Tom McDiarmid and Emily Cantakin are University of Exeter students who partook in the Q-Steps project with Exeter City Futures and kindly wrote this blog. They are currently studying History, International Relations and Arabic and International Relations respectively.
In December 2018 Exeter City Futures embarked on an exciting project with University of Exeter, Q-Step: ‘Pathway in Data Analytics’ students who were working with our City Data Analyst, George, to boost their data analytics skills by collating data sets and assessing the future and full potential of solar energy in Devon.
In this blog the Q-Step: ‘Pathway in Data Analytics’ students write about their experience and the activities worked on during this project.
The modern world has ever-increasing levels of data integration. From finance to meteorology, the effects of data analysis can be found in every walk of life. Exeter City Futures uses processed data to help achieve their 12 sustainability goals. Information gleaned from data allows them to target their resources effectively towards projects which will benefit Exeter and its community. Therefore, the process by which raw data is transformed into digestible information is one of vital importance. In this post we will explore the journey from raw data to information by looking at the process in which we, a group of University of Exeter students, analysed the uses and potential of solar energy in Exeter.
To understand data processing, we first must explore the nature of raw data. Generally accepted to be statistics collected from a source – examples of raw data can be found in public ‘open source’ data sets like the Exeter Data Mill. During our investigation into the potential for solar energy in Exeter, we used datasets from the public domain, typically the Department for Business, Energy & Industrial Strategy, Ofgem and the EU Commission. Raw data provides the foundation; however it is the process of analysis which allows digestible information to be revealed.
One of our primary tasks during this project was to organise data from public datasets and produce information which could be used at ECF. This, like most data analysis, was a labour-intensive task so we enlisted the assistance of three software platforms – Shiny, Qgis and Python. Each of these platforms provided a unique tool to help distil large volumes of data into more refined information. One of the highlights of using these platforms was the creation of an interactive map which can switch between various overlays, enabling complex ideas and disparate datasets to be compared and analysed.
We found that EX2 would be the prime candidate for increased solar installations, along with the numerous industrial estates which are dotted around the city. We also discovered that there is a solar installation for every 1 in 223 people in Exeter (EX1-EX6) and that the EX2 postcode has the most installations – more than double any of the other postcodes in Exeter (EX1-EX6).
The ability to turn numbers on a spreadsheet into visually stimulating forms of information is part of the reason why the sharing of data (e.g. on the Exeter Data Mill) and data analysis is such an incredibly valuable tool. It increases interaction amongst both the public, businesses and city decision makers; hopefully building a platform upon which real change for the City of Exeter can be encouraged and carried out.
Despite the scientific quality which data analysis possesses, it is worth noting that the discipline can’t be considered completely objective. Processes like data cleaning are reliant upon the decision making of an individual; and therefore have an inherent element of subjectivity. This doesn’t reduce the reliability of processed data – however it should be understood and accepted as a necessary part of the data analysis process.
Data analysis has undoubtedly improved the quality of life around the world in recent years, and hopefully it will continue to do so. We were delighted to be able to help Exeter City Futures in their mission to improve Exeter and its community, so make sure to pitch in your own ideas and get involved in the conversation by joining their Partner Network.