AN ONTOLOGICAL APPROACH TO CONSIDERING METADATA ACROSS SPATIAL AND NON-SPATIAL DATASETS
Abstract: This study presents the case for taking an ontological approach to metadata analysis as a means of facilitating enhanced interoperability across spatial and non-spatial datasets in GIS. A detailed literature review was undertaken in order to understand metadata definitions, concepts and usage, particularly as a “primary interoperability enabler” (Danko, 2008). Interoperability, within the context of this study, is understood as the ability to combine several types of datasets, specifically, demographic, health and spatial. The concept of ontology, which deals with the nature of being, is both presented and validated within the Theoretical Framework as a qualitative or descriptive approach to metadata analysis. A detailed case study of the Demographic and Health Surveys (DHS) Program portal was undertaken, covering the full scope of the DHS Survey Process, with the purpose of identifying two suitable candidate countries for comparison. A further evaluation of the actual metadata categories associated with both sets of datasets was then performed, in order to navigate the sub-levels of metadata layers, facilitating the closer investigation of interoperability capacities within and across both candidate countries. It was found that a flexible approach to an ontological framework involving three levels of application was effective. Furthermore, interoperability was found to operate within a single dataset, between specific related datasets and across the full range of dataset types. Through the consideration of appropriate metadata categories, both the context and meaning of such interoperability was better understood. Finally, applying an ontological approach, illustrates how the DHS’s specific taxonomies effectively encapsulate deeper contextual meaning which cannot normally be expressed semantically in metadata tagging and layering.
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