Agriculture Spatiotemporal Business Intelligence using Open Data Integration

Abstract

Business Intelligence is a technology for collecting, transforming, and presenting data for analysis as a tool for supporting decision making. Business Intelligence using Data Warehouse, Multidimensional data, and Online Analytical Processing (OLAP) has proven to be useful for obtaining information and knowledge relevant to the business. Nowadays the development of the internet with Web 2.0 model is increasing the availability of data over the internet. Linked Open Data (LOD), Open Data, and Open Government Data is constantly growing, producing a large amount of valuable data in the form of semi-structured data, flexible and machine-readable. Data sharing on agricultural production is one of the requirements for the best of analysis of agricultural production, but most of the data is still in the format of 2/3-stars open data and does not yet have spatial data that facilitates analysis based on spatial dimensions. The emerging open data concept makes the data warehouse more dynamic and can accommodate external data. Spatiotemporal support in open data also enables a more sophisticated analysis of data with spatial queries. This research develops tools to integrate agricultural data originating from the Village and Rural Area Information Systems (SIDeKa) that has open distributed data, a service-oriented approach, and spatiotemporal data. This paper also describes the design of business intelligence and multidimensional data for analysis and decision-making tools that enable spatiotemporal and non-spatial based analysis. This paper also highlights the opportunities for scaling and sustaining the initiative.