A Negotiation Agent for Distributed Heterogeneous Statistical Databases Sally I. McClean, Rónán Páircéir, Bryan W. Scotney, and Kieran Greer   View Paper (PDF)   Return to Statistics Abstract The World-Wide Web provides an ever-increasing source of diverse information. We focus on query agents, in particular the matching and negotiation agents that are responsible for pre-integration where the matching agent decomposes the query into sub-queries, and then searches metadata to find datasets that match the query fragments. In the case of heterogeneous data, the matching agent utilises a negotiation agent to find datasets that match the query fragments, provides mappings from the data to the query, and constructs the appropriate (sub-)query re-writing rules. Such matching is done by generalising the data and testing if the (sub) query is matchable to the generalised (meta) data: we call this g-matchable; if it is then we can construct an operator stack to transform the data to match the (sub) query. Such an approach provides a capability of automating the process of executing queries on heterogeneous statistical databases that are distributed over the Internet. The novelty lies in the provision of automated methods for statistical aggregates, where the heterogeneity essentially resides in the classification schemes of categorical data, including both heterogeneity of nomenclature and heterogeneity of granularity. In addition, our solution permits queries to be specified in a goal-driven query-by-example format. Rather than impose an a priori global standard, the user can query through a unified interface where integration is done at run-time. DiSC'03 © 2003 Association for Computing Machinery