Building a Relational Database to aid in the Automation of Photometry Pipeline

This research experience highlights the collaborative efforts between Dr. Kaloyan Penev, Angel Romero, Seyed Javad Jafarzadeh, and Micaela Landauro in the development of a photometry pipeline. The primary objective of the pipeline is to enable high-precision photometry using affordable color cameras while establishing a data processing framework for transforming citizen scientist observations into high-precision light curves.

The pipeline architectures (input data, processing products, and configurations) for this project are stored in a relational database. The basis of this research was to begin the automation of the database to keep track of all configurations used in the pipeline steps and to keep track of the intermediate images throughout the image’s journey through the pipeline.