Modelling dataspace entity association using set theorems

Abstract

The development of dataspace support systems is far from reality as individuals and enterprises are faced with the huge challenge of data management. Critical to this is the need to provide a model that represents the relationships between the entities collaborating in a dataspace. A dataspace is a new abstraction and target architecture to data management that does not require up-front semantic data integration. This paper models a dataspace using the set theory with entity mappings. A technique for identity resolution and pay-as-you-go data integration is explained. In order to provide a strong degree of assurance, the authors subject the model to certain real world entities that might form part of a global dataspace.

The development of dataspace support systems is far from reality as individuals and enterprises are faced with the huge challenge of data management. Critical to this is the need to provide a model that represents the relationships between the entities collaborating in a dataspace. A dataspace is a new abstraction and target architecture to data management that does not require up-front semantic data integration. This paper models a dataspace using the set theory with entity mappings. A technique for identity resolution and pay-as-you-go data integration is explained. In order to provide a strong degree of assurance, the authors subject the model to certain real world entities that might form part of a global dataspace.