| Full text | |
| Author(s): |
Lopes Siqueira, Thiago Luis
[1, 2]
;
de Aguiar Ciferri, Cristina Dutra
[3]
;
Times, Valeria Cesario
[4]
;
Ciferri, Ricardo Rodrigues
[2]
Total Authors: 4
|
| Affiliation: | [1] IFSP, Sci & Technol Sao Carlos, Sao Paulo Fed Inst Educ, BR-13565905 Sao Carlos, SP - Brazil
[2] Univ Fed Sao Carlos, UFSCar, Dept Comp Sci, BR-13565905 Sao Carlos, SP - Brazil
[3] Univ Sao Paulo Sao Carlos, Dept Comp Sci, USP, BR-13560970 Sao Carlos, SP - Brazil
[4] Univ Fed Pernambuco, Informat Ctr, UFPE, BR-50670901 Recife, PE - Brazil
Total Affiliations: 4
|
| Document type: | Journal article |
| Source: | GEOINFORMATICA; v. 18, n. 2, p. 313-356, APR 2014. |
| Web of Science Citations: | 2 |
| Abstract | |
Although many real world phenomena are vague and characterized by having uncertain location or vague shape, existing spatial data warehouse models do not support spatial vagueness and then cannot properly represent these phenomena. In this paper, we propose the VSCube conceptual model to represent and manipulate shape vagueness in spatial data warehouses, allowing the analysis of business scores related to vague spatial data, and therefore improving the decision-making process. Our VSCube conceptual model is based on the cube metaphor and supports geometric shapes and the corresponding membership values, thus providing more expressiveness to represent vague spatial data. We also define vague spatial aggregation functions (e.g. vague spatial union) and vague spatial predicates to enable vague SOLAP queries (e.g. intersection range queries). Finally, we introduce the concept of vague SOLAP and its operations (e.g. drill-down and roll-up). We demonstrate the applicability of our model by describing an application concerning pest control in agriculture and by discussing the reuse of existing models in the VSCube conceptual model. (AU) | |
| FAPESP's process: | 11/23904-7 - Processing of OLAP queries extended with image similarity predicates and spatial predicates over non-conventional data warehouses |
| Grantee: | Cristina Dutra de Aguiar |
| Support Opportunities: | Regular Research Grants |