A recent article in Environmental Technology Online reports on a community-based science project called ‘Float’ that is actually part-science and part-art project. The idea is that pollution-sensitive kites will be flown over Beijing. These kites contain Arduino pollution-sensing modules and LED lights and will indicate levels of volatile organic compounds, carbon monoxide and particulate matter by changing colour to green, yellow or red depending on the pollutant levels. The kites are attached to GPS device loggers and the real-time data website Cosm.
The project is designed by students Xiaowei Wang from Harvard’s Graduate School of Design and Deren Guler from Carneige Mellon and is designed to involve local residents in data collection. The project relies on public funding and is still raising funds. The project derives its funds from Kickstarter, a website devoted to creative projects and obtaining funding for such projects (The Float project on Kickstart). The project also has funding from the Black Rock Arts Foundation and the Awesome Foundation.
The project has generated a lot of interest on the Web:
Fighting China’s Pollution Propaganda, with Glowing Robot Kites For the People
Pollution-detecting kites to monitor Beijing's air quality
Glowing Pollution Sensor Equipped Kites Replace Beijing's Stars
Kickstarter Project Plans to Measure Beijing Pollution Using Kite Sensors
Only a couple of comments and an expression of interest in the results really.
The project is undoubtedly part of the growing and, in my view, superb trend towards more inclusive community or participatory science (choose whichever term you prefer, Guler uses citizen-science). The ideal of getting local communities involved in the data collection as well as involving them in all aspects of the research process is an excellent way to raise awareness of an issue as well as educate people about the scientific approach and its problems and potentials. The Float project has involved local communities, young and old, from the start with workshops in Beijing and as well as in the design of the kites. In terms of how to organise a community-based, participatory science project it is one that I will advice my students to look at. It is just a shame that the descriptions of the project veer from highlighting the science to highlighting the arts aspects as if the two are, or need to be, distinct. It should also be remembered that this project, as any project involved in monitoring pollution, is entering the political as well as the scientific arena. Involving local populations is a political act (as is their agreement to involvement) as much as the monitoring of pollution by the American Embassy or the siting of monitoring sites by the Chinese. Local is as political as the national or international, but the nature of the act does not necessarily mean the data is political bias only that data collection is for a purpose.
The project is designed by students Xiaowei Wang from Harvard’s Graduate School of Design and Deren Guler from Carneige Mellon and is designed to involve local residents in data collection. The project relies on public funding and is still raising funds. The project derives its funds from Kickstarter, a website devoted to creative projects and obtaining funding for such projects (The Float project on Kickstart). The project also has funding from the Black Rock Arts Foundation and the Awesome Foundation.
The project has generated a lot of interest on the Web:
Fighting China’s Pollution Propaganda, with Glowing Robot Kites For the People
Pollution-detecting kites to monitor Beijing's air quality
Glowing Pollution Sensor Equipped Kites Replace Beijing's Stars
Kickstarter Project Plans to Measure Beijing Pollution Using Kite Sensors
Only a couple of comments and an expression of interest in the results really.
The project is undoubtedly part of the growing and, in my view, superb trend towards more inclusive community or participatory science (choose whichever term you prefer, Guler uses citizen-science). The ideal of getting local communities involved in the data collection as well as involving them in all aspects of the research process is an excellent way to raise awareness of an issue as well as educate people about the scientific approach and its problems and potentials. The Float project has involved local communities, young and old, from the start with workshops in Beijing and as well as in the design of the kites. In terms of how to organise a community-based, participatory science project it is one that I will advice my students to look at. It is just a shame that the descriptions of the project veer from highlighting the science to highlighting the arts aspects as if the two are, or need to be, distinct. It should also be remembered that this project, as any project involved in monitoring pollution, is entering the political as well as the scientific arena. Involving local populations is a political act (as is their agreement to involvement) as much as the monitoring of pollution by the American Embassy or the siting of monitoring sites by the Chinese. Local is as political as the national or international, but the nature of the act does not necessarily mean the data is political bias only that data collection is for a purpose.
As with most community-based projects, however, there is the issue of belief, trust or confidence in the data collected. These projects do tend to illustrate quite nicely the continuing divide between the ‘specialist’ or ‘expert’ and the ‘public’ (I would say amateur, but much of British science in the nineteenth and early twentieth century only developed because of amateurs!) The expert has been trained and accepts certain methods as being appropriate for data collection. Control and standardization are essential in ensuring what is termed ‘intersubjectivity communication’ between researchers – basically it means I know what you did because that is how I was trained to do it, so I trust your data as being real. Guler seems to downgrade the status of the data collected even before the project really begins by stating:
‘We’re trying to interact with people on the street and see what they’re tying to do with the information they see. I don’t plan to argue that this is the most accurate data because there are many potential reasons for differences in air quality reports. We want to just keep it up, upload the data, and focus on that more after we come back’.
My impression is this statement is a great get-out clause for ‘official’ monitoring be it by the Chinese or atop the American Embassy. I wouldn’t’ be so pessimistic. The aims of the project in terms of improving public understanding of air pollution, its impact on health and the visualization of pollution through the kites are all excellent and likely to be successful. The data collected is also of value. The ‘official’ pollution monitoring sites probably conform to national or international standards for static sites in terms of equipment and monitoring periods. The kite data does not necessarily provide comparable data to these sites. The kites are mobile and collect data on levels that can be spatially references (I assume in 4 dimensions). They provide a different perspective on atmospheric pollution rather as a spatially altering phenomenon, something the official monitoring sites can not provide. It could even be argued that the kite data provides information on pollution as experienced by the population (although the population is unlikely to move across the sky at the height of the kites!) The important thing to remember is that there is not one, single correct measure of atmospheric pollution; there are merely different representations of atmospheric pollution. The official static sites have the advantage of having clearly defined protocols that ensure the data or information they collect is immediately comparable with data or information collected at similar monitoring sites globally. The Float project is generating a different and novel set of data or information. This may require a different approach to thinking about the information and its interpretation (Guler seems to suggest this with some hints at triangulation of trends) and in how confidence or belief in the information is assessed either qualitatively or quantitatively. I will be very interested to see what form the results and interpretation takes. Good luck with the project!
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