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The increasing number, complexity, and variability of business rules in today's enterprises introduces the need for their effective and flexible management. In several research fields, such as the semantic web, library science, and data tailoring, effective organization of knowledge is enabled by contexts. We previously proposed a static structure model for context-based business rule management....
In order to unleash the full potential of System Wide Information Management (SWIM), the BEST project (Achieving the Benefits of SWIM by Making Smart Use of Semantic Technologies) proposes the semantic container approach which shields service and application developers from the complexities of data provisioning in Air Traffic Management (ATM). In combination with SWIM, semantic containers facilitate...
The design and implementation of analytical information systems requires both technical expertise and domain knowledge, the complexity of which often deters small and medium-sized enterprises from adopting business intelligence (BI) technology. Reference models for data analysis consist of domain-specific best-practice multidimensional models and greatly facilitate the development of analytical information...
An enterprise database contains a global, integrated, and consistent representation of a company’s data. Multi-level modeling facilitates the definition and maintenance of such an integrated conceptual data model in a dynamic environment of changing data requirements of diverse applications. Multi-level models transcend the traditional separation of class and object with clabjects as the central modeling...
Many real-world situations are more easily represented using multilevel models that abandon traditional two level instantiation. In business process management, multilevel modeling allows for the explicit representation of the interdependencies between the processes at the different hierarchy levels within an organization. Furthermore, multilevel modeling allows modelers to capture the variability...
Data warehouses combine data from various, often heterogeneous sources. The hetero-homogeneous approach to data warehouse modeling allows for the representation of heterogeneities while preserving the advantages of homogeneous models. A hetero-homogeneous model allows for the stepwise, controlled introduction of additional levels and measures for different sub-hierarchies and sub-cubes of an otherwise...
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