The KDD process for extracting useful knowledge from volumes of data
Communications of the ACM
Principles of data mining
dg.o '03 Proceedings of the 2003 annual national conference on Digital government research
Successfully adopting IT for social welfare program management
dg.o '04 Proceedings of the 2004 annual national conference on Digital government research
A dynamic website for county level child welfare outcome measures
dg.o '08 Proceedings of the 2008 international conference on Digital government research
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Self-evaluation is a form of empowerment evaluation that is collaborative and participatory. Through self-evaluation, a county social services agency, with the assistance of experts, can design, monitor, and improve indicators that ultimately improve the outcomes that are important in their local community. A key element to the self-evaluation efforts is the availability of timely and accurate data that appropriately measure the outcomes of interest. However, many of the local agencies lack the resources to collect and analyze the data for such evaluations. Furthermore, it would be easier to have consistency across similar outcomes in different local governments if the state provided the technical assistance for such efforts. In this paper, we discuss a successful case study in which the North Carolina Department of Health and Human Services (NC-DHHS) in partnership with the University of North Carolina at Chapel Hill School of Social Work (UNCCH) used Knowledge Discovery and Data mining (KDD) technology to effectively support these self-evaluation efforts at the local level in child welfare. We present the key elements of the KDD information system built on the child welfare program in North Carolina.