Published: 
Aug 24, 2022

Dr. Reina Camacho Toro

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NASA TOPS—Success Stories of Open Science Series

Fostering the next generation and adapting to local realities: Q&A with Dr. Reina Camacho Toro on open science practices

 

 

July 19, 2022
By Steffie S. Kim
[Email] [Twitter]
Digital Marketing Intern at NASA Transform to Open Science
*Session Mentor: Isabella B. Martinez


 

Dr. Reina Camacho Toro

Dr. Reina Camacho Toro

Dr. Reina Camacho Toro is an experimental particle physicist and a member of the ATLAS collaboration at CERN. Her research revolves around analyzing data to better understand the smallest components of matter, researching and developing instrumentation, developing science capacity-building programs to foster the next generation of scientists in Latin America, and strengthening collaborations between Europe and Latin America. Reina is part of a European-Latin American network creating postgraduate courses in advanced physics guided by the principles of open science and education at LA-CoNGA physics. LA-CoNGA physics was launched in 2020 and co-funded by the Erasmus+ program with the support of CERN, ICTP-UNESCO, and CNRS, among other scientific and industrial partners. She is also participating in the TOPS effort to build the OpenCore curriculum.

What is your definition of open science?
I would say that open science is an umbrella term. Open science is a set of best practices and policies that can globally make science more accessible and collaborative while improving the quality of science. Open science is something that can enhance engagement between scientists and the global society in general. So, it is an umbrella term for strategies that can help make more responsible science.

There are different schools of thought in open science. Where do you focus your open science practices?
It depends on where I am. For example, within the ATLAS collaboration at CERN, I've been more involved in open data practices. However, for capacity-building projects between Latin America and Europe, I've been more focused on training others in open science. I work with several colleagues on different initiatives. Currently, I'm focused on an Erasmus+ project, LA-CoNGA physics, which involves three universities in Europe and eight universities in Latin America—Venezuela, Colombia, Ecuador, and Peru. As part of a one-year specialization program in advanced physics, we teach students at the bachelor’s and master’s levels best practices in open science for physics to foster the future generation of open science.

What motivates you to be passionate about open science?
Academically, I was raised in the culture of open science—where collaboration is key—without even knowing it was open science. Using tools to share code and datasets already existed in the high energy physics field. I was so used to working this way since my Ph.D.; to be honest, I didn't realize for many years that this was not common for other communities. I was in a privileged bubble. But, I knew there was a lot of potential in the Latin American region that was not being tapped. I come from Venezuela, and there was no experimental particle physics research in Venezuela when I was finishing my bachelor’s degree.

In 2014, when I finished my Ph.D. with a group of colleagues working in Europe and North America, we created a network, CEVALE2VE, with some young students in Venezuela. We wanted to check what we had learned so far in our Ph.D. and start talking about particle physics with them. CEVALE2VE was initially created with the goal of promoting and disseminating particle physics in Venezuela., which eventually extended to several Latin-American countries. We developed several open educational resources with CEVALE2VE.

Also, with all the global challenges like climate change or COVID, we need to understand how nature works. Particularly, in particle physics, we need to investigate how the smallest particles in matter interact with each other. All these challenges cannot be tackled by a single research group or a single country. Those challenges need to be tackled by extensive collaboration. For example, in the ATLAS collaboration, there are around 4,000 engineers and physicists worldwide from 40 different countries and 180 institutions. So the word “collaboration” is very important for me, not only in the way I work but also in my life.

What challenges have you faced while practicing open science? What strategies did you use to overcome these challenges?
While building CEVALE2VE, the first barrier that we encountered was language. Sometimes, it's challenging to access knowledge just because [this knowledge is presented] in English or a different language from the language you speak. The other thing we realized is that, in some areas, there is no infrastructure even if we have this dataset and code. If you want to start sharing your resources, you need the infrastructure. And we didn't have it. We first tried to work with regional institutions that have an objective to help the scientific community with their computing infrastructure. We have partnered with them in order to be able to create the e-learning platform that we use with the students for the courses, to share the software and datasets, and to communicate with them as well. In 2018, we got funding from the European Commission for LA-CoNGA physics, which allowed us to formalize some of the lessons that we have been learning through the years while working with this community.

Have you experienced failure while practicing open science?
Definitely; there are challenges, and we learn from them. The community in Venezuela has the potential and willingness to move toward open science, but the country is experiencing a complicated crisis—economic and political. This situation has made it very difficult to implement some of the projects we have planned, even though we are still trying. We have heroes in the academic community who are really trying to make things work. But, sometimes, the conditions are just not there. So we keep working on capacity-building for future generations, hoping the situation can improve in the next few years. Also, different institutions are creating strategies and policies to create a good environment. In the end, all the efforts coming from different directions will hopefully meet at the right point and place.

How has open science improved your research? Are there other benefits you have experienced from practicing open science?
Open science makes science more efficient. You don't need to reinvent the wheel when you share the resources, codes, and results with others. For example, if an analysis tool already exists, you can just improve it and use it. We usually analyze a thousand terabytes of data. In order to do that, you need efficient tools; a single person cannot work on this data from scratch and build a complete data analysis plan. You really need to share with others. I'm currently working on an analysis with six different institutions across Europe, Latin America, the United States, and Canada. The only way to put together a full analysis of the data we have is to share everything to make the process more efficient. Also, open science can improve the quality and transparency of science. For example, the internal review process in the collaboration increases the quality of the results. If there is a mistake, someone can detect it because they have the full information available.

Finally, open science increases the transfer of knowledge. At CERN, our peer-reviewed publications are released as pre-prints registered on arXiv. Also, experimental data and associated metadata needed for reinterpretations of published results are released to the public within five years of the data analysis in order to maximize the scientific value of the publications according to the CERN Open Data Policy. So, open science is about everything that is necessary for research. For everything that you develop, someone else can just pick it up and improve it. 

What are your recommendations for practicing open science?
First, find like-minded people because you don’t want to reinvent the wheel. If you can start working with them, it gets so much easier to work in open science. Second, discuss with the community and understand the conditions: What are the resources that are available and the needs they have? It’s dangerous to say that your plan will solve all the problems of the community. It could be that what you brought up was not even a problem for them. You need to be close to the community and understand their needs. And it has to be a continuous conversation about what and how in terms of adapting to the community. Although open science encompasses many practices, you don't always need to check all the checkboxes. You can implement some of the strategies to adapt to a particular case. Always be conscious of where you are.

Can you elaborate more on how to localize for each community?
The first thing is the language being used: Do the people speak good English and have access to the resources? If not, you need to find other resources in other languages or even translate some of the available resources. It can be a good idea to work with a particular university in the region to facilitate localizing. Then questions can be asked like: What is the infrastructure of the specific university? Can they store data? Do they have computing clusters? If not, where do they get them? What are the strategies/policies of the university? Will people be recognized for their work?

When you arrive somewhere, you might need to try different things because the original plan is not a possibility. Sometimes you can encounter ethical or accessibility issues that you need to consider. Sometimes you can put the community in danger. In Latin America, for example, there are a lot of datasets regarding biodiversity. But, open science is limited because there’s a possibility that a particular species will be in danger if the data openly indicate where they are. So you need to adapt to the realities of the community you are working with. There has to be a little bit of flexibility when implementing a project with open science as a guiding principle. I follow the principle, “as open as possible, as closed as necessary.”

What are the most important things that should be addressed in the field to accelerate open science further?
We need to make sure that we create diverse scientific communities. Many of the trends and initiatives regarding open science are coming from developed countries. In order to promote open science, we also need to involve the communities from developing countries because open science is about diversity. Enriching science will require having people with different backgrounds and coming from different realities. Also, like the localizing strategies I mentioned, everything discussed about open science has to be adapted to the local realities. At least, we have to be aware that open science can take different shapes based on where you are and where you're coming from. The need for open science changes so much from country to country and continent to continent. The last thing to consider is skill development—training related to data and software. There are two things to be discussed when it comes to training. You need to consider the results of open research and how to use it, as well as the documentation associated with it.

In your opinion, should the training be different for data experts and non-data people?
Let’s think about this. Does the community need to be able to do everything from start to finish? Or is it enough that we have people with different skills who come together, and together you have everything? Recently, we ran a hackathon co-founded by the Code for Science and Society Foundation. Our team had some people who knew where the data were and how to process the data and others who were more devoted to graphic designs and communication aspects of the challenge. Non-data people could not analyze and run the software, but they gave much more to the project because of the skills they could bring. If it is a collaboration, and you have people with different skills who can contribute to the project, then the project is rich enough. So, I think it is important to decide at what point you need everyone in a team and to know how to handle each part of the project. I think having people with different skills at the right moment is important. They can help us understand the scientific process from different perspectives.

What would you say to early career researchers who fear sharing data?
We all need to understand how the cycle of open science works. It's not only about opening the data but also about having a code of respect for the way we use the data in scientific research. It goes in both ways. You are opening your data, but others are also opening their data. There is a sense of commitment with the rest of the community. You can benefit from the information you are getting from other people—the quality of your science can improve. At the same time, you are reciprocating by opening your information. It's important to put everything into perspective for young scientists. I think there are many myths and fears about open science that can be handled by offering training and by having open discussions to raise awareness about what open science means in one’s community because the needs of each research community are different. It can also change depending on the institution and the country that you are in. So, think about the global context of what open science means and the bigger objective of why you're doing science.

What are some of your favorite open science tools or resources that you’d like to share with us?
There are so many great resources available that it’s difficult to choose. There is a book called Data Feminism written by Catherine D'Ignazio and Lauren F. Klein. They have compelling examples of working with local communities and how power structures affect data science. The Turing Way community from the Turing Institute has an open book about reproducible science. We have also used it while developing our courses for data science within LA-CoNGA physics. They also put a lot of effort into translating the book into different languages. Open Life Science does a great job of providing a mentoring and training program for open science ambassadors. I participated in the training as well and found it helpful. Finally, CERN has an Open Data Portal where you can access open data in particle physics and Arts at CERN that offers a residence for artists to engage other sectors in the scientific endeavor.

Lastly, is there anything you would like to share regarding open science?
I believe it is important to share the experiences from different perspectives since the paths to open science are so different.