Thesis and Dissertation Workshop (WTDBD)
Data Warehouse, Data Warehouse Geográfico, Dados Espaciais Vagos, Tipo Abstrato de Dados
A data warehouse is a solution for organizing and storing multidimensional data related to decision-making processes in companies, generating a historical, highly voluminous, subject-oriented and non-volatile database. A geographic data warehouse (GDW) stores spatial data (represented by crisp geometries) as attributes in dimension tables or as measures in fact tables. Thus, spatial data have exact location in the space and well-defined boundaries. However, modern geographic applications require the storage of vague spatial data, which have inaccurate location or uncertain boundaries. This master's project aims at incorporating vague spatial data to GDWs. More specifically, we address the implementation of a new abstract data type (ADT) called VagueGeometry to represent vague spatial data in the Spatial Database Management System PostgreSQL with the PostGIS extension. The proposal of the ADT VagueGeometry encompasses the issue of physical storage and the management of vague spatial data over GDW. Although there are few studies in the literature that implement vague spatial data, these studies have several limitations, for instance, the related work produces low performance in processing analytical queries with vague spatial predicates. This master's project, therefore, aims to investigate this gap in the literature of GDW related to the management of vague spatial data.
Anderson Chaves Carniel, Ricardo Rodrigues Ciferri