Temporal aggregation on user-defined granularities

Time-varying data play a major role in many applications, and, starting from the 80's, they have been widely studied in temporal databases. In the last two decades, several researchers have shown that, to deal with many application domains, user-defined temporal granularities must be coped with. When data are stored at multiple user-defined temporal granularities, the task of defining proper conversion functions to aggregate data from an origin granularity (e.g., business days) to a task granularity (e.g., months) is of primary importance. However, current temporal database approaches mostly demand such a task to system administrators, or to specific applications, providing no methodology or general guideline to accomplish it. In this paper, we propose a general and application-independent methodology which, on the basis of the temporal relationship between two user-defined granularities, provides users with a set of conversion/aggregation functions between them, consistent with the telic vs. atelic character of the data to be aggregated. The correctness of the approach is also proved.