Abstract. Semantic integrity constraints specify relations between entity classes. These relations must hold to ensure that the data conforms to the semantics intended by the data model. For spatial data many semantic integrity constraints are based on spatial properties like topological or metric

Abstract. This paper introduces a formalization of a set of spatial semantic integrity constraints on an extended-relational database model. The formalization extends traditional notions of functional and inclusion dependencies by adding interaction with spatial attributes. This enables to specify

Global semantic integrity constraints ensure integrity and consistency of data spanning multiple databases. In this paper, we take initial steps towards representing global semantic integrity constraints for XML databases. We also provide a general framework for checking global semantic integrity

of reasoning techniques like the composition of spatial relations and constraint satisfaction in networks of relations to find conflicts and redundancies in sets of spatial semantic integrity constraints. These integrity rules specify relations among entity classes. Such relations must hold to ensure

As part of the quality description of a spatial data set logical consistency is very important to support interoperability between different systems. Logical consistency specifies “the degree of adherence to logical rules of data structure, attribution and relationships ” [1]. For the evaluation of logical consistency of spatial object related

to existing solutions our approach allows for the integration of ontologies to achieve interoperability and abstraction from implementation aspects of documents. This makes it specifically suitable for the integration of heterogenous and distributed information resources in the semantic web.

the database. Formal definitions of spatial data types were used in attempt to formulate novel equations and architectures to detect constraint violations and framework for spatial repository. A data structure called Semantic Spatial Outlier R-Tree (SSR O-Tree) was proposed for the Semantic Integrity

The provision of more intelligent support for complex database applications is becoming an important research topic, and declaratively stated integrity constraints are increasingly being seen as a potential source of semantic information for such advanced DBMS's. However, despite much research

are applied on such data. In this paper, a data quality mining technique is proposed to automatically generate Semantic Integrity Constraint Rules from the data. Further, this process leads to identification of Outliers, which are then to be classified as either violations or genuine cases of exception

for semantic integrity constraints that is very small with regard to the number of new language elements. The proposed language does not only obey the principles of object-orientation but additionally is inherently conform to the new structural concepts of object-oriented database systems. We proved