UAP Independent Study Team Final Report

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example). Therefore, the reports do not alone constitute data that can support a repeatable, reproducible analysis,
and the hypothesis that what was witnessed was a manifestation of known natural or technological phenomena
cannot be falsified.
Collecting New Data
The instrumental characteristics of the equipment that can potentially capture UAP data are important information
that should be available for researchers studying the observations. This is essential for a data- driven study of UAP.
These characteristics may include lab-measured (rather than field-reported) error rates of sensors that are routinely
used by both civilian and military aircraft; modeling of optical “ghosting” in the images due to scattering of solar
and lunar glints within the camera system; solar or bright star glints from oceans’ surfaces; and noise sources
intrinsic to the sensors themselves.
Multisensor platforms are important for providing a complete picture of a UAP event. An object’s motion should be
recorded, as well as its shape (imaging data), color (multispectra or hyperspectral data) and any sounds and other
characteristics. Crowd-sourced observations that are standardized can also offer important metadata information
that can be used to filter and classify events.
The panel sees an advantage to augmenting potential data collection efforts using modern crowd-sourcing
techniques, including open-source smartphone-based apps. Using open-source software is consistent with NASA’s
commitment to transparency. From multiple near-simultaneous observations with smartphones, imaging and sound
data could be collated, and metadata used to triangulate an object’s location and estimate its velocity and size.
Such a database could be developed through a partnership involving AARO, NASA, and commercial partners. The
collected data would need to meet the standards described above, so platform developers would need to focus on
constructing a data architecture that would support such collection. NASA can use its experience in citizen science
projects to help minimize data noise, systematic errors, and cognitive biases related to human observed events
(as opposed to sensors).
Once an anomalous signal is identified, new discovery infrastructure may be needed to characterize it in full. Collecting
additional data on a rapidly evolving phenomenon of interest has become a common practice in astrophysics,
but collection of what in astrophysics is referred to as “follow-up data” requires a high level of automation in the
collection, reduction, (real time) analysis of the discovery data, and robotization of follow-up facilities. While NASA
has historically paved the way for this mode of observing by developing and supporting the General Coordinates
Network (GCN) that enables rapid coordination of observations from ground and space assets, consideration of
developing such an infrastructure should follow after careful planning of the discovery data as outlined above as
such a plan is significantly resource-intensive. If systematic studies of these events continue to reveal anomalies,
then future studies may consider optimizing such a system of follow-up observations.
Data Curation and Integration
There is no standardized Federal system for making civilian UAP reports. While the DoD is establishing a systematic
mechanism for military UAP reports, current FAA guidelines instruct persons wanting to report UAP to contact local
law enforcement or a non-governmental organization such as the National UFO Reporting Center4. This results in
inhomogeneously collected, processed, and curated data.
Integrating NASA’s open, civilian dataset with DoD’s more focused, restricted information would take some effort.
Additionally, data integration opportunities exist with NOAA. Assets such as the NEXRAD Doppler radar network
(160 weather radars jointly operated by the FAA, U.S. Air Force, and National Weather Service) or the Geostationary
Operational Environmental Satellites may be very useful for distinguishing interesting objects from airborne (wind-
borne) clutter.
4 https://www.faa.gov/air_traffic/publications/atpubs/atc_html/chap9_section_8.html