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Taught by the IIHS Urban Informatics Lab, Data Visualisation in Research and Practice will give participants practical introduction to visualisation of quantitative data using data sets, and questions largely related to urban research and practice. It aims to lay the foundation on the design principles for data visualisation, and to impart the skills needed to create software-based visuals, including charts, maps, dashboards and infographics. Easy-to-use Graphical User Interface (GUI) tools will be used for hands-on sessions. Basic familiarity with simple tabular data sets and spreadsheet tools like MS Excel is expected. No prior knowledge of visualisation is needed. The course is delivered online, through a mix of lectures, live demonstrations, quizzes and practice sessions in small groups.


Who this is for:

  • Young researchers working in academia or in the social sector
  • PhD scholars and Master’s students who would like to acquire data visualisation skills
  • Practitioners employed in the government, NGOs or private sector, working broadly in the areas of urbanisation, sustainable development or public policy


This course will enable participants to:

  • Visualise data to communicate powerful insights
  • Identify the appropriate types of charts given a problem or topic and the corresponding data set
  • Avoid common mistakes and misrepresentations in data visualisation
  • Create commonly used types of data visualisation for tabular and geospatial data using GUI tools like Tableau and Data Wrapper
  • Understand public data sets like Census of India, National Family Health Survey, etc., and the methods to bring out patterns in them

Shriya Anand

Shriya is a faculty member at the Indian Institute for Human Settlements, teaching topics related to urban economic development and quantitative research methods. She anchors the Urban Informatics Lab. Shriya has worked extensively with datasets from the Census of India, the National Sample Survey Organisation (NSSO), and the Economic Census for various research projects. Her research at IIHS is primarily centred on the Indian urban economy and economic geography, with a particular focus on the role of employment in urban development and poverty reduction. Shriya holds a Master’s in Public Affairs with a concentration in Economics from Princeton University, and a Master’s in Mathematics from Cambridge University, UK.



Sooraj Raveendran

Sooraj works in the Urban Informatics Lab at IIHS. His current focus is in applying statistical models to disaggregate previously aggregated demographic and socioeconomic data from the Census and national-scale sample surveys. He applies computational and statistical methods on urban data to develop a comprehensive understanding of India’s complex urban transformation. Sooraj’s academic training is in computer science and statistics. He has been teaching multiple quantitative methods courses in the Urban Fellows Programme at IIHS. Sooraj was also part of multiple quantitative methods and data visualisation training workshops for different organisations, including Atal Bihari Vajpayee Institute of Good Governance and Policy Analysis (AIGGPA) in Bhopal, and GIZ (Deutsche Gesellschaft für Internationale Zusammenarbeit) and Center for Internet & Society (CIS) in Bangalore.



Herry Gulabani

Herry works in the Urban Informatics Lab at IIHS and applies quantitative methods, mixed methods and spatial data analysis across multiple practice and research projects. He has worked on projects related to urbanisation, economic development and transit-oriented development. In addition to the national-scale public data sets, Herry is familiar with various housing and real estate data sets available at different spatial scales. He regularly teaches courses in the Urban Fellows Programme and has also taught capacity building workshops on data visualisation. Herry has a Bachelor’s in Civil Engineering from Nirma University and a Master’s in Urban Planning from University of Southern California.

Programme Structure

  • Delivered through a combination of lectures and discussions, tool demonstrations, hands-on activities in small groups, presentations and quizzes
  • Active hand-holding and individual feedback from the faculty
  • Ample peer-learning opportunities


Key Differentiators

  • Live examples relevant to urban research and practice in the Indian context
  • Includes data sets from the Census of India and national-scale sample surveys
  • Heavy focus on hands-on practice


Session Plan


Session 1
This introductory session on data visualisation will cover the basic principles, best practices and things to avoid. Through several examples, the participants will understand the appropriate types of charts to show the distributions of different types of variables and their relationships. There will be an interactive part of the session dedicated to reading, interpreting, and critically analysing several visualisations.
Session 2

This session focuses on putting several of the concepts learned in the first session to practise. Using multiple data sets from sources like the Census of India and NFHS, visualisation tools like Datawrapper and Tableau Public will be demonstrated. This will include all the commonly used charts like bar graphs, pie charts, scatter plots, etc. The participants will then get the opportunity to try creating multiple charts on their own, with active guidance from the instructors.

Session 3

In this session, the initial part will focus on the necessary conceptual understanding of geospatial maps and will do an overview of different types of maps used in different contexts and the corresponding digital representations and file formats. Then, a few example data sets will be used for demonstration of tools to create choropleth maps, point location or symbol maps and heatmaps. Geocoding tools and techniques will also be briefly discussed.

Session 4

This session has two parts: In the first half, participants are given time to explore one of the data sets available in the context of the problems shared. During the second half of the session, the groups will present the visualisations they made to the class and get feedback from each other and from the faculty. Improvements and alternative representations will be discussed.

Week 1

Friday, 18 August 2023
02:00 pm – 03:30 pmIntroduction to Data Visualisation – basic principles and best practices (Part 1)
04:00 pm – 05:30 pmIntroduction to Data Visualisation – basic principles and best practices (Part 2)
Saturday, 19 August 2023
02:00 pm – 03:30 pmVisualising examples using public data sets
04:00 pm – 05:30 pmHands-on practice


Week 2

Friday, 25 August 2023
02:00 pm – 03:30 pmBasics of visualising Geo-spatial data sets
04:00 pm – 05:30 pmTableau examples
Saturday, 26 August 2023
02:00 pm – 03:30 pmGroup exercises
04:00 pm – 05:30 pmPresentations and feedback

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