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Title:
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A KDD PROCESS TO RETRIEVE AND AGGREGATE DATA FROM RELATIONAL DATABASES |
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Author(s):
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Jérôme Dantan, Yann Pollet, Salima Taibi |
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ISBN:
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978-972-8939-68-7 |
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Editors:
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Miguel Baptista Nunes, Pedro Isaías and Philip Powell |
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Year:
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2012 |
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Edition:
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Single |
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Keywords:
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Information extraction, Ontologies, Relational database, Semantics-based parametrization, Soil quality index, Structured Query Language |
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Type:
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Poster/Demonstration |
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First Page:
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443 |
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Last Page:
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445 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Relational databases are a standard for representing data models. SQL is the most widely used language for querying such databases. Consequently, in many research domains, scientists extract data from relational databases, compute them and do statistical treatments. But they have to deal with the complexity of relational databases models. In addition, it takes a long time for the scientists to manually retrieve and compute data. That's why we propose a system which automatically does. It contains the following layers: parameterizable extraction of data, automatic process of SQL queries, data aggregation, statistical parameters computation, writing the results to tables and final data processing by the scientist, thanks to statistical analysis software. A use case on the research on a soil quality index from a large relational database will be presented. |
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