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Jose Rafael Verduzco-Torres: AccessUK: An R Toolkit for Easy and Extensible Accessibility Analysis in Great Britain

Geographic accessibility indicators measure the ease of reaching valued destinations. This talk introduces AccessUK, an open-source R package designed for general analysts—not just spatial or urban specialists—interested in accessibility analysis across Great Britain. The package operates at three levels, ranging from simple light-touch or contextual applications to large-scale analytical workflows.

In this session, I’ll show how AccessUK streamlines the usage of a series of validated Accessibility Indicators—pre-computed measures for employment, healthcare, education, food services, and urban centres at small geographic areas. The package efficiently handles large travel-time matrices without overwhelming your system memory by using DuckDB in the background, addressing a common computational bottleneck in this type of analysis.

Overall, AccessUK offers three operational levels: retrieving ready-to-use accessibility indicators with simple function calls; customising measures for specific destinations using pre-computed travel matrices; and creating new measures with your own data.

Rafael Verduzco-Torres is a Lecturer in Urban Analytics at the University of Glasgow. His work centres on examining the potential applications of emerging forms of data and innovative methodologies to address research questions in urban mobility and transport. He is especially interested in the interactions between spatial accessibility, the urban economy, and social equity. He uses R on a daily basis in his research and teaching, and is particularly interested in recent extensions of R and efforts to expand and diversify the R community.

Rafael is also a member of the Urban Big Data Centre (UBDC), a national data service, where he often collaborates on the development and curation of various datasets. His experience spans government transport agencies and local authorities, bridging theoretical insights with real-world applications which motivates collaborations beyond academia.


Simon Taylor: The line-up protocol for interpreting data visualisations

Presenting and interpreting visually presented data is an essential skill for statisticians and data scientists. Visualising data is useful tool to explore the hidden structures with data, and to assess the validity of modelling assumptions. In short, they are used in making decisions … but do you see what I see? At best, we see different and interesting nuances within the data. At worse, we see things that do not exist and may be an artifact of natural randomization. Descriptive guidelines like ‘the points should appear as a random scatter’ are only useful if you know what a ‘random scatter’ looks like. In this talk I will present the ‘line-up’ protocol using the “nullabor” R package, a form of police line-up where the target image is placed amongst a panel of ‘null’ images.

Dr Simon Taylor is a lecturer in statistics within the School of Mathematics at the University of Edinburgh. Simon completed his doctorate in 2014 at Lancaster University in computational Bayesian statistics. Since arriving in Edinburgh, focusing on the teaching of the introductory statistical mathematics course for undergraduate studies. Through this, he has taken an interest in how students develop their skills in statistical understanding, particularly when information is presented visually as for standard model diagnostic plots.


Feb 2026: accessibility analysis and interpreting visualisations



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