What Can We Do with Data? Below is an overview of five main approaches to working with data, along with potential outcomes and examples.
1. Exhibit
Goal: Present raw data in a clear, straightforward manner.
Techniques:
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List:Organized bullet points or enumerations of data.
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Table: Rows and columns to compare different aspects easily.
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Infographic: Visually striking displays that combine text, charts, and icons to convey key data points.
Example
- A public dataset of city populations displayed in a table for quick reference.
Reference
- Edward Tufte’s concept of the “data-ink ratio”: Edward Tufte Website
2. Explain
Goal: Provide clear answers to questions through structured analysis and storytelling.
Techniques:
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Data Journalism: Articles or news stories underpinned by data-driven evidence.
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Report: Formal documentation that organizes findings, interpretations, and conclusions.
Example
- A news article explaining election results supported by interactive charts.
Data Storytelling
Dear Data
Dear Data is a year-long, analog data drawing project by Giorgia Lupi and Stefanie Posavec, two award-winning information designers living on different sides of the Atlantic. By collecting and hand drawing their personal data and sending it to each other in the form of postcards, they became friends.
What Goes On At 213
A pocket-book zine showing data visualization through illustration. San Myeong Kim observed people walking past this one door on East 23rd Street and took note of their peculiarities and illustrated them. They pose this question: In a space where infographics is created and consumed entirely digitally, how can I re-incorporate the raw handwritten quality to data visualization (in a fun, silly way)?
Reference
- The Data Journalism Handbook: https://datajournalism.com/read/handbook
3. Explore
Goal: Investigate the data to discover patterns, trends, or questions you didn’t know to ask.
Techniques:
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Dashboards: Interactive interfaces showing multiple linked visualizations.
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Simulations: Models allowing “what-if” analyses or scenario testing.
Example
- A real-time business intelligence dashboard that alerts users to unusual sales patterns.
The Life and Death of Data
Tied in Knots
Reference
- Ben Shneiderman’s mantra: “Overview first, zoom and filter, then details on demand.”
4. Experience
Goal: Reveal deeper meaning or evoke an emotional/intuitive response through creative, immersive, or artistic representations.
Techniques:
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Data Art Piece: Artistic installations that transform data into sculpture or visual art.
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New Media Installation: Interactive exhibits where visitors can engage with data physically or virtually.
Example
- A museum piece visualizing climate change data as a dynamic art display that changes color over time.
Data Art
Poppy Field
Following the end of the First World War, the poppy became a symbol of commemoration. It was among the first plants to spring to life on Europe's devastated battlefields. Poppy Field reflects on the human cost of war
from the beginning of the 20th Century.
Reference
- Lev Manovich’s work on cultural analytics and data art: Software Studies Initiative
5. Enable
Goal: Develop specialized tools or platforms tailored to particular data visualization needs.
Techniques:
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Custom Software: Applications built to visualize specific datasets or domains.
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APIs and Libraries: Extensible codebases that empower broader data analysis and visualization.
Data by Design
A digital book chronicling the history of data visualisation. By retelling the history of data visualization alongside the histories of colonialism and slavery, Data by Design shows how questions of ethics and justice have always been present—and continue to offer lessons to viewers and designers of data visualizations today.
The Data Visualization Society
The Data Visualization Society is a global community of data visualization professionals, educators, and enthusiasts.