We present SciServer, a science platform built and supported by the Institute for Data Intensive Engineering and Science at the Johns Hopkins University. SciServer builds upon and extends the SkyServer system of server-side tools that introduced the astronomical community to SQL (Structured Query Language) and has been serving the Sloan Digital Sky Survey catalog data to the public. SciServer uses a Docker/VM based architecture to provide interactive and batch mode server-side analysis with scripting languages like Python and R in various environments including Jupyter (notebooks), RStudio and command-line in addition to traditional SQL-based data analysis. Users have access to private file storage as well as personal SQL database space. A flexible resource access control system allows users to share their resources with collaborators, a feature that has also been very useful in classroom environments. All these services, wrapped in a layer of REST APIs, constitute a scalable collaborative data-driven science platform that is attractive to science disciplines beyond astronomy.
@article{arxiv.2001.08619,
title = {SciServer: a Science Platform for Astronomy and Beyond},
author = {Manuchehr Taghizadeh-Popp and Jai Won Kim and Gerard Lemson and Dmitry Medvedev and M. Jordan Raddick and Alexander S. Szalay and Aniruddha R. Thakar and Joseph Booker and Camy Chhetri and Laszlo Dobos and Michael Rippin},
journal= {arXiv preprint arXiv:2001.08619},
year = {2020}
}
Comments
Accepted for publication in the Astronomy and Computing journal