Research On Spatial Integrity Constraints Of Linked Data

In recent years,Linked Data has been introduced into the field of Geographic Information Science and has become a critical way of publishing and sharing geographic information on the Web.To standardize the representation of spatial information in Linked Data,the Open Geospatial Consortium has proposed the Geo SPARQL standard for describing geospatial Linked Data.However,currently,not all of these geospatial Linked Data published for spatial objects and spatial relationships contain complete information.The incompleteness of information is not conducive to the maintenance and management of data,as well as interaction among various datasets.At the same time,there may also be spatial semantic consistency problems,such as inconsistent topological relationships,in the published Linked Data.Therefore,in order to improve the quality of geospatial Linked Data,it is necessary to establish a spatial integrity constraint mechanism and a validation method for the integrity of Linked Data.Currently,SHACL is a language proposed by W3 C for describing the integrity constraints of Linked Data.SHACL not only provides a set of commonly used built-in constraint components,but also supports users to create custom constraint components with SHACL-SPARQL.Based on SHACL and SHACL-SPARQL,this paper proposes a set of spatial integrity constraints for Linked Data,and discusses their satisfiability and validation problem.The research work of this paper is as follows:Firstly,this paper extends the integrity constraints of spatial datatype property and spatial object property based on Geo SHACL.The extended spatial datatype property constraints can not only specify the spatial data domain,but also use spatial computation functions to verify the correctness of data.The extended spatial object property integrity constraints not only verify the correctness of topological relationships,but also restrict the spatial relationships between entities based on the feature of spatial entities.Secondly,for the extended spatial integrity constraints,this paper proposes a reliable satisfiability validation method.A set of transformation syntax is defined to translate spatial integrity constraints into description logic axioms,and then the Tableau algorithm is used to determine the satisfiability of axioms.For the spatial inconsistencies(i.e.,topological inconsistencies)that cannot be directly inferred and validated by logical reasoning,OWL property axioms and rules are used to check the path consistency of the topological relationships involved in the constraints.Satisfiability validation ensures that the constraints are not contradictory to each other.In addition,this paper proposes a validation method for the integrity of geospatial Linked Data.The validation problem of Linked Data is divided into non-recursive and recursive spatial integrity validation.For non-recursive spatial integrity validation,this paper explains the semantics of nonrecursive spatial integrity validation based on the semantics of Geo SPARQL query language.For recursive spatial integrity,whose constraints are with reference cycles,the shape assignment is used to provide a termination validation strategy for recursive constraints.Finally,to prove the effectiveness of the proposed spatial integrity constraints,four European city datasets from the SLIPO project were selected as experimental datasets,and a set of spatial integrity constraints were designed.The satisfiability of the spatial integrity constraints and the data integrity validation were evaluated separately.The results show that the proposed spatial integrity constraint mechanism and validation method can effectively detect spatial semantic inconsistencies and missing spatial information in Linked Data,and provide support for improving the quality of geospatial Linked Data.