VizChitra 2025: India's first community-driven Data Visualization conference

Schools taught us, “We cannot see air, only feel it.” But sadly now, we don’t just feel it deep inside our lungs but also see it with our red, itchy eyes. But there is more than what our irritable eye can see.

This session is about learning to see air using data from monitoring stations, modeling results, and satellites. At the end of the workshop, the participants will build a pollution storyline of a city of their choice.

Workshop structure:

1. Introduction to the primers: (~10 mins) Copies of primers on air quality data and analysis will be distributed, along with a brief description of the content. The primers are designed at high-school level and visualized for the audience to make data connections from generation to usage.

2. Introduction to scenario players: (~30 mins) A lot of air quality data comes from monitoring and modelling efforts. Besides its use to understand absolute air quality, its biggest use is for policy planning - to design an optimal strategy to tackle air pollution. We will demonstrate versions of players (in excel and online) to show how to navigate this data and how to make connections between generating data and designing a strategy - a “what-if” game.

3. Atmospheric Science 101: (~30 mins) It is good to know some jargon in any field. In this session, we will play an interactive “find your partner” card game designed to teach participants the basics of air pollution science. This will help you understand the nuances of the data and make better connections between science and communications, going beyond a mere number-crunching exercise.

4. A data stroll: (~30 mins) Participants would get their hands on different types of air quality data. They would explore simple tables (CSVs) to geospatial data (Shapefiles, GeoJSONs) and satellite data (GeoTIFFs).

5. Narrate your city’s air pollution story: (~75 mins) How do you tell a city’s air pollution story using available datasets. In this session, participants will be guided to tell their, following some examples. Case study material and codes will be provided. At the end of the session, participants would leave with a chart-work they created. Here are some of the air quality visuals and simulators that we created. Here are some of the air quality visuals we created.

We are eager to see how participants would design this data in newer ways.

The sessions are designed to be highly interactive, featuring:

1. Discussion of comic-style primers
2. A card game to understand basic jargon
3. An interactive time with “what-if” scenario players
4. Case studies in the final session, using pre-curated datasets. Participants will collaborate in groups to explore these datasets, analyze examples, and create meaningful stories based on their findings.
5. Time permitted, a short quiz to engage participants and assess their understanding.

Key Takeaways

Participants would-

1. Understand the role of visual communications in air quality management via comic-style books and games.
2. Understand the role of environmental data, looking beyond colors and aesthetics.
3. Learn to tell visual air pollution stories without missing out on scientific rigor.
4. Learn the use of Google Earth Engine (GEE) to obtain satellite data for any region and chart it.
5. Learn the application of simple calculators and linear programming methods - to combine various data fields.
6. Leave with a case study and a technology stack they are comfortable with (Excel, QGIS, Python-Jupyter Notebook, Tableau, etc.) to play with air quality data.

Prerequisites:

The session would be useful for journalists, public policy analysts, researchers, and students. Prior experience working with Excel sheets and CSVs would be sufficient to start narrating a simple story. Data Viz apps like DataWrapper, Flourish, Tableau etc., can be add-ons, but they are not necessary. Participants who know can use Python (matplotlib, sklearn, bokeh, streamlit, pandas, geopandas, rasterio) and QGIS can leverage them to tell more nuanced stories. Nevertheless, we’ll focus on telling whatever story you can tell using the available data and science.

Participants are expected to carry their personal laptops with any data processing and visualisation software of their interest (Excel, Python, R, QGIS).

Participants can go through our Air Quality Modeling tools page for more details and resources.

The workshop will be handled by Dr. Sarath Guttikunda, Founder/Director of UrbanEmissions.info and Sai Krishna Dammalapati, Research Associate.