Unidentified flying objects (UFOs) have been of considerable interest throughout the world for over half a century, especially with the prospect that UFO Sightings defying worldly explanation would most likely be associated with highly advanced extraterrestrials (ETs), which, if confirmed, would undoubtedly have major implications on society. Yet, in order to confirm or deny this ET hypothesis, or a non-ET hypothesis involving a highly strange physical phenomenon, UFO Sighting data needs to be useful for scientific research. The usefulness of such data has been criticized by some scientists, such as Jacques Vallee, PhD, who has done prominent work on unidentified aerial phenomena and computer science. And this relates to the increasing prominence of “big data,” since various UFO Sighting databases exhibit the key characteristics of big data: high volume, variety, and velocity. The main purpose of this paper is to help make UFO Sighting data useful for scientific research through an approach that considers a layered data model by Jacques Vallee and Eric Davis in studying anomalous phenomenon, in conjunction with networked storage and analytical processes associated with big data. A background on UFO Sighting data is provided beforehand to foster an introductory understanding of the matter, along with cases of existing UFO Sighting data and its limitations. Recorded at the Society for Scientific Exploration Conference in Boulder, Colorado 2016.