Statistical and scientific computing applications exhibit characteristics that are fundamentally different from classical database system application domains. The CROSS-DB data model presented in this paper is optimized for use in such applications by providing advanced data modelling methods and application-oriented query facilities, thus providing a framework for optimized data management procedures. CROSS-DB (which stands for Classification-oriented, Redundancy-based Optimization of Statistical and Scientific DataBases) is based on a multidimensional data view. The model differs from other approaches by o~ering two complementary rnechanisrnsfor structuring qualifying information, classification and feature description. Using these mechanisms results in a normalized, low-dimensional database schema which ensures both, modelling uniqueness and understandability while providing enhanced modelling flexibility.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:80623 |
| Date | 13 September 2022 |
| Creators | Lehner, Wolfgang, Ruf, Thomas, Teschke, Michael |
| Publisher | ACM |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/acceptedVersion, doc-type:conferenceObject, info:eu-repo/semantics/conferenceObject, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 978-0-89791-873-2, 10.1145/238355.238547 |
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