[MUSIC PLAYING]
PAIGE MARTIN: Hi, everyone.
I thought I'd start my talk today with something
a little nontraditional.
And that'll be with a song.
And this is just a preview.
I'm going to be working on the song
in our year of open science, which
I will talk about in 2023.
So you might recognize this song.
[MUSIC PLAYING]
(SINGING TO "MAMMA MIA") I am lonely and sad doing my PhD.
The running other's results unsuccessfully.
The data is not shared, nor is any code.
It just isn't fair how this time I spend reproducing.
And there's no transparency.
Just two words that I heard someone say.
Words that will change my whole research way.
Whoa, open science.
What a great idea.
My, my, how could I resist you?
Open science.
You have me in your thrall.
My, my, open science is for all.
Yes, I was sad and lonely too.
I found this community.
My, my, I will never look back now.
Hey, AGU, by now, you all should know
open science is the way to go.
[CHEERS AND APPLAUSE]
OK, good way to kick off the time.
Drew in a crowd.
OK, so my name is Paige Martin.
I'm a program officer with the NASA TOPS Transform
to Open Science Mission.
So I'll be talking today about what TOPS is doing, especially
in the year of open science, which starts in 2023, which
is just around the corner.
So this might look familiar to many of you.
This is the first image of a black hole.
Now, this was obtained a few years ago.
And Dr. Katie Bouman developed an algorithm building
upon open source code to make this happen.
They used live Python libraries, like NumPy,
like, SciPy, Matplotlib, that many of us
may be familiar with.
There were teams working together in an open way.
And that is the only way that this happened so quickly.
This breakthrough was enabled by open science.
And we would not-- it would not have been possible
without open science practices.
So there's another breakthrough discovery
that was published just a couple of months ago.
This is one where astronomers observed carbon dioxide
on an exoplanet for the first time.
Now, this work also was only possible
because of open science practices.
This was obtained from data from the James Webb Space Telescope
that was made publicly available immediately upon release.
Now, this is really--
it was really great.
It was able to get through really quickly.
But it wasn't just the data release.
It actually was years in the making of people working
in a collaborative open fashion to get
to the point of launching the telescope
and to be able to process the data afterward.
So there are a lot of these breakthrough discoveries.
And NASA's looking ahead at these really big discoveries.
What can we enable?
What will we be saying next?
So this particular imagery is from the Hubble Space
Telescope.
And it shows the debris blasted from the surface of Dimorphos
after the asteroid was intentionally impacted
by NASA's DART spacecraft.
So this might sound a little familiar
if you've seen the movie "Don't Look Up."
But NASA's looking ahead at what are
these big challenges that we might have to encounter?
And how are we going to be able to address these 21st century
challenges?
We need to change science now to make this happen.
We need to have--
for science to be successful, efficient, and inclusive,
we need to think about how we structure
our scientific ecosystem.
And we need to respond--
we need to use this to respond to the next great challenge
that comes along.
This means that we need more WE science and not just ME
science.
So we need to work collaboratively, work together.
And together, we'll be able to accomplish
what we need to address these challenges moving forward.
OK, so what does this mean?
We need more people.
We need more hands.
We need more eyes, more brains.
We need more of everyone.
And we need diverse experiences in order
to actually do the science that we need to do.
Sorry, I'm losing my notes here.
The evidence is clear.
Diverse teams find better solutions.
And so it isn't just enough to just open up the knowledge.
But we actually need to open up who can participate
in the science as well.
This means making it easier to access NASA data as well
as other types of data.
So what is NASA doing about this?
NASA is putting a lot of effort into open science.
Open science is the path to 21st century science.
It's accessible.
It's reproducible.
It's inclusive.
And open science creates research that's excited more.
It has a bigger impact.
It increases the transparency of the scientific process.
And it's more inclusive, which means
that it's more collaborative and creates more equitable systems
and allows more people to participate.
It's got a lot of-- got a lot of big pluses here.
So what I'm involved in is NASA's TOPS mission, which
is transformed to open science.
It's a five-year initiative.
And it's designed to accelerate scientific discovery
by accelerating adoption of open science.
So we have three main goals that you can see here.
Our first goal is to train 20,000 scientists
and researchers in open science practices.
We also want to double the participation of historically
excluded communities in science and enable five
major scientific discoveries.
So TOPS is working toward a more inclusive and a more equitable
scientific future where more people are
able to participate in science.
And more people aren't just in the room
but actually have a seat at the table.
All right, so what specifically is TOPS doing to get here?
So we have a few items that we're working on right now.
So one of those is developing the open court curriculum.
This is a community-developed introduction
to open science practices and guidelines.
There are several modules.
There are five modules as part of this OpenCore, which
I'll talk about in a moment.
And we'll be starting to teach this curriculum next year
at conferences throughout our year of open science for 2023.
We also have some funding available for open science
activities.
So the one that just closed is one listed here is TOPST.
And this is for developing curriculum
for specific scientific disciplines
and also to create some more schools and virtual cohorts
to really create a community of learners
who can go through the curriculum
together and learn from one another.
There are a few other collaborators
that we're working with, like the Office of Science
and Technology Policy.
And we are working-- we're doing all--
putting all of our content up on GitHub.
And that's a space that's that we really
welcome others to contribute.
If you see something you can add to that or something
that you think needs more clarification, please--
please do engage.
And as part of the year of open science,
we have three main priorities.
So we'll be developing this curriculum I've mentioned.
We have a number of events planned.
And we have several opportunities
that are coming up.
So I'll talk about all of these now.
Let's start with the curriculum.
So let me just catch up here.
So the curriculum is part of our goal of training 20,000
scientists and researchers.
And it will have a number of different topics discussed.
It will include the open science best practices
and also provide a community.
There will be a certification process at the end.
So once you complete the curriculum,
you get the certification.
That will indicate that you have learned the basic core skills
of open science.
So some of these core skills are digital tools,
like working with Zenodo, working with GitHub,
becoming familiar with data and software management plans
and also, really learning how to be part of
and grow open science communities.
We know that communities are where a lot of the support
comes and where a lot of the great work happens.
So you can see here that these are community-developed.
And we always keep at the forefront, inclusivity,
accessibility, and diversity.
And these are very important to us at TOPS.
So a little bit of the specifics of our OpenCore curriculum
in case you're interested.
There are five modules.
The first of those is the ethos of open science.
This gets at the idea of the mindset
that we all have to be in to do open science.
And it will take a bit of a culture shift
in understanding how we can change our ways to make
sure the science is more open.
The next module is open tools and resources.
So this will get a--
an introduction to what are the tools and resources that we
need to have-- we need to have a basic knowledge of in order
to do open science?
There's also open software where we'll
learn about the impact of open source software
and how that can really ensure the equity
within the scientific process.
And then we have open data.
So we'll learn how to make data management plans that
adhere to the fair principles.
And finally, we have open results.
So this is how we can publish our results
in an open way, where we can publish them,
and how we can-- how we can do review
in the most equitable and inclusive fashion.
So if you complete all of these five modules,
you'll get a badge and a certification
that says you did it.
You completed this curriculum.
And you can use that.
NASA will start to require this as a future funding cycle.
So this will be a way to say yes, I know
all about all of these things.
And I'm on my journey already to open science.
So if you're interested in any of that,
you can scan this QR code here.
Well, you'll get some information.
This will be an email list.
We don't spam it very much.
I promise, but it's a monthly email list.
You'll get information about what's coming out
about the OpenCore curriculum.
And we do anticipate a full launch of May 2023
for the open core curriculum.
But we'll start teaching a couple of the modules
earlier in the year.
So we'll have all that information there.
We also have all of our information on our GitHub
and website.
So you find more information there.
And I think I will close there.
And we have to take any questions.
Thanks.
AUDIENCE: What is the meaning of the symbol?
PAIGE MARTIN: So this is a top, like a spinning top that's
launching because we're trying to launch
open science into the world.
So that's what this means.
Good question.
And we have a few different logo themes that you can see here.
And I don't know if my colleagues are here.
You can go to our booth that's just down the road.
And we have stickers and pins that you can pick up
with these logos on.
OK, so the question is what is my journey in open science
and the makeup of our team?
So I am actually one of the newest members of the team.
I just finished a postdoc where I
was working in climate science.
And I was using some of the big climate models
and working in the cloud.
I was doing cloud computing.
And there are actually multiple ways
that I end up getting into open science
and being such an open science enthusiast.
One of them was the necessity of working with really big data
sets.
And we just could not keep analyzing these data sets
with the traditional tools.
I cannot download and upload these giant data sets.
So I started working in the cloud.
I started using these open source libraries that
were really, really helpful.
And I also have worked with some groups.
I helped teach an oceanography summer school in West Africa.
And I have used Python for over a decade now.
I have a lot of experience with it.
I started teaching Python there.
And it was really eye opening and how many barriers there
are to doing research in different places.
And Python, I found an open source.
Other open source tools really enabled a lot of individuals
that I worked with and in ways that were a bit surprising.
So I'll tell one quick story.
And I know it's OK.
He presented about this early this week.
One colleague that I have from the school
is his name is [INAUDIBLE] Oladipo.
And he works in Nigeria.
He's currently a lecturer and finishing up his PhD.
And he was one of the individuals at our summer
school.
And he had been using some proprietary software
on his local computer to try and do some of his research
on solar flares.
And he came to one of the summer schools.
We got Python on his computer.
He got a plot from his own data on his own computer.
He stood up and cheered.
It was really great.
What I actually learned is after that, he went home,
taught himself Python.
And he was able to get over a barrier
that I hadn't even considered.
And that was he had instrumentation out
in the field to collect data from solar flares.
That instrumentation, OK, the only thing
that he knew how to run was on a proprietary software
that needed a license that had to run on a desktop.
Now, desktop takes a lot of power to run.
And we have something running out in the field.
There weren't a lot of resources.
There's not a lot of funding to power something
like a desktop to run continuously to collect data.
So then this was all his idea.
He said, Wow, I know Python now.
And I found this thing called a Raspberry Pi.
I can program that in Python, select the data
I need, and it runs with very little power.
And it was within his budget.
So it was-- this was an really eye-opening
for me in that this was an issue of not enough money of getting
power to a computer.
But that open source software enabled him
to get the data that he needed.
So I think that's a really incredible story.
So that, really, that was when I was like,
this is the way we have to all move.
This is the future.
So thank you all so much.
[CHEERS AND APPLAUSE]
AUDIENCE: OK, [INAUDIBLE]
[MUSIC PLAYING]