About me
Hi, I’m Robin. Welcome to my personal website 🎉
I’m a data scientist, geographer, transport modeller, software developer, and writer. This website should help you find out about my work. I mostly use it to share my publications and previous/upcoming talks, with links aplenty to visual/audio/video content that you can read/listen/watch to in your own time 📖🎧📺
I also share lots of reproducible code for data science and reproducible research, this could be a good place to find resources to get started and try out things if you’re interested in reproducing or building on some of the work that I’ve done (which in turn builds on the work of others as all research does). I also occasionally share blog posts and other things here. If you’d like to get in touch, see here 🚀
In my main academic job I’m Associate Professor of Transport Data Science at the University of Leeds. At Leeds, I’m based primarily at the Institute for Transport Studies where I research, develop and teach free, open, reproducible and internationally scalable techniques for working with data to support evidence-based policies.
I am author of papers and books on transport planning, energy, geographic data analysis and modelling. I lead the Transport Data Science module, which is available to students taking Data Science and Data Analytics and Data Science and Urban Analytics courses at the University of Leeds.
- Geocomputation
- Transport modelling
- Reproducible geographic data analysis
- Mode shift, especially uptake of active modes
PhD in Transport and Energy, 2013
University of Sheffield
MSc in Environmental Science and Management, 2009
University of York
BSc in Environmental Geography, 2008
University of Bristol
Featured Publications
Geographic analysis has long supported transport plans that are appropriate to local contexts. Many incumbent tools of the trade are proprietary and were developed to support growth in motor traffic, limiting their utility for transport planners who have been tasked with twenty-first century objectives such as enabling citizen participation, reducing pollution, and increasing levels of physical activity by getting more people walking and cycling. Geographic techniques— such as route analysis, network editing, localised impact assessment and interactive map visualisation— have great potential to support modern transport planning priorities. The aim of this paper is to explore emerging open source tools for geographic analysis in transport planning, with reference to the literature and a review of open source tools that are already being used. A key finding is that a growing number of options exist, challenging the current landscape of proprietary tools. These can be classified as command-line interface, graphical user interface or web-based user interface tools and by the framework in which they were implemented, with numerous tools released as R, Python and JavaScript packages, and QGIS plugins. The review found a diverse and rapidly evolving ecosystem tools, with 25 tools that were designed for geographic analysis to support transport planning outlined in terms of their popularity and functionality based on online documentation. They ranged in size from single-purpose tools such as the QGIS plugin AwaP to sophisticated stand-alone multi-modal traffic simulation software such as MATSim, SUMO and Veins. Building on their ability to re-use the most effective components from other open source projects, developers of open source transport planning tools can avoid `reinventing the wheel’ and focus on innovation, the ‘gamified’ A/B Street software, based on OpenStreetMap, a case in point. The paper, the source code of which can be found at github.com/robinlovelace/open-gat, concludes that, although many of the tools reviewed are still evolving and further research is needed to understand their relative strengths and barriers to uptake, open source tools for geographic analysis in transport planning already hold great potential to help generate the strategic visions of change and evidence that is needed by transport planners in the twenty-first century.
Recent Publications
Skills
80%
90%
100%
Experience
Responsibilities include:
- Cycle uptake modelling
- Software development
- Deployment
Responsibilities include:
- Project Management
- Data analysis
- Modelling
Contact
Feel free to get in touch in using the form below. It may be worth considering contacting me in other ways, however, including:
- On GitHub, by commenting on an existing issue or discussion or creating a new one.
I put this one first not because I love the world’s premier code-sharing side (although I do ♥) but because I get a lot of software questions. For example: “I have got xx, data, can I get xx outputs using one of your tools?” It’s good to see these questions but often a most appropriate to ask in an open forum such as GitHub or StackOverflow, because:
- You’re likely to get a response quicker
- Other people can benefit from your answer (see here for a good example of how to ask a good question on GitHub)
- I prioritise well-asked questions, ideally with a reproducible example, over vague questions sent directly to me
- On Discord, a great place to ask questions about methods and technology. You can join the Geocompr Discord Server and ask questions here:
- In a comment below one of the pages on this website. See the bottom of this page for an example of this in relation to the Propensity to Cycle Tool (note: you need a GitHub account to add comments in this way, as you do to ask questions on GitHub)
- On social media where I can be found, hopefully with the aim of increasing the signal-to-noise and light-vs-heat ratios on such platforms
- Via my work email address which you can find online if it’s directly related to my work
