Undergraduate Course: Modelling of Systems for Sustainability (INFR10088)
Course Outline
| School | School of Informatics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 10 (Year 4 Undergraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This course takes an interacting systems perspective on sustainability, using computational modelling and visualisation to gain understanding of system behaviours and interactions. Relevant complex systems key to sustainability arise from natural evolution (atmosphere, biosphere), social interactions (community, nation, economy), and engineering (energy, transport) - we look at computational models of such systems. Key concepts explored include emergent behaviour, stability and tipping points. Students from across the university will bring knowledge of the type of systems under study, or of computational methods - knowledge of both is not required. Multidisciplinary group projects provide the opportunity to explore systems and gain experience working in interdisciplinary teams. |
| Course description |
The fundamental aim of this course is for students from a variety of backgrounds, including Informatics, to get hands-on experience with specifying, implementing, exploring and presenting results from models of real-world systems that are key to planetary sustainability. The range of such systems is vast, encompassing large parts of earth sciences, engineering, health sciences, social and political sciences. Some key systems include the climate system, many ecosystems, agricultural systems, water systems, public health systems, social systems, international political systems, energy systems and transport systems. We will describe a subset of these systems, and there will be opportunity to develop deeper understanding in the project.
Most of these are what are known as "complex systems", meaning: their behaviour and evolution often cannot be reduced to a few equations or paragraphs of description; they exhibit patterns of emergent global behaviour that are not explicitly encoded in any local interactions; they often exhibit multiple potential stable states, with not-easily-triggered "tipping points" to move to another stable state; stability is often exhibited as a dynamic pattern over time rather than as a fixed state. We will touch on the science of complex systems, focussing on those aspects that are of most relevance to the particular real-world systems we study.
A ubiquitous challenge in sustainability is to appreciate how these individually complex systems interact with each other in the real world to produce unexpected outcomes. The key methodology we will bring to the study of these systems and how they interact is computational modelling and visualisation. We will study specific systems for which there are reasonably tractable computational models and visualisations. For each, we will explore the underlying computational framework, be it a statistical model of observed data, a physical model of known physical / chemical / biological interactions, or an abstract model of ecological or social systems. The modelling paradigms studied and used in practical work will include system dynamics and agent-based modelling, with brief mention of other paradigms such as discrete event and finite-step simulations.
The first half will consist of lecture material covering the key system concepts, the specific systems to be studied, and the computational modelling and visualisation methods used for each system. These will be supplemented by hands-on lab sessions, to explore computational models and visualisations using tools such as NetLogo and Python; and small-group tutorial sessions aimed at multidisciplinary discussions of specific systems. The second half of the semester will be devoted to a group project in which each 3/4-person group will have students from at least 2 and ideally 3 or 4 disciplines; the project will aim to construct and explore a model of one or two complex systems related to sustainability (e.g., energy, economic and political); and project supervision will be provided by staff and PhD students familiar with the project systems and models.
Assessment will be by coursework, aimed at the material covered in the first half of the semester, (systems and modelling paradigms) and a group project report and presentation for the work in the second half of the semester.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | Students from outside the School of Informatics must be comfortable using computer software such as spreadsheets but do not need specific maths background or any programming experience. They should also have some understanding of at least one system relevant to sustainability (see summary and description for examples).
Students must register interest in May the year before the academic year the course is taught (i.e. register in May 2023 for the course taught in academic year 2023/24). |
Course Delivery Information
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| Academic year 2023/24, Not available to visiting students (SS1)
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Quota: 32 |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 18,
Seminar/Tutorial Hours 5,
Dissertation/Project Supervision Hours 5,
Supervised Practical/Workshop/Studio Hours 5,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
163 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
100% coursework
Coursework will involve explaining sustainability modelling concepts, how they are applied in modelling studies, and formal description of models. The second coursework will consist of a group project, which will use the material covered in the lectures, labs and tutorials, to implement a model, or study an existing model, of one or more systems relevant to sustainability. Assessment will be based on a report submitted about the project work, and associated presentation, and this will include reporting of the behaviour of implemented models. |
| Feedback |
Feedback will be given on coursework in progress. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- explain how computational modelling frameworks can be used to understand the behaviours of complex interacting systems involved in sustainability such as social, economic and ecological systems
- investigate a sustainability system question, identify system elements and their interactions, and codify a system model using an appropriate model description framework
- critique and interpret the results / output of models of sustainability systems
- communicate findings of sustainability modelling studies, including uncertainty, to a variety of audiences
- work collaboratively and accountably with other students to formulate, explore and communicate a sustainability system model
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Reading List
1. Railsbeck and Grimm (2019), Agent-based and individual based modelling. 2nd Ed. Princetown University Press [Note that the library has a subscription to the 1st Ed, but getting a subscription to the 2nd Ed is proving problematic.]
1. Principles of Systems Science / George E. Mobus, Michael C. Kalton (2014). Library has online subscription.
2. Thinking in Systems : a primer / Donella H. Meadows ; edited by Diana Wright. (2008). Library has a copy and online subscription. |
Additional Information
| Graduate Attributes and Skills |
Critical thinking, handling complexity and ambiguity, knowledge integration, independent research, planning and organizing, team working, assertiveness and confidence, ethics and social responsibility, self-awareness and reflection, creativity and inventive thinking, decision making, cross-cultural communication, written communication, verbal communication. |
| Keywords | Sustainability,Complex Systems,Modelling,Visualisation |
Contacts
| Course organiser | Dr Nigel Goddard
Tel:
Email: Nigel.Goddard@ed.ac.uk |
Course secretary | Miss Yesica Marco Azorin
Tel: (0131 6)505113
Email: ymarcoa@ed.ac.uk |
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