Where appropriate repositories are not available to support all relevant astronomical data products, data can fall into darkness: unseen and unavailable for future reference and re-use. Some data in this category are legacy or old data, but newer datasets are also often uncurated and could remain dark. This paper provides a description of the design motivation and development of Astrolabe, a cy...

This work explores the use of big data technologies deployed in the cloud for processing of astronomical data. We have applied Hadoop and Spark to the task of co-adding astronomical images. We compared the overhead and execution time of these frameworks. We conclude that performance of both frameworks is generally on par. The Spark API is more flexible, which allows one to easily construct astr...

Survey telescopes such as the Vera C. Rubin Observatory and Square Kilometre Array will discover billions of static dynamic astronomical sources. Properly mined, these enormous datasets likely be wellsprings rare or unknown astrophysical phenomena. The challenge is that are so large most data never seen by human eyes; currently robust instrument we have to detect relevant anomalies. Machine lea...