Author Spotlight
Bryan R. Vallejo Leverages Geospatial Science and Real-Time Data to Help Ecological Conservation
“Sometimes, I just take a walk to understand the environment I am in and try to uncover patterns.”
In the Author Spotlight series, TDS Editors chat with members of our community about their career path in data science, their writing, and their sources of inspiration. Today, we’re thrilled to share our conversation with Bryan R. Vallejo.
Bryan got a Bachelor’s in Geography and Spatial Planning from the Catholic University of Ecuador, and then went to the University of Tartu for his Master’s in Geoinformatics. He completed his degree with a specialization in Automating GIS at the University of Helsinki. As a former visiting member at the Digital Geography Lab, he has been involved in research focused on human mobility with novel big data sources.
During his specialization year, he became fascinated by marine wildlife migration and its interaction with ocean eco-geographical variables, and developed the Wildlife Tracker for Oceans, a geo-framework specialized in real-time tracking and satellite data retrieval.
Bryan currently works for an Estonian private company developing client-tailored GIS solutions with mobile positioning data. After work, he takes dance classes to get motivated and recharge batteries. In his free time, he supports marine conservation projects in the Galapagos Islands, implementing his platform with marine megafauna telemetry data.
What sparked your interest in the intersection of geography and data?
I can truly say the moment I realized I was going to be a geographer was in my first cartography class at university. I loved mapmaking because it is such a nice way to communicate with data. During my life I had been attracted to numbers, informatics, and workflows, so data was kind of my thing—but when it became geospatial data it took me to a totally new world.
I discovered geospatial processing during demography practices, and I was fascinated by the transformation, aggregation, calculation, and other kinds of data processes that were happening from a spatial unit perspective. The final maps were sending messages about social situations. I was glad about this creative-analytic process I was able to do.
Of course, I had challenges. I realized I found my limit when my desktop software started crashing when I wanted to manipulate the National Census database. I had a question for myself at that point: What comes next?
And what was the answer?
I wanted to approach my challenge in the most formal way, so I started looking for post-graduate programs focused on geospatial analytics. Fortunately, I got an opportunity on the other side of the world, and I had no hesitation to go forward and find the next wave of my transformation from geography to geoinformatics.
That sounds like a major transition.
Let’s be honest: the hardest part of this process was to leave my home country and land in a new culture full of daily challenges. But from the hardest moments, I found motivation to keep developing myself.
I overcame my limits when I learned a programming language for geospatial analytics. Python is my armor. It took me a year and a half to get a solid foundation in data manipulation. By the following year, I jumped over geospatial objects and felt like a fish in the water. I discovered new tools, developed processes, learned tricks, and shared many tutorials as well. In the same way, I received support from open science—so I decided to give back.
So now here I am, automating geospatial processes, creating analytical workflows with modern visualizations, and also trying to scale my analysis.
What kinds of data-focused projects do you find yourself most drawn to these days—and what topics do you hope to focus on in the next stage of your career?
I have seen a new wave of projects focused on real-time GIS. I enjoy diving into this area, which seems to have potential. It’s a geospatial workflow that starts with real-time data retrieving, followed by algorithms on the fly, and ends with a map: a nice funnel that is reactive to every change in the data, giving insights about current situations.
I decided to start my own real-time GIS project and I have been working on it since 2021. There is actually a vast range of options, but I decided to go with ecological conservation. In the coming months—and I hope years—I want to keep working on my real-time monitoring system for wildlife tracking, which already has nice results and implementation on site. I love nature, and for me, it is like magic how everything seems to be connected with wildlife and ecosystemic changes.
Being more specific, I want to develop myself further in algorithmic development and implementations at big data scalability. Of course, I will add a nice map so final users can see the message clearly.
I am talking about my personal desire and my hobby projects, but of course, I am open to seeing what comes in my professional path. I would love to be part of a great team willing to develop geoinformatics solutions at scale—a place where I can find my next level.
What prompted you to start writing publicly about your work?
I reached a moment during my professional development where automating geospatial processes became an effortless and enjoyable daily task. I could reduce the time spent on analytical processes considerably, and I was able to find insights and communicate them in maps.
I had many ideas accumulating in my mind and it was difficult to keep working on other stuff because I was carrying old ideas with me. I needed to liberate them and set them free from my head, and I felt relieved when I wrote my first story. It was like I gave out some weight and I had more space in my head for more ideas.
I have read nice posts on Medium and in Towards Data Science, so I decided to join and share my analytical stories. I have learned a lot from open science, and the community-development model is quite nice and friendly, so I feel good giving out material that can be used by others in the world.
For choosing topics, I can say I am a bit thematic. The first thing I do is choose an original dataset with enough information for finding insights. It depends on the mood I am in—for example, it can be socio-spatial analysis, environmental, urban, or simply writing about applications and usage of the wildlife-tracking systems I work on. Then, I choose a geospatial process that leads me to that desired message I want to transmit. Finally, I create an elaborated map with the final message to people.
Do you have any particular tricks to spark your creativity?
Sometimes, I just take a walk to understand the environment I am in and try to uncover patterns. Cities are alive, and it is wonderful to see their behavior. Once, I was shocked by how many people were riding a bike in Helsinki. I had the curiosity to really see this pattern in a process so I wrote a story about aggregating bike routes in Summer.
The moment I feel most excited is at the beginning of the story, because I need to open the topic and land on the path of my idea. It’s better to give it time. I have left the topic open for a week until I managed to start the analysis. For me, it is not only the topic that’s important, but also the mood you are in and the place about which you want to tell your story.
Do you have any advice for people who might want to write about their data-related work, but aren’t sure where to start or how to find the time?
For sure. For those who have nice data-related work and are willing to share with people, I can advise from two perspectives.
The first one is personal. Find your time and peace while writing. Keep in mind that a story is a mirror of your thoughts, so better to keep them clear. I understand that work can make for long days and it can be difficult to find the time to write. Choose a day when you feel free, relax, drink tea, and find a spot.
I can say that many of my good beginnings happened while wearing pajamas. Also, listen to your mind and to the silence: it will help you to organize your ideas. Be systematic and write day by day. Start with an intro, rest. Write the body, rest. Analyze, sleep, design your outcome, and go on. Even if you post one story per month, you will be satisfied.
The second perspective is technical. Be sure you are writing an engaging introduction and that you are uncovering the topic and its relevance for humanity. Then, be specific about the purpose of the story. You can state one objective that can be solved with one analytical process—there’s no need to include many. A good story, for me, requires five to fifteen minutes of reading.
For the analysis, keep it simple, highlight the state of the art, and do not make it exhaustive. If you are coding, find a good way to make the code shareable and reusable, which will make other people grateful. At the end of the story, just close what you opened in your writing—one paragraph that leads to the usage of your analysis and to solving the objective you state. Finally, the most important thing: Read your post once and twice, and correct or clarify as needed. You will feel how good the transmission of the message is.
Now, I will probably refill my cup of tea...
Whether in your own subfield or in data science more generally, what changes do you wish to see in the near future?
Well, I can truly say that geospatial-science development is already at the moment I hoped for. If you take a look, most geospatial educational materials are open, many of the resources are open access, and there is a broad geospatial community on social media that can respond to your inquiries and doubts. What would come after this?
Sometimes I get shocked: I can connect to satellites in a way that feels like a kid who just learned how to turn on the TV. Even though I feel this is outrageous, I realize later that there are people out there who are creating the tools I am using. So it is a sphere of knowledge that is supported in the community.
What is the future of geospatial science? The last innovative school of geographic science for me was time geography, which involved studying geographical phenomena with the function of time as its third dimension. I took it seriously to advance to that future, so I have been focused on working on spatiotemporal analysis in the last two years.
Of course, I have seen Modern GIS, a new trend that is guiding geospatial science to a global and scalable level. It refers to the usage of open tools that can be combined and developed to analyze spatial data and provide useful insights in an automated way. To be honest, I dislike the name of this new trend because it suggests that it is the last and ultimate paradigm. Instead, I would name it based on its purpose, which is to scale globally. So I think the real new trend coming in the near future should be named Cloud GIS.
Cloud GIS can really scale at a global level and provide computational resources to run models that can give insights into spatial data. I would also include “real-time” in this new trend. For the future of (geospatial) data science, I would say its path should not be focused on statistical models, because they have been developed already since the ‘70s. Nowadays there are more innovative fields of application, so the vision of geospatial science should be focused on its usage in real-life situations, and to improve people’s comfort in their daily lives. What makes this new trend fascinating is that it can be accessed by anyone.
To learn more about Bryan’s work and to stay up-to-date with his latest projects, follow him here on Medium and on Twitter. If you haven’t read his previous articles, here is a sample from the TDS archives:
- Nearest Neighbor Analysis for Large Datasets in Helsinki Region (December 2021)
- Spatiotemporal Visualization of Yearly Wildfires in Madagascar (January 2022)
- Discover Urban Viewer: An Interactive Web Map to Visualize Population of Urban Areas Worldwide (July 2021)
- Ocean Currents Seasonality in the Galapagos Islands, Ecuador (March 2022)
Feeling inspired to share some of your own writing with a wide audience? We’d love to hear from you.
This Q&A was edited for length and clarity.
