A Multilayer Semantic Augmentation Model For Geographic Information Applications

dc.contributor.advisorKarabatis, George
dc.contributor.authorPillai, Manesh Ramachandran
dc.contributor.departmentInformation Systems
dc.contributor.programInformation Systems
dc.date.accessioned2022-09-29T15:38:11Z
dc.date.available2022-09-29T15:38:11Z
dc.date.issued2022-01-01
dc.description.abstractCurrent mainstream geographic information systems and maps in general depend on the user’s ability to derive meaning from the multi-layered nature of those maps. A complete answer to the question "what is relevant to my location of interest” should consider the user’s context and include records from multiple Geographical Information System (GIS) layers. The problem this research attempts to solve is the inability of organizations to query geospatial data in a way that conforms with the multi-layered nature of GIS data as well as the topological relationships that can exist between the GIS layers containing those geospatial objects. This dissertations extends the theory behind graphs (or networks) of objects with research into multilayer and semantic link networks to create a formal mathematical model of geographic objects and take advantage of relationships that exist among nodes within a single layer and across multiple layers. This includes the creation of a geospatial ontology that mathematically represents the relationships between different classes of geographic objects. The algorithms in this dissertations take traditional GIS queries and expand them using semantic reasoning and topological rules to include additional geographic objects that are relevant to the user, introducing the concept of a multi-layer Semantically Linked Network (mSLN). This research elevates traditional GIS operations into a common mathematical model to simplify the needs of an organization. This mathematical model has been proven to be correct and a framework based on the model has been designed to be easily implemented by organizations that utilize GIS systems. A prototype system, SAM-GIS has been developed and an empirical evaluation of this framework has been conducted using several real-life case studies relevant to local communities based on data from an actual local government population, along with a performance evaluation of the entire system. Results show that SAM-GIS providesexpanded GIS search results with increased accuracy, precision and recall over those of traditional GIS systems.
dc.formatapplication:pdf
dc.genredissertations
dc.identifierdoi:10.13016/m2xhrr-jgti
dc.identifier.other12554
dc.identifier.urihttp://hdl.handle.net/11603/26015
dc.languageen
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Information Systems Department Collection
dc.relation.ispartofUMBC Theses and Dissertations Collection
dc.relation.ispartofUMBC Graduate School Collection
dc.relation.ispartofUMBC Student Collection
dc.rightsThis item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please see http://aok.lib.umbc.edu/specoll/repro.php or contact Special Collections at speccoll(at)umbc.edu
dc.sourceOriginal File Name: Pillai_umbc_0434D_12554.pdf
dc.subjectGeographic Information Systems
dc.subjectMultilayer Networks
dc.subjectSemantic Link Networks
dc.subjectSemantics
dc.titleA Multilayer Semantic Augmentation Model For Geographic Information Applications
dc.typeText
dcterms.accessRightsDistribution Rights granted to UMBC by the author.
dcterms.accessRightsAccess limited to the UMBC community. Item may possibly be obtained via Interlibrary Loan thorugh a local library, pending author/copyright holder's permission.

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