Ultimately, GIS is merely a tool to be used in a variety of contexts, applicable to content appropriate to many different issues and as a resource for decision makers who use the tool as an adjunct to their work. GIS has been used to date primarily by persons who value maps more than data and applications. Community leadership and local organizations tend to view GIS as automated mapping rather than as a data organization resource. Information has been often limited in scale to levels at which information is broadly available - rarely to degrees of detail important to neighborhoods. The information generally available is derived from MIS systems or broadly general census surveys - quickly recognized by those addressing community problems as of limited value to the questions that they face.
For nearly four years, Milwaukee Associates in Urban Development, an association of 240 nonprofit organizations in Milwaukee Wisconsin, has operated a Neighborhood Data Center program. This program has become a comprehensive GIS service operation. Block, parcel and accurate address map bases have been created or adapted. Data sets from a wide variety of sources have been negotiated for, cleaned up and integrated with each other. More than 100 local, neighborhood based organizations have been served by short term products tailored to specific neighborhoods and to specific program content issues. Templates have been developed to streamline the creation of data tables and maps so that production efforts can become secondary to new applications.
The most important aspect of the Neighborhood Data Center program has been its development within an organization with a clear mission to support the "empowerment" of local organizations to expand their capacity to work with data. Community development objectives have been realized in a number of ways: A substantial series of educational sessions have been offered to identify the vision, to help organizations to identify needs and to interpret available material and to use more sophisticated tools. Focus groups within specific content areas - housing development, health care, services to the elderly, youth programs, block club development, crime prevention programs, and others - have informed priorities for data development and created a collaborative environment for further data acquisition and research. A "community fellows" program has provided up to 100 hours of training for selected community organization staff. A group purchase of a GIS program included training and support of 8 nonprofit organizations in ongoing use within their organization. Recent collaborative neighborhood planning initiatives have increased the demand for a broad range of information and for improved methods of communicating patterns to residents. A "fee for service" model required that the program aggressively market its services and demonstrate cost effective value to financially strapped nonprofit organizations. Collaborative projects have involved supporting the value added role of local organizations given the "starting point" provided by public data sets. (Some of these efforts have demonstrated only partial success to date.)
An important outcome of the experience of the Neighborhood Data Center program has been the opportunity to critique the potential and the limitations of existing public data systems as resources for neighborhood organizations. Rarely do existing data sets provide insights neighborhood leadership do not already understand. Frequently, data sets are considerably richer when reviewed, corrected and enhanced by neighborhood organizations. As data systems improve, the capacity of such systems of data to inform and shape models of change within neighborhoods increase. Political and practical barriers to achieving relevant data systems can be substantial. But Milwaukee has reached a point that enough good information is available to demonstrate the synergy of comprehensive data systems and the value of GIS techniques to manage this information.
There are implications of these systems for new levels of neighborhood research as well. Annual data on individual properties, housing sales, crime events and other data allow micro level analysis of neighborhood change that permit serious investigation of the sequence of events that contribute to neighborhood decline. In Milwaukee, the best of these data sets are available for 21 years.
Both neighborhood program planners and researchers working to reassess our understanding of community issues are able to articulate needs for information that should drive future efforts to expand public data systems. While it is easier to "demonstrate" the power of GIS by performing exercises which "fit" the data that is most available, it is important to ask the question - What data is needed? This can be embarrassing because future users of data often ask for data that is not available and may be very difficult to access.
Data needs are also informed by the paradigms that users bring to the table. Data frequently focuses upon deficiencies and problem indicators rather than addressing assets and achievements. Public data sources may be more effective at identifying the problems individuals face rather than the failures of institutions that are important elements in the problems communities identify. Private organization information is even more difficult to access and analyze. (A major home insurance redlining case in Milwaukee demonstrated what could be done with court leveraged access to such data.)
Community development models are often premised upon the assumption that neighborhood organizations and leadership should not merely have access to data services, but that they should gain the capacity to do data analysis themselves. Does this mean replacing the role of technical assistance professionals? Is the context for GIS as a data manipulation environment too complicated to trust to those with limited training, even as the basic interfaces become trivial? Are local organizations likely to develop an organizational culture that embraces serious investment in data analysis and decision support systems informed by data? It is likely that new models will call for greater levels of collaboration between professional organization with access to more complicated data sets and analysis tools and the local consumers of data who can also improve upon the content of data sets and contribute "stories" (case studies) that also provide insight into what is going on.
To the rest of the hype about the "Information
Highway" it is appropriate to add the potential of the
Internet as a vehicle for access to data and maps, distributed
processing, and greater collaboration among local institutions
and between organizations with similar agendas in different
communities. Our insights into more effective models for data
analysis will be more easily disseminated in this environment.