Postgraduate Course: Representing Data (fusion online) (EFIE11001)
Course Outline
| School | Edinburgh Futures Institute |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
| Course type | Online Distance Learning |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | *EFI Shared Core Course*
Please Note:
This course is only available to students enrolled on one of Edinburgh Futures Institute's postgraduate programmes.
This course will introduce students to practical data representation. It will enable students to understand data visualisation theory and practice, while simultaneously inviting them to challenge and extend these concepts throughout the course. Students will examine a range of different methodologies and practices for representing data in a variety of formats including physical and embodied formats. |
| Course description |
The course will give an overview of key aspects of data representation, from analysis of data to aesthetics, form and ergonomics. Students will be introduced to selected readings on the theory of data representation and be asked to engage with a variety of datasets. From this they will discuss different ways to represent, or potentially misrepresent, data as well as the role of narrative and medium in designing an effective representation.
Students will explore these datasets through different visualisation concepts and techniques, supported by notebook-based computer worksheets. Then, working in groups, they will also explore a dataset related to a challenge theme and work up a data representation as a visualisation, or physicalisation using other construction techniques. Alongside this the groups will document this process and the considerations made in producing their final output.
Taught sessions will cover a mix of time spent on:
(1) Lectures
(2) Code-alongs
(3) Group discussion, and group collaboration
(4) Supported workshop time focussed on visualisations and other forms of data representation
Edinburgh Futures Institute (EFI) - Online Fusion Course Delivery Information:
The Edinburgh Futures Institute will teach this course in a way that enables online and on-campus students to study together. This approach (our 'fusion' teaching model) offers students flexible and inclusive ways to study, and the ability to choose whether to be on-campus or online at the level of the individual course. It also opens up ways for diverse groups of students to study together regardless of geographical location. To enable this, the course will use technologies to record and live-stream student and staff participation during their teaching and learning activities. Students should note that their interactions may be recorded and live-streamed. There will, however, be options to control whether or not your video and audio are enabled.
As part of your course, you will need access to a personal computing device. Unless otherwise stated activities will be web browser based and as a minimum we recommend a device with a physical keyboard and screen that can access the internet.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
| Not being delivered |
Learning Outcomes
On completion of this course, the student will be able to:
- Analyse the form of a dataset and demonstrate basic skills in producing various representations of these data.
- Engage critically with the fundamentals of theory and practice of data visualisation and representation.
- Work well in a team to effectively communicate data to a particular audience.
- Engage in constructive critiques of the design and narrative of data representations.
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Reading List
Indicative reading list:
The Visual Display of Quantitative Information (2001), Tufte
How Charts Lie - Getting Smarter about Visual Information (2019), Cairo
Visualization Analysis and Design (2014), Munzner
The Functional Art (2011), Alberto Cairo Design for Information (2013), Mireilles
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Additional Information
| Graduate Attributes and Skills |
Students will develop key visualization skills by directly engaging with complex real world data.
For each final visualisation product, they will produce collaboratively a written design document.
Working in small interdisciplinary teams, they will develop communication, autonomy, accountability and skills in working with others. |
| Keywords | Data,Data Representation,Data Visualisation,Data Physicalisation |
Contacts
| Course organiser | Mrs Dorsey Kaufmann
Tel:
Email: dkaufma2@ed.ac.uk |
Course secretary | Miss Abby Gleave
Tel: (0131 6)51 1337
Email: abby.gleave@ed.ac.uk |
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