Highly scalable and efficient data warehousing and mining methods are needed to handle the large amounts of sensor data collected due to advances in sensor, wireless and computer technologies. This sensor data has complex features and may be multi-modal, time stamped, geospatially referenced, from multiple sources, in different formats, and associated with semantic tags. A solid but extendable architecture is required to store data for integrated exploitation and analysis, for fast information access in bandwidth disadvantaged and distributed environments, and for developing efficient and effective information and knowledge querying services. To address this, IAI has been awarded a follow-on contract entitled, “A Distributed and Standard Based Data Warehouse and Mining System for Large-Scale Sensor Data.” This system, called SensorCube, can handle large amounts of geospatial sensor data and consists of three layers: data integration, data cubing and mining, and semantic search. To achieve scalability, all three layers have distributed server architecture and software agent technology. The data integration layer, which enables real-time monitoring and incorporation of sensor data, has an XML driven ETL (Extraction, Transformation, and Loading) process to integrate complex sensor data. The data cubing and mining layer has a powerful distributed computational engine to model multi-dimensional sensor data. In the semantic search layer, the search and query capability connects the meta data and information summarized in data cubes and mining models. Furthermore, the semantic search and cubing visualization can be accessed across different computational platforms such as smart phones and tablets. Open source tools are applied to the three layers to achieve flexibility in customizing and extending the software.