Dealing with multigranular spatio-temporal databases to manage psychiatric epidemiology data
| Autor: | G. Rambaldelli, Francesco Amaddeo, Carlo Combi, D. Salazzari, Alberto Belussi, Gabriele Pozzani |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
psychiatric case register
Information retrieval Exploit Computer science spatial granularity InformationSystems_DATABASEMANAGEMENT Spatial epidemiology spatiotemporal relationships Query language Semantics spatial relationships Temporal database Metadata ComputingMethodologies_PATTERNRECOGNITION Case register spatial epidemiology spatio-temporal granularity Psychiatric epidemiology |
| Zdroj: | CBMS |
| DOI: | 10.1109/cbms.2012.6266320 |
| Popis: | In epidemiology spatio-temporal data may represent surveillance data and origins of diseases. In order to better exploit these data, temporal and spatial dimensions could be managed considering them as meta-data useful to retrieve classical data. In this paper, we propose to use a framework for spatio-temporal granularities with the aim to improve the querying of clinical spatio-temporal data. We show how granularities can be used to enrich a psychiatric case register. We exemplify our approach reporting spatio-temporal queries, based on granularities, useful for epidemiological studies. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|