Alejandro 101 - Part 2 - Alejandro Coca-Castro

Hello world¶

In the previous instalment I described my journey from undergraduate studies to my PhD, which was without doubt a rewarding stage with considerable personal growth and countless academic and professional achievements. For this second instalment I’ll share what I experienced during the pandemic — a very difficult period for all of humanity, but one that reminds us how fragile we are, like any other living species on Earth.

Let’s continue!¶

Stage 3: pandemic and uncertainty¶

Let’s begin in March 2020, when COVID-19 restrictions started in most countries and coincided with the deadline for submitting my PhD thesis. What’s more, it was the month my sponsor’s scholarship-loan funding came to an end. Without many options, my wife and I decided to leave London and return to Bogota (my home city). Despite every possible pressure, I met my goal of submitting my thesis on 30 March 2020 — a very memorable day! I then defended my thesis remotely in May 2020, celebrating by video call with my family, supervisors and friends. I received my doctorate in Geography from King’s College London in September 2020.

During the period of thesis corrections and job hunting, I was selected for a virtual data-science training programme run by the Colombian government and organised by Correlation One. As part of the programme, together with other participants, we applied what we’d learnt in a project focused on developing models and a data dashboard to predict recidivism in the Colombian penal system (see details here). Later, in August 2020, I joined the Agustín Codazzi Geographic Institute (IGAC) — a Colombian government body known for its role in cartography and land-use planning — as a contractor. During my 5-month contract I had the opportunity to be the technical lead of teams of 5 to 6 researchers and to publish, in scientific journals, the results of two projects involving data-science and artificial-intelligence technologies: one on mapping buildings in rural settings (see details here) and one on digital soil mapping (see details here). I also coordinated a challenge for Correlation One’s data-science programme that sought to develop predictive models from an IGAC soils database (see the repository here).

With my IGAC contract at an end and little success in finding academic positions, I decided to take the entrepreneurial route. Along this path, the lessons I’d received in an extracurricular programme offered by my university’s entrepreneurship institute during my PhD proved valuable. I registered GeoMagic Labs, a geolocation technologies consultancy, with the Bogotá Chamber of Commerce. Through my venture I was selected in a consultancy competition with Solidaridad Network, an NGO focused on facilitating the development of socially responsible, ecologically sound and profitable supply chains. In my proposal I developed a methodology for mapping coffee production systems using openly accessible satellite imagery (see details here).

Opportunity 4 - Data science training

Data science has undoubtedly gained an important role across every domain of knowledge, with impact in all sectors. As a result, countless training programmes and resources are available. In my case, taking advantage of the period of uncertainty and remote working, I set myself the task of finding ways to improve my data-science skills. That’s how I found Correlation One’s Data Science for All (DS4A) programme. Funded by the Colombian government, this programme offers 13 weeks of training, open to all Colombian citizens interested in strengthening their data-science skills and joining Colombia’s growing artificial-intelligence ecosystem. To take part you must pass an admission exam assessing general knowledge of statistics, programming and logical reasoning. The programme is very interesting: not only do you receive training, but there are also talks by professionals from industry and academia explaining how they use data science day to day. I’d describe the programme as basic to intermediate level, with very practical examples and the chance to work in a team, putting everything you’ve learnt into practice through an applied project proposed by government institutions, the private sector or NGOs. Correlation One offers other training programmes focused on women, empowerment and engineering, among others, which are open to any nationality.

Stage 4: open science, May 2021 - present¶

In November 2020, my PhD sponsor’s loan-forgiveness rules changed, opening the door to new opportunities. It was no longer mandatory to demonstrate employment at an institution in Bogota for the length of time I’d received funding (that is, 4 years!). The new rules were flexible about other kinds of outputs, including publishing papers and/or starting a venture related to the PhD topic. Against this new backdrop, I applied for a postdoctoral position at the Alan Turing Institute in the United Kingdom in December 2020. I was already familiar with the Turing environment from a collaborative hackathon I took part back in December 2019 (see the report here). The postdoctoral position matched my profile, and I was drawn to the possibility of learning probabilistic modelling, improving my software development skills and contributing to Pangeo, a community championing open science for big-data analysis in the geosciences.

In February 2021 I was invited to an interview, which included a 5-minute presentation followed by a walkthrough of code I’d written and questions from the interview panel. It was my first postdoc interview, so it was natural to be a little nervous. Nevertheless, I gave solid answers, highlighting my experience collaborating across diverse research groups. When showing my code, I was able to demonstrate how it had been used and visited on Zenodo (a platform for registering digital research objects). A few weeks later I received the offer, starting remotely from May 2021. My wife and I then left our life in Bogotá and decided to restart our life in London at the end of July that same year.

Being part of the Turing, I’ve had the opportunity to collaborate with many researchers in the United Kingdom and their collaboration networks. Below are the projects and initiatives I actively contribute to:

My postdoctoral project consists of developing tools based on the intelligent fusion of environmental sensor data to improve the monitoring of our changing planet (see details here). In collaboration with researchers from the British Antarctic Survey and the Met Office, we’re developing a tool based on probabilistic modelling that combines data of different modalities (gridded data, in-situ stations and auxiliary data) to obtain finer, more local observations of environmental variables. In addition, using greedy algorithms, the tool is designed to suggest where to install local sensors to reduce the uncertainty of the modelled environmental variable. I’m fortunate to contribute my experience to the tool’s development, in my case working with researchers from the UK Centre for Ecology & Hydrology (UKCEH) to model soil moisture.
I’m the founder and lead of the Environmental Data Science Book (see details here).
It’s a resource led by the environmental community where Jupyter notebooks showcase advances in data, methodologies and other kinds of research using open-source tools. Through this initiative I collaborate with other members of the Pangeo community in Europe to further democratise scalable, open-source tools for the geosciences.
I’m a member and developer of scivision (see details here), an open-source tool developed by researchers across different domains — including molecular biology, agriculture and the environment — together with professionals from the Turing’s Research Engineering team. My role in the project is to ensure the tool generalises across a variety of imagery (satellite, drone, climate data, and more) and models from the environmental sciences community.
I’m a member and co-lead of the translation team in The Turing Way, a community-led initiative promoting best practices for open and reproducible science (see details here).

Opportunity 5 - Communities and open-science training

Beyond improving my programming skills and best practices for environmental applications, this last stage has allowed me to belong to and contribute to the open-science community. Despite having been part of research groups since my undergraduate days, I believe open-science communities have the greatest potential for long-term impact on our society. Examples of these communities are The Turing Way and Pangeo — the first aimed at a general audience and the second at the geosciences community. They promote a vision of science in which anyone can contribute to a common goal, democratising knowledge and good practices across projects in different sectors. The Turing Way has a diverse set of communication channels (see details here), but my first suggestion is to join the Slack. With around 400 members, this is the main space for exchanging ideas with the whole community and keeping up with its activities. Throughout the year, book dash weeks are organised — hackathon-style events proposing a range of activities such as proposing or reviewing content for the online resource, short talks on diverse open-science topics, and socialising or networking among members. Unlike traditional hackathons, there’s no competition for a prize; every contribution is part of a shared celebration. Through The Turing Way I also discovered the Open Life Science (OLS) programme. It’s another community, offering 16 weeks of training in open-science leadership. I took part in the fourth cohort to validate the idea of the Environmental Data Science Book through meetings with my mentor. Later, I was a co-mentor for a multilingual open-science knowledge project in Central Asia during the fifth cohort. Both experiences were valuable: in the first I learnt the basics of leading an open-science project, and in the second I gave back what I’d learnt through my mentoring role. I thoroughly recommend joining OLS — they welcome any branch of knowledge in which you want to practise open science.

Summary¶

That brings the second instalment of Alejandro 101 to a close. It’s a pleasure to share my professional and academic development, as well as some opportunities for those interested in open environmental science and information technologies.

I’ll take this chance to mention that, if my content proves useful, I’ll be publishing monthly (workload and family life permitting) on a range of topics — from tool discussions (with code) to concepts and frameworks in open science, environmental science and information technologies. From time to time I’ll also share the odd update on my personal life or travels that might be enriching for other readers of this blog.

For an inclusive and transparent science 🚀

References¶

Data Study Group Team. (2020). Data Study Group Final Report: WWF. 10.5281/ZENODO.3878457