Revealing the Mill Race: a research project to explore Lancaster’s hidden waterway
What is the Mill Race and why does it matter?
The Mill Race is a channel of water that lies underneath some of Lancaster’s low-lying streets. In medieval times, the Mill Race gained its name, powering mills near what is now Damside Street and Dye House Lane. Over the succeeding centuries, the Mill Race gradually became covered over, and was underground by the end of the First World War. The Mill Race has always been an issue for the town, in the 1800s it was likened to an open cess-pit. When the Corporation installed sewers later that century, the overflow from the storm drains was directed into the Mill Race, which caused problems then and now with flooding.
During Storm Desmond in December 2015, the Mill Race, overwhelmed by the volume of rainwater in such a short time period flooded the lower part of Lancaster. This flooding had a devastating effect on the businesses that traded there. Some were able to re-open after months of remedial work to their damaged premises, some have remained closed to this day. Since the storm, businesses, local government and universities have sought ways to prevent such devastation happening again. Sadly, the area was flooded again in July and November 2017, highlighting the urgency of this problem.
The project aims to merge computer science with environmental science, working with government, businesses, the public and third sector organisations. It seeks innovative ways to tackle urgent environmental problems, drawing on the Models of Everywhere approach . Computer models of environmental factors generally aim to be as universal as possible, however they may not work at a small enough scale to benefit areas such as that surrounding Lancaster’s Mill Race. In contrast, the Models of Everywhere approach aims to create a model of a specific area. In order to create a model that will be helpful to businesses and other stakeholders, there will need to be knowledge of flooding in the lower parts of Lancaster. The recent trend towards the Internet of Things enables much richer real-time data on water flow and level data to be gained, which can contribute to online warning systems of water levels and flood risks.
Data: ontologies, non-digital data and the Data Drift methodology
The knowledge gained about flooding in the Mill Race area will need to be structured in a common framework before it can become part of any model, which can be achieved through ontologies. Ontologies are a concept from information science, where the types of data and the relationships between them in a particular domain are named and classified. Each class of data has properties describing its features and attributes. When complete, the ontology of data can then become the structure for the knowledge base.
When the data on flooding is purely digital, creating an ontology of it can be a straightforward process. However, what happens to non-digital data? In the context of flooding in Lancaster, non-digital data includes the experiences of people working and living in the affected areas, and their wishes for a future where uncertainty does not deter new businesses and investment. Some of this data could be gained through interviews and questionnaires, designed so that the responses to them can form part of the data ontology.
However, we wish to consider another form of data, a tacit sense of place and how it is affected by environmental factors. Lancaster’s Mill Race is in an area where human activity has changed the local environment for centuries, an area steeped in history. In order to capture this tacit knowledge of the area and how flooding affects those who live and work there, we will take a design approach. Taking a design approach focuses on creating a desired future, in this case where the experiences and knowledge of the people affected by flooding in Lancaster can contribute to a richer local flood prevention model.
The Data Drift methodology was developed by Louise Mullagh for her PhD research as a way of designing an engaging way of collecting environmental data. It is a convivial way of bringing people from different backgrounds through going for a walk with a map pouch that allows for collection of notes, reflections and artefacts. After the walk, participants then bring together their data in a large map of the area which can then be thematically analysed. The themes can then form the basis for an ontology of non-digital data. The Data Drift methodology enables a range of data to be collected, including tacit knowledge of a particular place. The Data Drift methodology complements the Models of Everywhere approach in its strong focus on place and people’s responses to it.
The Revealing the Mill Race research project aims to work with the people who are affected by the recent flooding in Lancaster to gain a range of both digital and non-digital data. We will use sensors such as GPS locators together with a Data Drift walk and subsequent reflections to reveal a rich pool of data about the environmental and social effects of the hidden and often forgotten about Mill Race. We will then work with the Ensemble project team to meet the challenge of creating a Mill Race ontology.
The research is funded by seed funding from Ensemble, a project funded by the UK EPSRC as part of the Senior Fellowship in the Role of Digital Technology in Understanding, Mitigating and Adapting to Environmental Change grant no: EP/P002285/1.
It is being undertaken by Louise Mullagh (email@example.com) and Justin Larner (firstname.lastname@example.org), overseen by Dr Serena Pollastri (email@example.com) and Professor Gordon Blair; Dr Vatsala Nundloll is also contributing to the work.
Authors: Justin Larner and Louise Mullagh