The Empirical Citizen

Posted on Posted in Citizen Science, Tools

The Christian Science Monitor this week highlighted a story about “citizen scientists” who, as amateurs, contribute individual observations to a larger database in order to track scientific and social trends. Project Budburst was featured in the article, a group that organizes citizen scientists to report data on the blooming of trees, shrubs, and other plants in order to track climate data over seasonal cycles. It also used the example of birdwatchers organized by the Cornell Laboratory of Ornithology. If there is ever a group that is absolutely meant for citizen science, it is birdwatchers, as I can testify to being sucked into the phenomenon and keeping lists of viewed birds over multiple trips to Africa. Wired also highlighted the possibility of citizen science to take off with the advent of GPS-enabled cell phones, a definite possibility I will hit on a bit later.

The concept of citizenry science balances results versus accuracy. While traditional science methodologies might shy away from such “untrained” data collectors for fear of inaccurate or biased data, the substantial payoff in results for relatively little resources is quite inviting. Indeed, citizen scientists are not likely to be paid, as they simply have an interest in the environment and are willing to volunteer their time to contribute to a data set that can eventually tally a great deal of data from a limited area or a rather large region, depending upon the project target.

The results are data. Plenty of it, and useful enough to draw real conclusions. As I was reading this, I began wondering about the applications of such methodology for the city. If one were attempting to create a more livable city, how would you go about it? You can invest in public transport, parks, mixed-use housing, roads, sidewalks, governance structures, whatever. There are lots of options open. How do you decide where to spend a metropolitan area’s precious dollars? Perhaps you can ask the citizenry.

Of course this already takes place through any number of forms. Elections, polls, town hall meetings, public hearings, surveys, etc. What if, however, you wanted to make a more empirical basis for improvement? This, too, takes place when a department of transportation conducts a traffic survey to find out how many vehicles zoom through an intersection during an hour. If there are too many, a new traffic pattern must be configured, or perhaps the road expanded. In times past, this would be done by a person or persons actually counting, or laying down a temporary traffic counter in a particular location (something you still see today). The cost trade off for the number of possible collection points, though, is too vast for a usual transportation department to continuously collect the information. In more modern iterations, electronic traffic counters are installed on main roads or toll booths and funneled through sites to provide live traffic reports, though side streets are often missed. While plenty such sites exist, data collection and analysis technologies are still under research in order to determine more efficient methods of doing this. Such research can be found in many pockets around the country, such as MIT or the Intelligent Transportation Society of America, but it seems from a quick scan that full data integration in most places has not yet come to fruition.

Data collection in cities is ever-increasing, sometimes to the chagrin of privacy advocates. The city of London is completely wired for surveillance. New York is looking to follow suit. Red-light traffic cameras catch law-breakers in Washington, D.C., especially the rich lawyers living in Maryland who blow through the District’s streets on the way home, making an unsafe city (or so the argument goes…). Public transportation signs in networks everywhere tell riders when the next train or street car is coming, allowing them to use the information to make a feedback decision as to whether to take this train or divert to the alternate route. Here in Vienna, every major subway and streetcar hub has one of these indicators, flashing when the next train is to come. The signs are usually fairly accurate too, and as things go, are not out of service all that much. Dan Hill at City of Sound had a fascinating post on this topic, referring to the burgeoning field as urban informatics.

So, could there be a citizen effort for data collection? Could a city (or perhaps a private entity) organize continual data collection at the individual level which aggregates up to provide a clearer picture of a segment of urban life? This empirical slice could then be applied to improve urban life, sustainability, and interaction.

Obviously this already takes place. UN-Habitat, the UN’s agency that promotes, among other things, the development of livable and equal cities worldwide, gathers data through its Urban Indicators project. Through its urban observatories, the program collects data on “essential services such as water; sanitation; shelter; sufficient living space and security of tenure,” compiling it for annual reports and larger studies. While a novel effort the amount of information it could collect is immense and perhaps the initial biases present in setting up the data collection patterns affects the outcomes.

In a more technological form, the concept of the digital city is well-established by research groups in the urban realm everywhere. Multiple projects attempt to incorporate IT and digital usage into urban life for business, government, design, or recreation. Indeed, one can approach the IT infrastructure of a city as another underlying element that influences urban growth much as other infrastructures have affected the development of the urban space in past revolutions, such as highways, public transport, waterways, or sewer systems. Some data collection is of course in the private sector, such as the consulting firm Urban Mapping, which collects urban data related to geolocation in order to assist businesses and other interested parties in targeting effective advertising. Still, we can continue to search for the examples of the regular citizen contributing to urban data collection.

Related to the earlier discussion on transportation, UC Berkeley is rolling software for its Mobile Millennium Project, which enlists volunteers around San Francisco to download software to their GPS-enabled mobile phones that can provide data to a central repository on traffic patterns and movements. Filling a gap in traffic monitoring related to side roads, the project hopes that with enough volunteers, it can assemble a data set of regular traffic patterns that can allow city planners to optimize traffic flow and make everyone happier.

Moving out of the car and onto the sidewalk, MIT’s SENSEable City Lab is looking at some immensely creative projects. Using technology to track Wi-fi enabled cell-phones, researchers at the lab have tracked movements of individuals through the campus, as well as cities such as Copenhagen, in order to provide composites of urban patterns. Wholly interesting stuff, but there are serious privacy ramifications included in being able to track individual movements in near-real time. The Lab’s approach is to act like the un-corporation, meaning that in aggregate, the data is fascinating and belongs to the greater body of understanding. It is certainly feasible to see how a corporation could use or even exploit the information it gathers through such a network. So, it is a good thing that Google’s commitment to not being Evil is strong, considering their free Wi-fi offering for Mountain View.

The above examples are based on an individual volunteering, in varying levels of compliance, to submit data on urban life, but relinquish the burden of actually submitting the data to technology itself. What about engaging citizens to participate more in the process, i.e. the concept of submitting bird lists. An interesting twist on this theme comes from the Common Sense research project. The research team, comprised (mostly) of UC Berkeley and Intel researchers, is exploring how to integrate sensors with mobile phones in order to provide real-team, ultra-localized environmental conditions such as pollution, humidity, temperature, and more. In this direction, citizens are consumers of information that provides feedback and potentially makes the urban space more livable. What about asking citizens to contribute information? Part of the project, of course, is data collection, as all of these mobile sensors provide a benefit to the user in terms of increased environmental awareness. Another important aspect, however, is the aggregation of data, creating a more detailed set of data complete with localized, micro-level sensor readings.

In more of a community-action context, community policing in Chicago, as highlighted by this article from the Boston College Environment Affairs Law Review, showed how citizen input can improve community safety and reduce crime. In this instance, however, individual data points were not aggregating upwards, but instead more conceptual, qualitative data was funneled through the Chicago Alternative Policing Strategy in order to develop strategies about improving safety. In the process, citizens contributed their knowledge to an overall understanding of the problem, and after becoming involved, continued through to implement citizen-police solutions. The strategies for fighting drug-dealing and loitering would have been much different had the collective wisdom of neighborhood citizens not reached the Chicago Police.

In any case, academics and researchers love to speculate about how greater amounts of data can lead to greater amounts of understanding and analysis. It should be noted that more data can simply lead to bad analysis based on more data, but the upside is quite intriguing for figuring out how to design a better urban space, route traffic through a side street, or assist a shop owner in determining when to open during the Spring season. More to come…

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