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Modelling dataspace entity association using set theorems

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dc.creatorShibwabo, Bernard Kasamani
dc.creatorAteya, Ismail Lukandu
dc.creatorWanyembi , Gregory
dc.date01/09/2013
dc.dateWed, 9 Jan 2013
dc.dateWed, 9 Jan 2013 10:47:59
dc.dateTue, 15 Jan 2013 10:15:58
dc.date.accessioned2015-03-18T11:28:46Z
dc.date.available2015-03-18T11:28:46Z
dc.descriptionResearch Paper
dc.descriptionThe 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.
dc.description.abstractThe 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.
dc.description.abstractThe 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.
dc.formatNumber of Pages:7p.
dc.identifier.urihttp://hdl.handle.net/11071/3397
dc.languageeng
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dc.subjectDataspaces
dc.subjectentity collaboration
dc.subjectintegration
dc.subjectgeo data
dc.subjectdata management.
dc.titleModelling dataspace entity association using set theorems
dc.typeArticle
dspace.entity.typePublication
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