This study explores how a visualization of existing stops and planned trips within public transport along with collected travel data in Umeå municipality can give insight into patterns, connections and flaws in the current public transport model.
Using an abductive approach, where theories are used to confirm or discard our findings as well as test them against theory in practice, our methods used in this study include data collection, prototyping, data visualization, semi-structured qualitative interviews, data mining and data cleaning. Our interviews were conducted with a respondent from Umeå municipality in order togain relevant insights into specific needs, which could in turn be used in our prototype work.
The prototype is a map-based visualization, with animated paths showing actual travel patterns, a cluster layer showing aggregated travel patterns and circle shapes illustrating the position of bus and train stops. The prototype was made using the visualization tool Kepler.gl.
Our findings and the feedback from our respondent show that the final prototype did not include enough key features, such as clear travel connections between different areas within the municipality, and was presented in a way that could have affected the respondent's impressionof the final product negatively.
In conclusion, we found that a shortage of time, poorly anchored time and day scope in our data selection and the manner of presenting the prototype were all important factors that affected the end result.