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The University of Southampton

COMP6214 Open Data Innovation

Module Overview

Open data, pitched as the raw material of the new industrial revolution, holds great promise, but how do you exploit this new resource? This course is specifically designed to give students a greater understanding on how to innovate with open data. This course introduces the tools, techniques and skills required to rapidly innovate using data and how to pitch these ideas to potential investors. The course balances technical and non technical content throughout allowing development in all skill areas required to make a career in rich applications using open data.

Aims and Objectives

Module Aims

To explain how to innovate with open data

Learning Outcomes

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

  • Main current debates within the discipline and theories informing these debates
Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • Identify innovation opportunities for open data
  • Critically evaluate a large range of Infographics and interaction techniques suitable for different tasks
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • Pitching an innovative idea to industry leaders
Subject Specific Practical Skills

Having successfully completed this module you will be able to:

  • Critically evaluate and apply suitable UX and human engagement factors to build a compelling rich application
  • Apply appropriate validation, cleaning and transformation to use, reuse and combine a multitude of complex datasets


Technical content: - Open Data formats (CSV, JSON, XML, RDF) - Web technologies (HTML5, Javascript, JQuery) - Validating and cleaning data (csvlint, jsonlint, open refine) - Visualising data (D3.js) Non-technical content: - Defining open data, benefits and risks - Inforgrapics and interaction - Innovation and opportunities analysis - UX design - Human engagement and addiction - Pitching to investors

Learning and Teaching

Wider reading or practice40
Completion of assessment task62
Preparation for scheduled sessions12
Follow-up work12
Total study time150

Resources & Reading list

Information Graphics. 

HTML5 Foundations. 

JavaScript & JQuery: Interactive Front-end Web Development. 

Semantic Web Programming. 

Interactive Data Visualization for the Web. 

Managing Technology Entrepreneurship and Innovation. 

Best practices in data cleaning: a complete guide to everything you need to do before and after collecting your data. 

Information Visualization: Perception for Design. 

Contemporary Intellectual Property: Law and Policy. 

Open Data Now: The Secret to Hot Startups, Smart Investing, Savvy Marketing, and Fast Innovation. 

HTML & CSS: Design and Build Web Sites. 

Open Business Models: How To Thrive In The New Innovation Landscape. 

The Visual Display of Quantitative Information. 



MethodPercentage contribution
Application 30%
Infographics and Interaction 20%
Innovation Pitch 30%
Report 20%


MethodPercentage contribution
Coursework assignment(s) 100%


MethodPercentage contribution
Coursework assignment(s) 100%

Repeat Information

Repeat type: Internal & External

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