The Data Visualization of Carbon Footprint

  • Climate change has been a serious issue over the past decades, carbon footprint is considered the main factor for getting the situation worse. All the authorities and organizations are calling on people to stop climate change. But many people are not aware of it because climate change is usually illustrated by a bunch of numbers and data, it is not specified enough for ordinary people. Therefore, in this project, I wanna make climate much easier to understand in terms of visualising the carbon footprint.

 

  • I want to start with a campaign from Carbon Visuals, what they achieved is to visualize the carbon footprint in New York city in numerous blue spheres. It was such a huge visual impact for people to realize the fact that massive amounts of carbon footprint can be produced on a daily basis. This campaign refers to the idea of data visualization. But before diving into the data visualization, we need to understand the data first. What kind of data can be visualized?

 

  • There are two ways of looking at data. Firstly, the data is either qualitative or quantitative. Carbon footprint is considered quantitative data as it is valued for characteristics shared by all or many units in a dataset and it can be gathered in different fields. 

 

  • Secondly, the data is either structured or unstructured. The carbon footprint is unstructured when it has a visual presence pretty straightforward, which seems to be “raw” compared with data being collected by the experts.

 

  • Even though the campaign from Carbon Visuals was successful in terms of creativity, I still think that it is not interactive as there is no function for people to engage with. So I designed a mobile application called ‘InVisible’ as I am keen to touch on interactivity a bit more. The AR technology is applied as a booster for interactivity, With the “InVisible”, people can use their front cameras to scan or capture objects around, and carbon footprints will be detected automatically from objects such as vehicles and factories, these carbon footprints will be shown as numerous floating red asterisks in real-time. The use of red colour matches the aesthetic judgement as red colour generally symbolizes danger. 

 

  • The ideal users for the  “inVisible”, at least at the early stage of the App, would be mostly university students who are well-educated and capable of forming their own mindset through interpretations. However, it will be available for everyone eventually to avoid social issues like uneven power relations, where data-driven conversations are only aroused by knowledgeable people. This public discussion also refers to the concept of social discourse. Semiotically, people can generate ideas and share them once they get access to semiotic resources, and then social action can be taken.

 

  • So, what is next for the “InVisible”? There will be definitely more functions coming out in order to stimulate interactivity continuously. These new functions will be focused on mobile media artwork as the multisensorial is a driving force for the movement of specific forms of sociality. Also, I am really interested in the concept of “Hybrid Realities” which is bridging digital location information to physical environment, so I will definitely touch on that later.

 

 

References:

Hjorth, L, de Souza e Silva, A & Lanson, K (eds) 2020, ‘Mobile Media Art: An Introduction, The Routledge Companion to Mobile Media Art, Taylor & Francis Group, Milton, pp.1-8, viewed 1 April 2022, <https://ebookcentral.proquest.com/lib/rmit/reader.action?docID=6267354&ppg=34> 

Kennedy, H & Engebretsen, M, 2020, ‘Introduction: The relationships between graphs, charts, maps and meanings, feelings, engagements’, Data visualization in society, Project Muse, Baltimore, Maryland, pp.19-32, viewed 1 April 2022, <https://www-degruyter-com.ezproxy.lib.rmit.edu.au/document/doi/10.1515/9789048543137-005/html>.