MODELING AND QUERYING SPATIOTEMPORAL MULTIDIMENSIONAL DATA ON SEMANTIC WEB: A SURVEY

摘要

The usage of ?web of data? for decision making has increased with the presence of On-Line Analytical Processing (OLAP), Data Warehouse (DW), Multidimensional Data (MD), and Semantic Web (SW) technologies. These technologies are converging into technology that utilizes data on the web to obtain important information as the basis of crucial decision making. The implementation of these technologies continues to grow along with data published on the web using vocabularies like SDMX, QB, and QB4OLAP for linked cube data. Along with increasing analysis complexity, spatiotemporal OLAP emerges as a tool to obtain sophisticated, better, and more intuitive analysis results than OLAP. Vocabulary for spatial OLAP on the Semantic Web has been constructed, namely QB4SOLAP, and successfully implemented. Query language extension for SW was built significantly, but the fundamental model of more dynamic spatial (spatiotemporal) multidimensional data for OLAP on the SW still lacks to exhibit and implemented, even Spatiotemporal DW has been widely studied. This paper presents state-of-the-art research results and outlines future research challenges in Spatiotemporal multidimensional data on the semantic web. This paper organized into three parts, the first part (1) discusses the convergence of OLAP / DW and SW, the second part (2) discusses DW, and spatiotemporal DW on the SW based on the model and the query, and (3) discusses future research opportunities.