 Hi It's so great to be here. Thanks so much. I've been listening to such amazing talks all day I feel like there's so much more so many more questions and things I want to talk about then I have time to today, but I'm excited for the discussion afterwards as well So hi, I'm a marine ecologist But open data science and the communities and tools in this room and beyond have been so game-changing for My science and for my life and that is not an overstatement I have gone I've been so empowered by these tools that I've sort of been moving away from conducting my My own research towards enabling other people to do their research better So as a marine ecologist, I am I am in a my I am an environmental scientist So we're the geneticists the biologists the physiologists the climate scientists all of these different people who are Studying in the national environment and how people interact with it like the food systems That we have sustainability all these different things that United Nations report that came out this week about the million species That are going to be extinct that is scientists like me that are doing those that work So we have different backgrounds different study systems But we are united by the fact that we are never trained to work with data we are never taught how to use a computer and It yeah, it's it's like that awkward terrified laugh Because we're working with really important global systems and the Practices that go on in our labs like there's kind of this sense of like eyes down elbows out a little bit When it comes to working with data and with practices because we don't have a culture of sharing we don't have We just don't have like the the mindsets that we can do better some some some of these times So groups like our open side the carpentries our studio all these groups have enabled Me to see that there's better ways to do things and to learn from these communities And I really want to bring these to these practices to environmental science So to put this a little bit more I To go through this a little bit more. I like to use Star Wars analogies. So This is Luke Skywalker sitting on the edge of the Dagobah swamp after he's crashed his plane He is sitting there super demoralized looking at a problem. He cannot solve what the skill sets he has That that's that was me that is so many environmental scientists sitting there looking at their data Not knowing how to tackle it and and what will happen is some pretty messy pretty irreproducible Approaches to tackling this problem with the skill sets we have but There is a different way to solve that problem Here's Yoda coming along and solving this problem in a way that Luke never dreamed was possible and Luke is going to be able to learn from Yoda and He will be able to solve this problem himself and He will go on to tackle problems that are much bigger and broader in scope because it's it's gonna broaden his Imagination of the things he can take on. So this is what open data science does for scientists like me It is just game-changing. It is so empowering and it's yeah, it'll take you places. You never dreamed But something that's also really important is that it's not just the tools and it's not just The Jedi's it is this whole community of people Towards this bigger movement And there are such different backgrounds and skill sets and we can all come together to work on something bigger So this is the way I feel in the open data science universe And I want Ecologists and climate scientists and all these other amazing Scientists to feel part of this bigger movement So I love Star Wars analogies and I'll come back to them. Don't worry, but um, we've also We've also published scientific research about this story about how these tools and these communities have Made us do better science in less time and have much bigger impact so I want to talk about two examples of environmental open data science communities that I have been a part of and been leading for the past The Ocean Health Index has been for the past six years and open scapes as a program. I started in January as a Mozilla fellow So The Ocean Health Index is this big project to help bring more data and science into Policy ocean policy on the ground around the world. So we developed a scientific framework published in 2012 and And then also assessed how healthy oceans are for every country that has a coastline globally And we've now been repeating this every single year and this data-driven assessment with a hundred different public data sets modeled with With management targets and a bunch of different a lot of more backstory than than that Is now being used by the United Nations Because it is this transparent reproducible way of using data to assess oceans So it's been really it's a really awesome project and we've also been able to Enable other countries around the world to use our methods as well But what I want to talk about in the context of the Ocean Health Index is how Open data science has helped us work as a team and kind of kick that Feeling that many scientists have even within a lab of not having community and not being able to talk about data and Struggle solely with their data challenges and have basically everybody It's just feeling stranded the way Luke did But we all feel we work like a team we have overlapping skill sets and what it's done is that we've been able to each year Take less time to do these repeated assessments that we have to do every year And it's and it has so that you know the circles Show the amount of time relatively But it's also led us focus more on training other people and enabling other people and building community around these tools so We we lead these global assessments like I said, but we also enable Teams around the world to do this as well So I over the last six years have led this program where we've helped governments around the world This is uh, Colombia and Indonesia. We also have groups in The Baltic sea and then Norway and in Canada and Samoa who are using not only our science But our our open source tools in order to get better data and decision-making into the oceans So this is a busy slide and I'll walk us through it. We're going to start up in the top left and come around counterclockwise because I just want you to know how much open data science has contributed to This effort and made this possible like made it possible. So that small team of us Right here Has been able to help 20 countries around the world and do these assessments every year So I was hired in 2013 to teach our science to Governments and groups that were interested in using our our science And so I was able to work with my team to contribute to our global assessments and start a program that will enable other governments um, I pretty quickly in 2014 needed to learn r and I was thankfully Able to join our studio and our open sci communities rather than struggling with um as I had as a graduate student When I was trying to learn matlab by myself um, so learning are With these communities enabled me to help us develop our our software toolbox like as we call it our our packages and github workflows That then I would teach the these scientists around the world Um, so that was great So I'd started off trying to teach the science and then now I was teaching a science and our coding packages Which were awesome, but then I realized I needed to actually teach people how to use r and github Beforehand, so that's when I became a carpentries instructor and started teaching software carpentry workshops and I started co-started a A study group locally at UC Santa Barbara where we skill share And teach each other Different things we started off teaching each other github and then spatial data Analysis with r and all these kinds of things So that really equipped me to be a better teacher to my ocean health index community so that I could teach them r and github but Then I really realized that the problem That I faced within these communities wasn't that they Didn't know how to use r and github. It's that they didn't even have the mindset to want to learn them They didn't even have this like team mindset or or team culture or individual mindset that would enable that so That's when we led our nature paper in nature ecology and evolution paper and started an our ladies chapter locally In order to To sort of welcome more people into this world And and broaden beyond just ocean Oriented groups so trying to reach broader environmental data science communities And then this has also led to this mosella fellowship that I am super lucky to To have and be a part of And I've been able to lead Open scapes, which is this effort that I'm going to spend the rest of the time talking about Which I'm super excited to tell you about as well So the questions that kind of spawned open scapes are How do we welcome more people into this world and empower them with the existing communities and tools that already exist And how do we focus for me on environmental scientists? But actually do this more much more broadly and then how do we also in order to do this? I think we really need to think about helping science labs work more like teams Okay, so This is open scapes So the what i'm trying to do with open scapes is to Compliment existing efforts and welcome more people to this world And in doing so I want to increase the visibility and value of open data science within the environmental communities And I want to do excuse me do that by amplifying awesome scientists that are now using these practices So I want everybody to feel like this Well, that's not well, it's a team effort, but I just love this graphic Um So with open scapes, I have started this champions program Which is a mentorship program to make more champions for open data science in our communities And I'm focusing on early career scientists and their labs So scientists like me who are now tenured faculty And are doomed to to have a closed mindset and a closed lab Unless they're welcomed into this world because they've never been exposed to it otherwise So I really want to normalize open data science in the lab and then help seed it far beyond So, um It's this is a five month remote program. I'm does it developing or have developed In the vein and modeled after mozilla open leaders So that means that it's all done remotely through zoom Which also means we can have smaller breakout groups and have people discuss things as smaller groups as well as the whole community um And there's kind of two halves of the Um Of the curriculum the first being about Lab culture and lab mindset and the second half really being about skill building with the broader community on campus Um, and so it's all about kind of welcoming people to these tools and practices and communities that exist And I'm developing it to be Um, discipline agnostic. I should say too. I I have plans for Beyond this pilot cohort that I've created Um, but I am I have been testing this with It's either the inaugural cohort or the pilot cohort, but I I do plan to Continue this effort beyond this first cohort Um, so I'm developing all of this with these seven champions in their labs So I've got 24 people that joined me twice a month to Talk about open data science and what's how they can get this into their lab culture So these are my seven champions They are all incredibly awesome environmental scientists who I've chosen for three reasons Um, the first is that they are already rising star early career faculty and lecturers. They have Incredible momentum and they're doing really important science And I can Help them do better and help them be an ambassador for open data science as they continue to rise Which I am which is really exciting Um, the second reason I chose them is because they are not involved in open data science yet They are either unaware hesitant or or not not bought into open science So it's a tough crowd but The reason I picked them the third reason was trust These are all very close friends of mine from graduate school or currently at ucsb And they were willing to To participate in my program that they didn't know what it was because they saw that it was important to me And they knew that this was be something bigger So that trust is something that we can talk about with scaling as well but um What I think was cool and two of them actually said, you know I don't know if this is going to be useful for me at all But I'll join because you're asking me to and then they are like Some of the biggest advocates, which is amazing and that's exactly what I want um So and then this is our this is most of us on one of the cohort calls So these are all of those seven champions plus their labs together And I teach them together and it's it's hard and there's challenges, but um, I do it for again three reasons um The first is so that everybody pis and lab members together can value this can see this can know It's important and value it and then the pis the principal investigators can They can be an ambassador for it in their bigger channels on campus and beyond and they can enable their lab to do it And then their lab has agency to do it and they have Support from their p. I but it kind of removes this feeling that the p. I Needs to be an expert in it first in order to enable their lab, which is a big hurdle Um Okay, so there's been Some really awesome outcomes In the four months already And I am excited to talk to more people about how to quantify this and how to track this either now and and also beyond But i'll show you what i've come up with so far Um, everybody has every lab has a github organization for the lab and that's a big deal um To have everybody having an account and being able to participate somewhere and then there's this idea of longevity of the lab They have codes of conduct. They have protocol protocols for digital onboarding into the lab Um, they have data man some of them have data management Protocols so it's it's been really awesome to see that they are really putting this forward and saying like we do this This is important. This is the type of lab. We are this type of culture. We are which is really exciting Um Another their homework each week is to normalize talking about data science in the lab So instead of this kind of eyes down I'm working on my own science and I am unique to everyone else in the lab I want them to see those horizontal cross cutting similarities across the lab Everybody has to send data or figures to your your pi. How do you do it? Do you email your dropbox your google drive? Like let's have a let's have a system And it will make everybody's life easier and then we can figure out how to onboard new people into the system We have undergrads every every summer. How do we onboard them like that kind of stuff? So they not only are having these chats every week, but they are now starting to amplify that they're doing it so these are examples of Places online. You can see that They're also joining and leading communities outside of the lab. So they're participating in um Well, they're they're creating coding clubs on campus and they're joining existing ones And they're also starting new our ladies chapters and and really trying to figure out how to move forward in the community Um, and they're also being ambassadors more broadly They're tweeting to their environmental science communities about r and about Code packages. They didn't know exists and about the feeling of how awesome this is and and just You know trying to you know, they're they're they're saying for themselves what I want them to feel which is amazing um Not in such a heavy-handed way that that just sounded um And something that's also been great is um, there's there's some real tangible Scientific collaborations that have come out of this already people are writing a grant together about aquaculture Both from a bunch of different angles and it's just really exciting that they're within the realms of what is What they are measured upon within their scientific Structure, they are still having really good Wins that way as well um There are so many other things I would love to say there's so many little wins of little efficiencies time Mindset all these awesome things that I am also trying to track Um, I'll just wrap up with a couple challenges from this. Um, this first one is you know, I didn't really expect that labs didn't by default think like a team and um, even though I had experienced that in my own phd lab Um, I had kind of you know with rose-toned glasses forgotten So I really had to reframe my curriculum to really on the first half focus on just the idea that we're a team um imposter syndrome and hierarchy are real things um Early career faculty have so many pressures on them and they are trying to be leaders But both in with their peers and with their students and it is a big deal for them to say I don't know how to use github to their students You know and they shouldn't and they feel this like burden that they need to learn it in order to have their lab do it So this is something that I'm trying to do is like kind of break this hierarchy and and name that imposter syndrome um, and then limited time prioritizing and no and academic incentives across the board is really hard as well but um I think some ideas that come up with this are that I think a lot about how open software and open communities Really create a kinder culture in real life as well And like we see that here at this conference Like how do we channel this back to the labs and to science more broadly? So I think about that a lot. I'd love to talk about that um And I also think we need to invest in people that are making this culture change and and hat and value them and the way you value people is by Giving them job security and academia. That would be amazing if not If there were more people that wanted to support this with teaching and doing More adding more stability to labs were able to to do that um So this brings just me back to the whole idea that this is a part of a bigger movement And it's really exciting to have more scientists feel a part of this movement And i'm really excited to to be here and be a part of it with you. So thanks everybody