Principal Investigator Joseph Ferreira
Project Website http://uis.mit.edu/
As more and more information becomes available in increasing detail, it is evident that traditional data management and distribution techniques fail to provide an environment in which: a) large organizations can deliver tailored views of their databases to clients; and b) small organizations can afford to engage in data analysis efforts that thrive under real-world conditions, such as database updates, personnel turnover, and cross-agency collaboration.
The Intelligent Middleware project prototypes and tests an approach for sharing data within a metropolitan area in a manner that is likely to be more effective, scalable, and sustainable than the traditional ‘data center’ approach.
These tools and methods provide a mechanism for accumulating local knowledge about neighborhood-scale land use, ownership, and market potential and for using that knowledge to re-interpret administrative datasets and develop customized analyses of neighborhood conditions and market potential.
The proposed collaboration will prototype and test an intelligent middleware approach for sharing data within a metropolitan area in a manner that is likely to be more effective, scalable, and sustainable than the traditional ‘data center’ approach. The proposed tools and methods also provide a mechanism for accumulating local knowledge about neighborhood-scale land use, ownership, and market potential and for using that knowledge to re-interpret administrative datasets and develop customized analyses of neighborhood conditions and market potential. The collaborators include local and regional agencies with in-house GIS expertise and significant experience acting as ‘data centers’. These agencies are ready and willing to collaborate with MIT in the development and testing of data-intermediary approaches that can facilitate both horizontal data sharing across agencies and towns and vertical data sharing among regional, local, and neighborhood organizations. They have been working for several years with the Boston Foundation as local partners in the National Neighborhood Indicator Partnership and they are interested in methods that can enhance the reusability of administrative data and streamline its integration with locally generated neighborhood data, to permit customization of neighborhood indicators and analyses.
The project develops and tests prototype tools and methods for sharing and augmenting the data needed to understand neighborhood markets and community development options. University expertise is tapped to design next-generation tools for data sharing. University researchers, local and regional agencies, and community organizations collaborate closely in prototype development and in several workshop and class projects that test the practicality of the new methods. Advisory Board input and continued involvement in related national efforts provide useful input and several outreach and communication channels.
The project team has been extensively involved in efforts to improve the quality and utility of data sharing efforts that can inform community development and metropolitan planning. The team includes Boston’s NNIP partners and has been active in recent efforts to establish a nationwide Community Statistical System Network. A number of planners and community organizations across the country have expressed interest in finding alternatives to the traditional ‘data center’ model and are interested in implementing the middleware tools and methods developed by the project if the prototype proves effective.