opentripplanner provides functions that enable multi-modal routing in R. It provides an interface to the OpenTripPlanner (OTP) Java routing service, which allows calculation of routes on large transport networks, locally or via calls to a remote server. The package contains three groups of functions for: (1) setting up and managing a local instance of OTP;(2) connecting to OTP locally or remotely; and (3) sending requests to the OTP API and importing the results and converting them into appropriate classes for further analysis.

License Authors of papers retain copyright and release the work under a Creative Commons Attribution 4.0 International License (CC-BY). Summary stats19 provides functions for downloading and formatting road crash data. Specifically, it enables access to the UK's official road traffic casualty database, STATS19 (the name comes from the form used by the police to record car crashes and other incidents resulting in casualties on the roads). Finding, reading-in and formatting the data for research can be a time consuming process subject to human error, leading to previous (incomplete) attempts to facilitate the processes with open source software (Lovelace & Ellison, In press). stats19 speeds-up these data access and cleaning stages by streamlining the work into 3 stages:

Recent analysis of area-level COVID-19 cases data attempts to grapple with a challenge familiar to geovisualization: how to capture the development of the virus, whilst supporting analysis across geographic areas? We present several glyphmap designs for addressing this challenge applied to local authority data in England whereby charts displaying multiple aspects related to the pandemic are given a geographic arrangement. These graphics are visually complex, with clutter, occlusion and salience bias an inevitable consequence. We develop a framework for describing and validating the graphics against data and design requirements. Together with an observational data analysis, this framework is used to evaluate our designs, relating them to particular data analysis needs based on the usefulness of the structure they expose. Our designs, documented in an accompanying code repository, attend to common difficulties in geovisualization design and could transfer to contexts outside of the UK and to phenomena beyond the pandemic.

Recent analysis of area-level Covid-19 cases data attempts to grapple with a challenge familiar to geovisualization: how to capture the development of the virus, whilst supporting analysis across geographic areas? We present several glyphmap designs for addressing this challenge applied to local authority data in England whereby charts displaying multiple aspects related to the pandemic are given a geographic arrangement. These graphics are visually complex, with clutter, occlusion and salience bias an inevitable consequence. We develop a framework for systematically describing and validating the graphics against data and design requirements. Through an observational data analysis, we then relate designs to particular data analysis needs based on the usefulness of the structure they expose. Our designs, documented in an accompanying code repository, attend to common difficulties in geovisualization design and could transfer to contexts outside of the UK and to phenomena beyond the pandemic.

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