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<!doctype html>
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<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="chrome=1">
<title>ID 413 - Information Graphics and Data Visualization</title>
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<h1 class="header">Information Design Lab</h1>
<p class="header">The digital presence of <nobr>Information Design Lab</nobr>, IDC, <nobr>IIT Bombay</nobr></p>
<!-- For a while, we don't need these button
<ul>
<li><a class="buttons github" href="https://github.com/info-design-lab">GitHub Profile</a></li>
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</header></a>
<section>
<a id="top" class="anchor" href="#top" aria-hidden="true"><span class="octicon octicon-link"></span></a>
<h2>ID 413 - Information Graphics and Data Visualization</h2>
<p>Instructor: <strong>Prof. Venkatesh Rajamanickam</strong></p>
<p><strong>Registration</strong>: ASC may require some students to register manually. If so, please use <a href="files/ID413 Data Viz Regn Form.pdf">this registration form</a> and take my signature by Jan 9<sup>th</sup>, 11 am.</p>
<p><strong>Timings</strong>: Wednesdays and Fridays 9:30 am to 11 am (LT 303), and some Saturdays at IDC.</p>
<p><strong>Office Hours</strong>: Fridays 11:30 AM to 1:00 PM at my office in Transit Building, Room No. 330 or by appointment.</p>
<p>If you're on Github, you can <em>watch</em> the <a href= "https://github.com/info-design-lab/ID413-DataViz">Github course repo</a> for updates.</p>
<a id="top" class="anchor" href="#top" aria-hidden="true"><span class="octicon octicon-link"></span></a>
<h3>Course Overview</h3>
<p>Information graphics reveal the hidden, explain the complex and illuminate the obscure. Constructing visual representation of information is not mere translation of what can be read to what can be seen. It entails filtering the information, establishing relationships, discerning patterns and representing them in a manner that enables a consumer of that information construct meaningful knowledge.</p>
<p>Recent advances in technology have enabled us with means for creating, recording and analysing incredible amounts of data. Where once data was scarce, it is now available in abundance. The field of Computer Science has made great strides in creating capabilities for data handling and analysis. However the techniques required to most effectively display and communicate data are somewhat neglected. This design course aims to fill the gap by teaching techniques for creating effective visualizations based on principles from graphic design, visual art, perceptual psychology, and cognitive science.</p>
<h3>Course Objectives</h3>
<p>This course will provide students with the foundations necessary for understanding and extending the current state of the art in data visualization. By the end of the course, students will be able to:
<ul>
<li>Gain an understanding of the key techniques and theory used in visualization, including data models, graphical perception and techniques for visual encoding and interaction.
<li>Plan for data-based storytelling through charts, maps, and diagrams.
<li>Gain practical experience building and evaluating visualization systems.
<li>Gain the ability to read and discuss research papers from the visualization literature.
</ul>
</p>
<h3>Course Contents</h3>
<p>This course will provide students with the foundations necessary for understanding and extending the current state of the art in data visualization. By the end of the course, students will be able to:
<ul>
<li>Information visualization overview, historical perspective
<li>Vision, perception and cognition principles of information visualization
<li>Data principles, models, dimensions and analysis
<li>Information taxonomy
<li>Visual encoding of data
<li>Mapping, cartography, geo-visualization
<li>Visualization tools and strategies
<li>Data stories and presentation
<li>Short exercises and a mini project in visual representation of data
</ul>
</p>
<a id="schedule" class="anchor" href="#schedule" aria-hidden="true"><span class="octicon octicon-link"></span></a>
<h3>Schedule</h3>
<table>
<tr>
<th style="width: 120px">Date</th><th>Content</th>
</tr>
<tr>
<td>6<sup>th</sup> Jan, 2016
</td>
<td>Introduction to Information Grahics & Data Visualization - Part 1
</td>
</tr>
<tr>
<td>8<sup>th</sup> Jan, 2016
</td>
<td>Introduction to Information Grahics & Data Visualization - Part 2 <a href="files/01_Introduction_6Jan2016.pdf">(View slides)</a>
<p>
<<<<<<< HEAD
Complete the 2 class participation exercises (see slides) and submit them by next class (13th Jan). For ecercise 1, you can simply hand draw on a A4 size paper, and for exercise 2, you should put the photographs in a PDF file (with explanatory text where required) and email it to me (subject line: ID413-exercise 2).
=======
Complete the 2 class participation exercises (refer to slides) and submit them by next class.
>>>>>>> origin/master
</p>
</td>
</tr>
<tr>
<td>13<sup>th</sup> Jan, 2016
</td>
<td>
To be updated.
</td>
</tr>
</table>
<p>
<em>Links to slides will be added after the respective lecture</em>
</p>
<a id="top" class="anchor" href="#top" aria-hidden="true"><span class="octicon octicon-link"></span></a>
<h3>Assessment</h3>
<p>For this course, you will be assessed as follows:</p>
<ul>
<li>4 individual assignments (20%)
<li>1 group project (40%)
<li>No midsem
<li>Endsem (30%)
<li>Attendance & class participation (10%)
</ul>
<a id="top" class="anchor" href="#top" aria-hidden="true"><span class="octicon octicon-link"></span></a>
<h3>Textbook</h3>
<p>There is no recommended text for the course. All lecture slides will be made available as PDFs after the lectures for your reference. However lecture slides alone won’t be sufficient to prepare for the end semester exam. So keep a notebook and take notes.</p>
<a id="top" class="anchor" href="#top" aria-hidden="true"><span class="octicon octicon-link"></span></a>
<h3>Reference Books</h3>
<ol>
<li>Bertin, Jacques (1967). Semiology of Graphics: Diagrams, Networks, Maps. Esri Press.
<li>Cairo, Alberto (2013). The Functional Art. New Riders
<li>Few, Stephen (2012). Show Me the Numbers: Designing Tables and Graphs to Enlighten. Analytics Press.
<li>Fry, Ben (2012). Visualizing Data: Exploring and Explaining Data with the Processing Environment. O'Reilly Media.
<li>Harmon, Katherine (2003). You Are Here. Princeton Architectural Press.
<li>Harris, Robert L. (2000). Information Graphics: A Comprehensive Illustrated Reference. Oxford University Press.
<li>Helfand, Jessica (2002). Reinventing the Wheel. Princeton Architectural Press.
<li>Holmes, Nigel (1991). Designer's Guide to Creating Charts and Diagrams. Watson-Guptill.
<li>Holmes, Nigel (2005). Wordless Diagrams. Bloomsbury.
<li>Institute for Information Design Japan (2005). Information Design Source Book. Graphics-Sha.
<li>Jacobson, Robert (2000). Information Design. The MIT Press.
<li>McCloud, Scott (1994). McCloud, Scott (1994). Understanding Comics Understanding Comics. Harper . Harper.
<li>Mijksenaar, Paul and Westendorp, Piet. Open Here: The Art of Instructional Design.
<li>Mijksenaar, Paul (1997). Visual Function: An Introduction to Information Design. Princeton Architectural Press.
<li>Myer, Eric. K. (1997). Designing Infographics. Hayden Books.
<li>Tufte, Edward (1990). Envisioning Information. Graphics Press.
<li>Tufte, Edward (1997). Visual Explanations: Images and Quantities, Evidence and Narrative. Graphics Press.
<li>Tufte, Edward (2001). The Visual Display of Quantitative Information. Graphics Press.
<li>Ware, Colin (2012). Information Visualization, Third Edition: Perception for Design. Morgan Kaufmann.
<li>Yau, Nathan (2011). Visualize This: The FlowingData Guide to Design, Visualization, and Statistics. Wiley.
<li>Yau, Nathan (2013). Data Points: Visualization That Means Something. Wiley.
</ol>
<a id="contact" class="anchor" href="#contact" aria-hidden="false"><span class="octicon octicon-link"></span></a>
<h3>Contact</h3>
<p>
You can reach Prof. Venkatesh Rajamanickam <a href="mailto:venkatra@iitb.ac.in">via email</a>
</p>
</section>
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<p><small>Powered by <a href="http://pages.github.com">GitHub</a> <a href="https://github.com/info-design-lab/ID413-DataViz">Link to Github Repo</a></small></p>
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