Research

Research perspective

Doing research is exciting and challenging. That’s true. If you join a research team, it’s worth asking yourself how you do your research. This is not a trivial question when researchers are continuously frustated by bureaucracy and evaluation metrics (how many high-impact papers, how many citations, etc) that can interfere in the real objective of research: improving people’s lives adn making the world a better place.

Research is no longer an individual task. If you think you can tackle the big challenges of our society alone, you are mistaken. Doing science means communicating: talk with your office mates, chat with colleagues in person or remotedly, and network whenever you can. You never know when inspiration will strike.

To quote Richard Hamming, “The closed door is symbolic of a closed mind.” In his talk, Hamming observed that “if you have the door to your office closed, you get more work done today and tomorrow, and you are more productive than most. But 10 years later somehow you don’t know quite know what problems are worth working on; all the hard work you do is sort of tangential in importance. He who works with the door open gets all kinds of interruptions, but he also occasionally gets clues as to what the world is and what might be important.” So why not try to follow this simple rule: “Leave Your Door Open”.

A research team is a collaborative environment with its own dynamics. It’s wonderful when you work effectively to develop innovative solutions that improve people’s quality of life, but, most importantly, you are part of a group and should help ensure the well-being and healthy relationships of team members and colleagues. Remember: in science, the whole is greater than the sum of the parts.

Research interests

My research interests are in the areas of GIScience, urban computing, and open science and reproducibility practices in GIScience.

GIScience

What is GIScience? What does it mean to do research in GIScience? Today, it is easier than ever to do geospatial analysis, thanks to the abundance of geospatial tools and frameworks, and access to vast amounts of geospatial data and products. However, easier access does not automatically lead to better understanding. The challenge in GIScience today boils down to the following question: what kind of spatio-temporal question is being asked, and which methods and models are suitable for answering it, and why? As different questions require different methods, GIScience should be then understood as a meta-science of the practice of designing, using, and justifying geographic information methods and models to answer different kinds of spatio-temporal questions.

Within this frame, my work spans geospatial data science, geospatial data management, GeoAI, spatial analysis and visualization, and geospatial data fusion, but always emphasizing the critical evaluation of the use and validity of geospatial methods, questions, and results.

Urban computing:

The use of computing and geospatial technologies to address urban problems, such as mobility, transport, aging population, environmental health, and education.

Open science and reproducibility practices in GIScience:

Reuse, reproducibility, replicability, transparency, openness, integrity, ethics – all in the context of computational research on geospatial data.

Readings for good practices in (sustainable and green) research

Ten simple rules series

And more in the Ten Simple Rules collection.