A Dual-Database Trusted Broker System for Resolving, Protecting, and Utilizing Multi-Sourced Data

A Dual-Database Trusted Broker System for Resolving, Protecting, and Utilizing Multi-Sourced Data

Neal Gibson, Greg Holland
Copyright: © 2014 |Pages: 11
DOI: 10.4018/978-1-4666-4892-0.ch018
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A longitudinal database structure, which allows for the joining of data between disparate systems and government agencies, is outlined. While this approach is specific to government agencies, many of the ideas implemented are from the commercial world and have relevance to problems associated with data integration in all domains. The goal of the system is to allow for the sharing of data between agencies while upholding the strictest interpretations of rules and regulations protecting individual privacy and confidentiality. The ability to link records over time is central to such a system, so a knowledge-based approach to entity resolution is outlined along with how this system that integrates longitudinal data from multiple sources can still protect individual privacy and confidentiality. Central to this protection is that personally identifiable information should not be proliferated on multiple systems. The system, TrustEd, is a hybrid model that provides the simplicity of a centralized model with the privacy protection of a federated model.
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There has been a push in recent years for government agencies to share data, especially at the federal level. The impetus for this was 9/11. Subsequent hearings showed that a number of agencies were aware of and even actively monitoring some of the hijackers involved, but that the full scope of the danger remained somewhat hidden by the fact that data were not being shared between agencies (National Commission on Terrorist Attacks Upon the United States [9/11 Commission], 2004, p. 79). The response was to create an “Information Sharing Environment,” to facilitate the exchange and integration of data on matters dealing with national security (http://www.ise.gov/). The federal government has also encouraged state agencies to share data, by awarding funds through competitive grants for states to create longitudinal data systems through which such programs as Early Learning, K12 Education, Higher Education, and Workforce can be integrated into what are known as state P20W systems. The U.S. Department of Education and the U.S. Department of Workforce have provided significant grant monies to encourage states to integrate data from early childhood, elementary and secondary education, higher education, and workforce.

Two general models are being used by states to create these longitudinal systems that can track individuals from early learning programs, on to school and college, and their outcomes in the workforce (Garcia & L’Orange, 2012, p. 13). A centralized model is the simplest, where data is brought together in a central data warehouse. For the purposes of privacy, PII can be stripped from the data and a unique identifier used to link data together. A federated model allows agencies to retain the data within their institutions, and a system is put in place to allow for the querying of data across disparate systems.

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