Cycle to School Scheme Report

July 21, 2021

The Cycle to School Scheme report was a winner of last year’s Open Data Engagement Fund award.  It is a study of a prospective government scheme and includes sections on feasibility and potential future outcomes of the scheme.  Here, Carl Lange gives us a run-down of the work done on the study.

The Cycle to School Scheme is a hypothetical scheme to supply bicycles - one bicycle per student - to all secondary schools in the Republic of Ireland. The intent of this scheme would be to increase mobility and exercise among all socio-economic groups of secondary school students, as well as decreasing Ireland's carbon footprint by requiring fewer car journeys to and from schools.  We aimed to explore many aspects of the scheme in a readable and understandable manner using data analytics and static and dynamic visualisations. The report is not exhaustive, but we hope that it inspires interest in a scheme like the Cycle to School Scheme, and interest in open data and open research.  You can find the report itself at https://trick16.com/project/ctss/report.html and you can find the source code for the report and all its visualisations and so on at https://gitlab.com/trick16/cycle-to-school-scheme

The report is written primarily in org-mode, an open source, plaintext format for writing. The use of this format over proprietary formats such as Microsoft Word ensures that the text of the report is accessible to as many people as possible, and allows the report to be "source-controlled" - different revisions of the document are stored and retrieved, and the entire history of the document is available.  This org-mode document is converted into HTML, the format used for web pages, to publish the document on the internet.

Research was primarily done within Wolfram Mathematica, a proprietary programming language, document format, and toolkit.  Mathematica is commonly used for scientific research, and has an extremely large feature-set, enabling speedy research workflows. The use of a proprietary format for the research was a trade-off based on the ease of research. However, the Wolfram Notebooks are published alongside all other source material.  Nothing that is done within Mathematica cannot be recreated using an open-source programming language such as Python or R, and the Wolfram Notebooks are published to facilitate the verification of research results in arbitrary programming languages.  Diagrams and visualisations have been created by Wolfram Mathematica, except where otherwise stated. 

We structured the process of research around building blocks called "ARC"s - "Ask, Research, Conclude" blocks, which then built up larger sections of research over the course of a "sprint", typically 3-4 weeks in length.  An ARC section is typically a standalone data exploration.  We "ask" a question (for example, "How many bicycles would we need?"), "research" the answer based on several data sources, exploring the data and creating visualisations and prose, and then "conclude" the result.  We did monthly reviews of the questions we had lined up to explore using an ARC block, and usually did one ARC per week, although the sections often progressed asynchronously.  Typically at the end of each month, we had a writing week, where the results of each ARC was drafted into the report itself.  Then, a new set of questions for ARC blocks were created, and another "sprint" was begun. 

Building the report was a really fantastic experience. The wealth of open data available on data.gov.ie and other sources, such as Open Street Maps, made the research really fun to write.  We were able to explore such a large amount of data without needing to do much data cleaning, and crucially the act of searching for relevant data was extremely easy thanks to the search functionality on data.gov.ie. I think this project really demonstrates the versatility and benefits of open data!  A big, big thank you to the Open Data Engagement Fund for funding this work, and to everyone involved in creating this report.