Artificial Intelligence and Natural Language Processing in Space: A Methodological Framework and Four Case Studies at the European Space Agency 

Summary

The amount and depth of the knowledge produced throughout the different space missions and their contribution to scientific progress is enormous, involving large collections of documents like scientific publications, feasibility studies, technical reports, and quality management procedures, among many others. Handling such wealth of information, of which large part is unstructured text, is a colossal task that goes beyond human capabilities, hence requiring automation. In this seminar, we present a methodological framework based on artificial intelligence and natural language processing and understanding to automatically leverage the information contained in space documents and illustrate such framework through several case studies implemented across different functional areas of the European Space Agency, including Mission Design, Quality Assurance, Long-Term Data Preservation, and the Open Space Innovation Platform. In doing so, we demonstrate the value of these technologies in several tasks ranging from determining how innovative an idea can be, answering questions about space, and generating quality procedure questionnaires. Each of these accomplishments represents a step forward in the application of AI in space, from structuring and facilitating information access to automatically understanding and reasoning with such information.