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Much of the world’s data relate to processes and objects situated in space. This spatial dimension of the data requires special representation and analytical approaches. Therefore, application problems such as the analysis, monitoring and simulation of Smart cities and smart environments cannot be handled by standard programming approaches and require specialist knowledge.
Using case studies in the domains of smart environments and smart cities, this subject will enable students to learn the necessary computational thinking approaches and acquire technical software development skills to address specific spatial information problems enabling them to effectively address Spatial Data Science problems.
The subject will focus on the application of state-of-the art programming techniques and applications of spatial analytics to solve a series of spatial data science use cases, in particular in the urban informatics domain. The course projects will also introduce the principal aspects of software development life cycle relevant for a data scientist.
This subject assumes students are familiar with elementary spatial information data and the varied ways these are used by various stakeholders. Fundamental understanding of a programming language is assumed, with the first few weeks of the semester providing an ability to acquire these skills (using Python).
Students who successfully complete this subject will have a distinct competitive advantage in the smart environment, smart cities, and urban analytics practices, with the ability to support consultancy work requiring computational data handling, analysis, and the development of software tools for spatial analysts beyond the traditional spatial information industry.
Intended learning outcomes
INTENDED LEARNING OUTCOMES (ILO)
On completion of this subject the student is expected to
- Use an object oriented programming language to design, implement and test spatial programming solutions
- Design and generate an algorithmic solution to a specified spatial information problem
- Be able to understand, critically evaluate and explain software code developed by others
- Use varied spatial and non-spatial data, including dynamically changing web content in these solutions
- Document and maintain complex, re-useable software programs.
The following generic skills will be strengthened as a result of this course of study:
- Ability to apply knowledge of science and engineering fundamentals
- Ability to undertake problem identification, formulation, and solution
- Ability to communicate effectively, with the engineering team and with the community at large
- Ability to manage information and documentation
- Understanding of professional and ethical responsibilities, and commitment to them
- Capacity for lifelong learning and professional development.
Last updated: 29 April 2020