COURSE SUMMARY
Course Title: 
Data Visualization
Course Code: 
18CS708
Year Taught: 
2018
Degree: 
Postgraduate (PG)
School: 
School of Engineering
Campus: 
Coimbatore

'Data Visualization' is an elective course offered in M. Tech. in Computer Science and Engineering program at School of Engineering, Amrita Vishwa Vidyapeetham.

Value of Visualization – What is Visualization and Why do it: External representation – Interactivity – Difficulty in Validation. Data Abstraction: Dataset types – Attribute types – Semantics. Task Abstraction – Analyze, Produce, Search, Query. Four levels of validation – Validation approaches – Validation examples. Marks and Channels

Rules of thumb – Arrange tables: Categorical regions – Spatial axis orientation – Spatial layout density. Arrange spatial data: Geometry – Scalar fields – Vector fields – Tensor fields. Arrange networks and trees: Connections, Matrix views – Containment. Map color: Color theory, Color maps and other channels.

Manipulate view: Change view over time – Select elements – Changing viewpoint – Reducing attributes. Facet into multiple views: Juxtapose and Coordinate views – Partition into views – Static and Dynamic layers – Reduce items and attributes: Filter – Aggregate. Focus and context: Elide – Superimpose - Distort – Case studies.

TEXTBOOKS/REFERENCES

  1. Tamara Munzner, Visualization Analysis and Design, A K Peters Visualization Series, CRC Press, 2014.
  2. Scott Murray, Interactive Data Visualization for the Web, O’Reilly, 2013.
  3. Alberto Cairo, The Functional Art: An Introduction to Information Graphics and Visualization, New Riders, 2012
  4. Nathan Yau, Visualize This: The FlowingData Guide to Design, Visualization and Statistics, John Wiley & Sons, 2011.

At the end of the course the students will be able to

  Course Outcome Bloom’s Taxonomy Level
CO 1 Understand the key techniques and theory behind data visualization L2
CO 2 Use effectively the various visualization structures (like tables, spatial data, tree and network etc.) L3
CO 3 Evaluate information visualization systems and other forms of visual presentation for their effectiveness L4, L5
CO 4 Design and build data visualization systems L4, L5