this is separating your science questions from this first part, which is import and tidying.

The idea of tidying your data first and then being streamlined with the tools you can use for science is amazing. So not starting the science too soon. I’ve been burned by this, and it means forever building bespoke approaches to accommodate weird data formatting. And knowing that tidying data takes a huge percentage of analysis time

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EarthData Cloud Cookbook

In active, modular, open development

nasa-openscapes.github.io/earthdata-cloud-cookbook

Create place:

GitHub Org + Quarto

Purposeful documentation

Lives in one place, importer workflow
Researcher-focused: tutorials & how-to guides

quarto.org

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Live Demo

EarthData Cloud Cookbook

Support Mentors to co-create a common set of Cloud tutorials that they can then build off their specific science tutorials

https://nasa-openscapes.github.io/earthdata-cloud-cookbook

Common

Cloud

Foundation

NASA Specific Science Tutorials

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Identifying the common parts of documentation

documentation.divio.com

The first was stepping back and thinking about the common parts of our data analysis.

This is HW’s conceptual diagram for data science where he illustrates the importance of tidying data first before beginning to ask your research question. this was criticatl for us to separate out the common parts we were all reinventing so we could collab on those common parts and then give more creative energy and time for the science.

Less reinventing

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This is probably the most impactful figure in my science-life. The idea that no matter your question, your study system, etc, you will need to go through these deliberate steps if you’re working with data. And it’s really in this grey box of Understanding where the Science starts. So this is separating your science questions from this first part, which is import and tidying.

The idea of tidying your data first and then being streamlined with the tools you can use for science is amazing. So not starting the science too soon. I’ve been burned by this, and it means forever building bespoke approaches to accommodate weird data formatting. And knowing that tidying data takes a huge percentage of analysis time

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Next Steps and Engagement Opportunities

Engagement in our Cookbook development

Open source and in active development - we welcome contributions and feedback!
Join a call to help us refine our Github-based review process

Upcoming Workshops

Utilizing and repurposing Openscapes materials
November PO.DAAC, LP DAAC, NSIDC Cloudathon
Workshop at AGU Fall Meeting
Four centrally-planned Carpentries workshops throughout the year

Science Champions cohort in early 2022
Additional DAACs to participate in upcoming years as existing mentors continue to lead through Openscapes framework

Thanks to the Openscapes DAAC Mentors!

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Thank you

We’re looking forward to working together!

Further background:

Entryways to open data science and the power of welcome

Lowndes 2020, plenary at Earth Science Information Partners (ESIP) Meeting

Openscapes: Better Science for Future Us

Lowndes, Robinson 2021, plenary at SORTEE Meeting

Better Science for Future Us: Supporting NASA Earth science research teams’ migration to the cloud with Openscapes

Robinson, Lowndes 2021, Pangeo Showcase, June 2021

Join us:

Twitter: @openscapes

Details: openscapes.org

n asa-openscapes.github.io

openscapes.github.io/approach-guide

slides: https://nasa-openscapes.github.io/about.html#slides

Openscapes artwork by Allison Horst

Julia Stewart Lowndes, PhD