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Title:Spatial provenance: A case study on geological carbon sequestration
Author(s):Korose, Christopher P.
Advisor(s):Wang, Shaowen
Department / Program:Geography
Discipline:Geography
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):spatial provenance
spatial workflow
lineage
geological carbon sequestration
RDF
SPARQL
Geographic Information System (GIS)
Abstract:The collection, preservation, and accessibility of detailed lineage information derived from the handling of spatial data—spatial provenance—requires effective management of transformational workflows and associated metadata for workflow components. The spatial provenance model presented in this thesis captures important information for understanding spatial data lineage and related data transformation tasks that are chained together in operational workflows. This research has led to the development of an integrated solution for capturing and managing spatial provenance by interfacing with, and building upon, existing geographic information systems (GIS) software. The challenge of organizing, storing, and ultimately accessing spatial provenance information is tackled by exploiting semantic representations and database technologies to enable the comparison of alternative and/or historical iterations of spatial data processing workflows. Using a case study based on geological carbon sequestration research, this thesis examines source data revisions and updates to a spatial analysis over time. Experiments in tracking the spatial propagation of potential errors and comparing temporal attributes of alternative workflows of processing spatial data verify the effectiveness of the spatial provenance model and its implementation based on semantic representation and query. The case study and experiments serve as a proof-of-concept scenario to demonstrate the benefits of a provenance-enhanced spatial analytical workflow framework. This spatial provenance approach is built upon general components and principles of GIS software that can be scaled to handle massive data sets and support collaborative workflow tasks.
Issue Date:2011-01-14
URI:http://hdl.handle.net/2142/18245
Rights Information:Copyright 2010 Christopher P. Korose
Date Available in IDEALS:2011-01-14
Date Deposited:December 2


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