An Interoperable Framework for Planetary Defense Data Integration and Visualization to Support the Mitigation of Potential Hazardous Asteroids



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A large asteroid impact can cause catastrophic environmental effects, as was shown by the Chicxulub impact some 66 million years ago (Pope et al. 1997). In order to protect our planet from future near-Earth objects (NEOs), it is crucial to efficiently and seamlessly integrate data, discoveries, and resources. However, planetary defense information remains scattered throughout multiple branches, organizations, and countries.The challenges that come with dispersed planetary defense information are manifold. First, the heterogeneity of planetary defense situations requires unique responses from various organizations. Second, there is a lack of structured integration, and interoperability among planetary defense stakeholders. This hampers effective communication and collaboration. Third, the diversity of data and information for planetary defense research creates discrepancy between PD data formats for individual researchers. Finally, future threats mitigation efforts are often hindered by a lack of comprehensive understanding of the problem. Consequently, an interoperable framework for planetary defense data integration and visualization is needed to support the mitigation of potentially hazardous asteroids. This dissertation has presented a data-fusion framework that can be used to support the detection, characterization, and mitigation of potentially hazardous asteroids. The data-fusion framework was used to develop the Planetary Defense Knowledge Gateway (PDKG), a platform that enables users to access, visualize, and analyze integrated, and interoperable planetary defense data. This dissertation also focused on multiprocessing techniques, comprehensive data modeling, and data inaccuracies verification. The implemented multiprocessing techniques provides three main advantages: (1) a data pre-fetching technique to minimize data retrieval latency, (2) an in-memory caching technique to improve data access performance, and (3) a query parallelization technique to speed up the execution of complex queries. The comprehensive data modeling considered the different types of information that needed to be integrated, such as observational data, catalog data, and expert knowledge. The data inaccuracies verification was performed using a set of heuristics that were designed to identify errors in the data. This research provides a foundation upon which the planetary defense community can build to mitigate the effects of dispersed information and aid in the overall decision-making strategies.



Data integration, Data visualization, Mitigation support tool, Planetary defense, Search engine