Semantic Summarization for Context Aware Manipulation of Data

Intelligent robots for planetary exploration produce a wealth of information – both science data collected by the robots and data about remote robotic operations. The management and analysis of this data provides unique opportunities as well as significant challenges for both science and rover operations, including understanding and summarizing what data have been collected and using this knowledge to improve data access. TRACLabs proposes to develop software for automatically building semantic summaries of data and images collected by remote rovers and using this information to retrieve subsets of this information for manipulation and visualization. We will use these semantic summaries to construct scripts for spatial and event-based data retrieval (e.g., retrieve data collected at a location). This ability to retrieve and manipulate a subset of data relevant to a situation of interest will be used to provide details on demand displays as well as support data exploration starting from a situation or event. Semantic interpretation has focused on document interpretation and database indexing while the proposed approach provides in-line semantic annotation and summarization of data streams. TRACLabs and its partner Carnegie Mellon University bring extensive experience in advanced software development and rover operations enabling integrated software solutions for NASA's planetary exploration.