Module 4 - eGovernment Example

City of Madison, Wisconsin: Neighborhood Indicators Project

http://madison.apl.wisc.edu/index.php

Overview

The City of Madison’s Neighborhood Indicators Project is an attempt to disseminate data about the quality of life in the city and its various neighborhoods via the Internet. The data available on the project website includes general demographic information as well as 32 variables designed to measure quality of life or lack of quality of life. These indicators include voter turnout, property foreclosures, number of particular types of crime, families in poverty, transit availability, kindergarten readiness of children, access to basic goods and services, and pavement condition. Data is viewable for the city as a whole, by planning district and by individual neighborhood. Data sources include city and county government departments, the Madison Metropolitan School District, private data companies and the Madison Area Metropolitan Planning Organization. Currently the website includes data from 2008, 2009 and 2010.

Using the interface on the site, users can:

·      View values for the entire variable list for a neighborhood or planning district by year;

·      Compare up to three of these lists at a time;

·      Create time series graphs showing how a particular variable has changed from 2008-2010 in up to three separate neighborhoods/districts within the same graph; and

·      Map a variable to see how it varied across the city by either neighborhood or planning district in a given year.

When possible, the data is also normalized (for example by providing a percentage or per capita amount) to allow for comparisons between neighborhoods and planning districts. Users cannot view multiple variables in more than three neighborhoods or districts at time, nor can they combine variables in novel ways. Raw data is also not accessible via the website.

Project Goals and Intent

Wohlers (2007) states that some of the main objectives of e-government initiatives are to “increase government efficiency, effectiveness, and transparency and (to) improve citizen-government interactions” (p. 3). The Neighborhood Indicators Project addresses all of these aims to some extent. The project’s website states that the goals of the project are to help city government, citizen committees and the general public to better understand the city’s neighborhoods, to shape solutions to problems based on specific neighborhood characteristics, to identify emergent trends and problems at an early stage when they can potentially be addressed more effectively, and to allocate the city’s public resources more efficiently. As such, the project seems to fall squarely in the category of e-government initiatives designed to increase efficiency and effectiveness. By providing this data to the public, however, the project may also be increasing transparency while also providing opportunities and motivations for civic engagement among city residents.

The intended targets of the project are government employees and citizens. As such, in terms of intent, the project is a hybrid between a site like apps.gov, aimed at helping government employees work more effectively, a site like data.gov, designed to provide government data to a wider audience, and a site like challenge.gov, designed to get more people involved in solving public problems. It is, however, a much less interactive and less comprehensive initiative than any of these federal government sites, as one might expect from a relatively small municipality (population approximately 98,000). In terms of content, the project is most similar to data.gov but, as discussed below, the two sites differ in many ways.

What the Neighborhood Indicators Project Does Well

Bertot and Jaeger (2008) argue that an e-government service “that is difficult to use is a service that is not used” (p. 153). The Neighborhood Indicators Project appears to avoid this pitfall. The website has a very simple interface, with a fixed navigation bar allowing one to move easily between different pages of the site without having to use the browser’s “back” button. The method for choosing data to view is also simple, consisting of dropdown menus for choosing the neighborhood/planning district, variable and year. Mapped variables appear on a common Google map interface with a legend clearly explaining the range of values for each color contained on the map, and check boxes allow the addition or subtraction of details such as neighborhood and district boundaries and names.

Compared with an interface such as that found in the interactive datasets on data.gov, this interface clearly has a much smaller learning curve. Most users should be able to intuit the interface fairly easily. For those less technically inclined, the site also includes PDF documents that summarize the variables for the entire city and for each neighborhood and planning district. Detailed help for using the interface is not available as a page on the site but is available for download in PDF format.

Bertot and Jaeger (2008) also argue that governments should assess the needs and desires of citizens before designing e-government programs, and that assessment of the program’s usefulness, functionality and how users actually utilize the service must occur during and after the design process. The Neighborhood Indicators Project appears to be following these recommendations. The website states that the public, elected officials, city department managers, commission members, school district representatives and other stakeholders were heavily involved during the year-long process of designing the program. The site also offers several ways for users to offer feedback on the project, including an online form, an email address and a phone number.

The project also appears to trying to protect privacy of city residents. Raw data is not available on the site, making it difficult to trace most of the information back to an individual resident. Moreover, in cases where a characteristic could be tied to specific individuals (say, for example, when almost everyone in a neighborhood has a certain characteristic), the project withholds the data. Clearly the project takes privacy protections to a different level than a site like data.gov (which offers more than 3500 raw datasets), but these extra precautions are likely necessitated by the small size of the city. As Anderson (2009) argues, however, even supposedly anonymous data such as that contained in the raw datasets on data.gov is traceable to individuals by a savvy investigator. As such, the Neighborhood Indicators Project may be doing a better job of protecting privacy than data.gov by not releasing raw data.

Finally, the project is making previously unavailable or difficult to access information available to anyone with a computer. In doing so, it may be increasing transparency and civic engagement, as well as making government service provision more efficient and effective. In this sense, the site has a similar mission to data.gov, albeit on a much smaller scale. The project is also more targeted than data.gov, since the data being provided is particular to neighborhood quality, whereas data.gov contains a broad range of government data. In this sense, the project may be less about providing transparency and more about providing a particular service to government employees and citizens.

How the Neighborhood Indicators Project Could Improve

While the simplicity of the Neighborhood Indicators Project interface ensures accessibility to a large number of users, it also prohibits more advanced or technologically savvy users from customizing or combining the data in new and innovative ways that meet their particular needs or interests. This simplicity, combined with a lack of interactivity, makes the site less like e-government exemplars like data.gov and We the People, and more akin to the “traditional bureaucratic paradigm” where “local government websites are mostly informative and limited to providing a range of basic one-way services” (Wohlers, 2007, p. 4).

In order to balance the interests of basic and advanced users, the project may consider adding a second interface for advanced users that allows more customization and experimentation. Doing so would not only accommodate a broader range of users, it could also make the service more of an interactive, two-way experience, where users can help drive the development of the site. Adding in some interactivity to the interface – such as the “discuss” option found on data.gov – could also provide the project with a new source of feedback while also fostering a sense of community among users that could potentially spur innovative analyses and solutions to problems.

As previously discussed, Bertot and Jaeger (2008) argue that governments should assess the needs and desires of citizens before designing e-government programs, and that assessment of the program’s usefulness and functionality must continue after implementation. While the city appears to have conducted such an assessment, it is possible that the project could still be stymying some users. For example, the small amount of variables and the lack of raw data contained in the project database may limit some users’ capacity to conduct detailed analyses, and lack of access to raw data may further limit these types of users. As previously discussed, the project may not be able to make the raw data available while also protecting privacy due to the small size of the city. Moreover, unlike the federal government, which collects mountains of data, most city governments do not have the capacity or even the need to collect large amounts of data. Such data is also not necessarily geocoded (i.e. able to be attributed to an address or other physical place), and adding this feature to the data requires forethought, time and money. Thus, it may be difficult for the City of Madison to completely erase the tension between providing ease of use and allowing more advanced users to find usefulness in the site.

Still, the addition of other city government data to the site could make it more valuable, especially in the eyes of residents who may be interested in discovering how the provision of city services might be related to other quality of life measures in a neighborhood. Neighborhood specific data on city services, such as average police and fire response times, park and recreation, public works, economic development and CDBG dollars spent, and number of building permits issued and permit inspections carried out, could, therefore, provide more transparency and accountability while also allowing residents a better understanding of how their neighborhoods benefit (or don’t benefit) from these services. The addition of data on expenditures by area could also help users better achieve the project’s goal of allocating the city’s funds more efficiently.

References

Anderson, N. (2009). “Anonymized” data really isn’t – and here’s why not. Ars Technica. Retrieved from http://arstechnica.com/tech-policy/news/2009/09/your-secrets-live-online-in-databases-of-ruin.ars

Bertot, J. C., & Jaeger, P. T. (2008). The e-government paradox: Better customer service doesn’t necessarily cost less. Government Information Quarterly, 25, 149-154.

Wohlers, T. E. (2007). Comparative e-government: Trends and sophistication at the grass roots. Paper prepared for the Midwest Political Science Association Annual Conference, Chicago, IL, April 12-15, 2007.