Documents / Report
This white paper, sponsored by the All-domain Anomaly Resolution Office and hosted with Associated Universities, Inc. and Florida State University, synthesizes a workshop held August 5 and 6, 2025, that brought together 40 participants. The workshop examined how to collect, standardize, link and analyze UAP narrative reports. It calls for standard metadata templates, human oversight of AI tools, triage of reports, preservation of historical records, better public reporting portals and further workshops.
2 Executive Summary From both government and scientific perspectives, advancing Unidentified Anomalous Phenomena (UAP) research requires rigorous data collection, standardization, and analysis. Most UAP reports are fragmented, sparse, and unstructured, ranging from military logs and pilot reports to archival records, social media posts, and civilian testimony. Interpreting this heterogeneous data at scale is complicated by barriers of classification, translation, and retention. At the same time, UAP reports also present opportunities for novel methods of integration, metadata design, and analysis. The 2025 UAP Workshop on Narrative Data, Infrastructures, and Analysis brought together 40 participants from government, academia, and independent research organizations. The meeting focused specifically on the challenges and opportunities of working with UAP narrative reports and related data sources. Workshop discussions highlighted several cross-cutting findings. First, effective progress requires clear standards and common reporting templates, with robust metadata capturing time, location, provenance, morphology, and contextual details. Second, linking across datasets – military and civilian, to include archival, environmental, and technical - must balance interoperability with privacy, ethical, and classification constraints. Third, credibility is best assessed through corroboration, but for efficiency there is a need for automated methods to filter reports and surface the most promising for investigation. Fourth, AI and machine learning tools offer capacity for transcription, triage, clustering, and semantic search, but they must be deployed cautiously to avoid hallucination, bias, and amplification of hoaxes. Human oversight and iterative workflows remain essential. Finally, the workshop underscored the importance of community engagement and trust-building, encouraging the scientific community to cultivate a sustainable “community of practice” for UAP research with further work and convenings. This report concludes with recommended actionable next steps to establish metadata templates; combine human expertise with AI tools; leverage existing tools and infrastructures; support triage with awareness of bias; convene community members; facilitate qualitative integration in investigation, such as interviews; prioritize collection of new high-quality reports while integrating historical data; and improve reporting interfaces to enhance accessibility, collaboration, and transparency. Together, these findings and recommendations point toward a multi-disciplinary and community-engaged approach to UAP narrative data, which may influence how and where technical sensors are deployed.
Report, from the aaro collection. The PDF is mirrored here; the original link is above. 17 pages are in the text index: search them above, or from the library's search.