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New Course Discourse // MA Data Visualisation


Written by
Dayna McAlpine
Published date
27 June 2018

London College of Communication’s MA Data Visualisation course is driven by the intelligent interrogation of data and intensive practice-led research, where students research, interpret, critique and visualise data using a range of media, tools and techniques.

The course is led by Henrietta Ross, a designer and LCC alumna who is interested in the social role of design as well as the developing disciplines of service and transformation design.

We caught up with Henrietta to hear more about her vision for the course, top tips for applicants and how students are shaping this new exciting discipline…

Tell us about MA Data Visualisation, how did the course develop and what makes it different?

This course was developed in response to the increasing number of data visualisation and information design focused projects which students and tutors within the Design School at London College of Communication have been producing in recent years.

Both the sophistication of these projects and the deep and sustained interest in this area that they evidence, prompted us to develop this new MA dedicated to supporting students to develop their own, independent research-led inquiry into the subject specialism of data visualisation.

This course is distinct from other programmes within the Design School, LCC and UAL because of its particular emphasis on supporting students to develop the tools, experience and understandings to work with complex data in a design context.

It is through the development and application of a design method for working with data that we expect students on this course to not only establish a specialist body of knowledge and expertise in this area, but – though their work, research, and collaboration with external partners – shape and define this new and emerging discipline.

Why are you launching this course now?

In part in response to the demand from students and prospective students for a programme of study which will equip them to engage with, and have impact on the field of design and our wider social and cultural context, through the specialism of data visualisation. But also, to meet the demand from a wide range of areas of industry and academia for practitioners with the ability to visualise data.

Crucially, however, we are concerned to ensure that this practice is not confined to a familiarity with a set of tools and how to use them, rather that this course responds to the increasing need for practitioners with an understanding of the social and ethical implications of working with data who have explored and helped to shape it’s possibilities and its parameters.

What is the basic structure of the course and what kind of projects can students expect to engage with?

This course recognises the diverse backgrounds students might bring to this programme of study – many could be graphic design students or practitioners, but skills and understandings established in fields such as journalism, the social sciences, user experience design, programming, or web development could also be a valid basis for study in the area of data visualisation. As such, the initial phase of this course will focus on fundamental design principals, practice and research methods – supporting students establishing the core design methodologies to equip them to work in this context.

The 45 week (4 term) course will begin with 3 parallel units in the first term. The first will focus on the theoretical context of data visualisation, investigating – through a mixture of lectures, seminars and workshops – where this practice sits in relation to fields such as graphic design, data science and user experience design.

The second unit will focus on visualisation tools, data sets and data stories. Here we’ll focus on fundamental design principals such as colour, visual grammar and typography through a series of hands-on workshops. Further exploratory workshops with external practitioners will go on to interrogate the definition of data as well as experiment with the practice of constructing information design and data visualisation.

Underpinning these units will be the major project proposal which will be informed by an exploration of design methods and the social, cultural, political and ethical dimensions of data visualisation work.

In the second and third terms we intend to work on two briefs set by external partners from leading London data visualisation practices. In addition the collaborative project will support students developing work in partnership with their peers – from their own course or across the university.

The fourth and final term is dedicated to supporting students developing, refining and completing their major project – a body of self-initiated research work culminating in a project outcome, as well as a critical reflective report. Progress on this piece of work will also have been supported throughout terms two and three with lectures, seminars and tutorial sessions.

What is the advantage of studying the course at LCC?

This course will draw on the rich history of design research and education here at London College of Communication. Working within a community of practice, within the Design School and neighbouring the Screen and Media Schools offers the opportunity to engage with a variety of diverse disciplines, and draw on the expertise of a wide range of specialist technicians, researchers, tutors and lecturers.

Our location and our reputation, as well as the strength of our alumni network, mean we can attract guest lecturers and expert practitioners who are leaders in their fields, and are able to collaboratively develop projects with a variety of external partners and stake-holders.

What skills/interests do you look for from applying students?

The most important attribute for prospective students is an enthusiasm for the subject and a commitment to their learning as well as their personal and professional development. An interest in, and understanding of, research in a design context, or a willingness to engage with this activity is also something we look for in postgraduate students.

However, we are interested in engaging with, and would support applications from, prospective students with a variety of academic or professional backgrounds. Some applicants from outside of an art and design discipline might be concerned about the requirement to submit a portfolio of work on application. The course team are always happy to be in touch with prospective students outside of the formal application process to discuss their suitability for the course and identify how best to demonstrate their experience and interests in order to meet the entry requirements.

Where could this course lead graduates in terms of employment/future projects?

The MA Data Visualisation course supports students developing both their practice and their self-initiated research. As such, we would expect graduates to be equipped to go on to further research in an academic context, to practice as data visual specialists in a professional context or to continue to develop their work as designer researchers, independently or in collaboration.

An interest in working effectively with data is becoming increasingly common across sectors from design to policy, healthcare to finance and banking – reflecting the breadth of possible directions graduates could take on completing this course.

Finally, can you tell us a bit about your own experience and background in teaching?

Before taking up this role, I was a lecturer on the Post Graduate Diploma Design for Visual Communication in the Design School here at LCC. Alongside my teaching practice I continue to work as a graphic designer at Soapbox – a London design studio specialising in work for think tanks and on public policy projects – where information design and data visualisation is a key part of our work. Prior to that I worked on freelance projects for organisations including Advocacy International while also developing and delivering the Infographic Storytelling short course here at LCC.

Find out more about MA Data Visualisation 

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