City Dashboards and benchmarking were developed to measure the performance of a city against best practice. The Dashboard displays data that can be statistically analysed and can be viewed as objective, factual and trustworthy. It allows those monitoring the data to gather important information at a glance as “indicators are viewed as vital sources of evidence … such as planning, environmental and social issues” (Kitchin et al, 2015. PG 09)
Information gathered is often used to govern how a city operates within its spaces. This monitoring falls into two categories self-securitisation of risk encountered in an environment and how a city orders and regulates itself. As the data gather revels patterns and trends within a city. Those using the data have the ability to compare areas whether by country regions or cities.
However, the validity of how the data is represented should be scrutinised when used as a comparisons. An example of this would be as part of a smart city initiative a navigational type app that gathers data to inform and the user around a city. The output of the information given could be bias dependent on the location of the city. Elements of the data have been used to marginalised sections of society and eventually cause tension. Leszczynski documented this as she discussed the use neighbourhood safety applications, which in many cases caused offence to areas in large cities, which these apps highlighted as avoidance areas due to crime rates and social deprivation.
When this information is packaged for general consumption it could also limit the option of the user for example when “Google Maps search for ‘restaurant’ in Tel Aviv conducted from the same location in Arabic and Hebrew … the results … Arab speakers directed to Arab sectors of the city; Hebrew speakers directed to Jewish quarters” (Leszczynski, 2016, PG 1695). The data gathered made assumption of user based on the language input that limited their options.
The overall use of dashboards to gather information and govern area within our society is a useful tool, which enables to user to digest data in a palatable format. However, there needs to be an air of caution when using this information on a commercial basis often the information communicated can view as bias
Bibliography
Citydashboard.org. (2017). CityDashboard: London. [online] Available at: http://citydashboard.org/london/ [Accessed 13 Mar. 2017].
Kitchin, R., Lauriault, T. and McArdle, G. (2015). Knowing and governing cities through urban indicators, city benchmarking and real-time dashboards. Regional Studies, Regional Science, 2(1), pp.6-28.
Leszczynski, A. (2016). Speculative futures: Cities, data, and governance beyond smart urbanism. Environment and Planning A, 48(9), pp.1691-1708.
The Google maps’ restaurant search suggesting different results for Arab and Hebrew speakers is a good example of what Bowker describes as data never being raw, but always already cooked. (Bowker, 2005 in Kitchin et al, 2015: 15). It is not a pure representation of the best or closest restaurant to the user, but rather uses assumptions based on the language they speak. This is not an accurate representation of the city of Tel Aviv and therefore, as with city dashboards and benchmarks, should not be assumed to be, as Kitchin explains, neutral, apolitical communication tools, but rather ideologically-loaded and engineered. (Kitchin et al, 2015: 20).
Bibliography:
Kitchin, R., Lauriault, T. and McArdle, G. (2015). Knowing and governing cities through urban indicators, city benchmarking and real-time dashboards. Regional Studies, Regional Science, 2(1). Pp.15-20.
Leszczynski, A. (2016). Speculative futures: Cities, data, and governance beyond smart urbanism. Environment and Planning A, 48(9), pp.1691-1708.
One of the aim of google maps is to direct the users (audiences) and provide them adequate information according to what they are looking for. As stated by Leszczynski, quoting Graham (2005), Software, in others words sort the city; bodies are positioned as belonging in or excluded from certain spaces (2016 pg 1695). She also states that those cities spaces are characterised by the presences of people (bodies) who frequently visit the area (2016: 1965). This therefore means the functioning of software depends on the bodies using them. When a search engine has to provide information for example, it will provide information according to some of the characteristics that are put in the search. In the case of Tel Aviv, Leszczynski stresses on how the different languages (Hebrew and Arabic).
Reference
Leszczynski, A. (2016). Speculative futures: Cities, data, and governance beyond smart urbanism. Environment and Planning A, 48(9), pp.1691-1708.