Show simple item record

dc.contributor.advisorHoeber, Orland
dc.contributor.authorEl Meseery, Maha Mohamed Nabil
dc.date.accessioned2016-07-27T19:53:47Z
dc.date.available2016-07-27T19:53:47Z
dc.date.issued2016-03
dc.identifier.urihttp://hdl.handle.net/10294/6856
dc.descriptionA Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Science in Computer Science, University of Regina. xi, 149 p.en_US
dc.description.abstractThe large number of environmental problems faced by society in recent years has driven researchers to collect and study massive amounts of environmental data. Such environmental datasets are often high dimensional and heterogeneous in nature, with complex temporal and geospatial relations. The ability to understand and extract meaningful information from such datasets is an essential step for effective decision making. However, reasoning about the data and discovering knowledge in environmental datasets is a challenging problem due to the complexity of the data. The goal of this research is to investigate techniques to support exploration and analysis of environmental data. Such complex data could be characterized as high dimensional heterogeneous geotemporal data. The research focused on the design, implementation, and study of approaches that facilitate the exploration and understanding of such data. A number of visualization approaches have been developed and studied to support the exploration and analysis among environmental datasets, including parallel coordinate plots, geovisualization, investigative scatterplot, and multiple coordinated views. The result of this work was the development of Geo-Coordinated Parallel Coordinates (GCPC), a geovisual analytics approach designed to support the exploration of complex environmental data. Multiple coordinated views are used to represent the high dimensional, heterogeneous, temporal, and geospatial aspects of the data. The approach uses various interactions and analysis features to support exploring and making sense of the data. Field trials were conducted to validate the benefit of the approach in the analysis of environmental data with experts. Environmental analysts used the system to explore within two real datasets in their domain. The results of the evaluation were very positive in general, which provided evidence of the advantages of using the system in exploration among the complex datasets. Domain experts were able to investigate the relations between multiple heterogeneous factors while remaining aware with the geospatial aspect of the data. However, the environmental analysts saw the system as a preliminary exploration tool rather than an analytical approach.en_US
dc.language.isoenen_US
dc.publisherFaculty of Graduate Studies and Research, University of Reginaen_US
dc.titleGeo-Coordinated Parallel Coordinates (GCPC): A Case Study of Environmental Data Analysisen_US
dc.typeThesisen
dc.description.authorstatusStudenten
dc.description.peerreviewyesen
thesis.degree.nameMaster of Science (MSc)en_US
thesis.degree.levelMaster'sen
thesis.degree.disciplineComputer Scienceen_US
thesis.degree.grantorUniversity of Reginaen
thesis.degree.departmentDepartment of Computer Scienceen_US
dc.contributor.committeememberYang, Xue-Dong
dc.contributor.committeememberMouhoub, Malek
dc.identifier.tcnumberTC-SRU-6856
dc.identifier.thesisurlhttp://ourspace.uregina.ca/bitstream/handle/10294/6856/El_Meseery_Maha_Mohamed_Nabil_200337155_MSC_CS_Spring2016.pdf


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record