ChiVOLabs: Cloud service that offers interactive environment for reprocessing astronomical data

摘要

The advancement of technology in telescopes and observation instruments has allowed more and more data to be available with higher resolution and quality, but the way to obtain this data is the same, astronomers are conditioned to obtain observation time. Once the data is public in most cases fall into disuse and except with initiatives such as the virtual observatory that seeks to offer this data over standards and protocols for storage and access, the data will not used again. Our proposal seeks to recover these large volumes of observations already made and offer them as a cloud service from a High Performance Computing (HPC) environment to be reprocessed by the scientific community with the aim of generating new science from them. This is why the Chilean Virtual Observatory (ChiVO) have created ChiVOLabs. a system with a microservice architecture on Docker that allow us. based on searches in our virtual observatory, to offer the possibility of reprocessing ALMA data through a Jupyter Notebook interface. The process starts using the IVOA protocol: Simple Cone Search (SCS) to find the astronomical data and then to select the option to reprocess them. The architecture creates a Docker environment with the entire analysis stack of ChiVO and Python in our datacenter. Furthermore, it transforms the reduction script used to generate the original product in a jupyter notebook automatically connected to our CASA (Common Astronomy Software Applications) cluster (Pipeline of reduction of ALMA). Finally, we search in our datalake raw ALMA data, known as ASDM. from which is generated the selected product and are created a link to these raw in the container. With this we offer to the scientific community the possibility of reprocessing these data according to their scientific interests and generating new data products that can finally be downloaded or continue to be working with our libraries using the full computing power of our datacenter.