Geographical Data Visualization in Logistical Services Visualizing Geographical Data to Facilitate Data Driven Decisions in Short Distance Logistical Services

Examensarbete för masterexamen

Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12380/256201
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Type: Examensarbete för masterexamen
Master Thesis
Title: Geographical Data Visualization in Logistical Services Visualizing Geographical Data to Facilitate Data Driven Decisions in Short Distance Logistical Services
Authors: Blomqvist, Oscar
Abstract: Bzzt, a pod taxi company operating in central Stockholm, has a lot of geographical data such as customer bookings, destinations and taxi locations. To explore and discover insights using all of this data, a geographical data visualization system is required. In this paper, the requirements and important considerations for designing such a visualization system are explored. This research is done by interviewing users and stakeholders at Bzzt, observing Bzzt’s operations and workflows, studying theory as well as analyzing existing geographical data visualization systems. The results of this investigation are the design of BGIS, a tool for visualizing, exploring and sharing geographical data. Further more, based on the discoveries during this design process, a set of design guidelines for designing geographical data science tools for logistical services are produced. Some of the most important findings are that the geo-data systems for logistical services needs to support a wide range of different geographical visualization methods, provide a high degree of flexibility in filtering data and support for exploring how data changes over time. The resulting design of BGIS, a web application for visualizing geo-data, includes these requirements. The paper also investigates technical consideration for implementing BGIS, how the design process may be continued as well future improvements of the design.
Keywords: Data- och informationsvetenskap;Computer and Information Science
Issue Date: 2018
Publisher: Chalmers tekniska högskola / Institutionen för data- och informationsteknik (Chalmers)
Chalmers University of Technology / Department of Computer Science and Engineering (Chalmers)
URI: https://hdl.handle.net/20.500.12380/256201
Collection:Examensarbeten för masterexamen // Master Theses



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