SciServer is a free science gateway that offers access to more than five Petabytes of data across multiple science domains, along with free online tools to analyze, share, and publish results. SciServer’s online services are entirely browser-based, with no software to install and configure, and are designed to be easy to learn and use. They include familiar user interface components for managing and sharing files, creating groups, and running computational analysis in Python, R, or Matlab by means of Jupyter Notebooks or RStudio.
The SciServer project grew out an existing system designed to support astronomy research, featuring several research and education tools that made access to hundreds of Terabytes of astronomical data easy and intuitive for researchers, students, and the public. One component of the previous system was Galaxy Zoo, a citizen science project that resulted in reliable classifications of hundreds of thousands of galaxy images, and led to more than 40 peer-reviewed scientific publications.
The current SciServer system has scaled out these tools for multi-science-domain support, applicable to any form of data. SciServer has been used in a variety of fields, from oceanography to mechanical engineering to social sciences and finance.
SciServer features a learning environment that is being used in K-12 and university education in a variety of contexts, both formal and informal. We have continued to develop the educational tools into a new component called Courseware which allows a classroom or course project to be defined giving teachers and students direct access to hosted scientific data sets. SciServer has sufficiently impressed some of our collaborators that three of them have taken the system and deployed it for themselves for use in varied environments. To facilitate this, over the past year we redeveloped the packaging and deployment model to support deployment in Kubernetes clusters. This work then led us to a new deployment of the system in the Amazon Cloud on their EKS platform. This latter installation is allowing us to experiment with the issues around data hosting and data transfer in a hybrid-cloud environment, and how best to support integration of user data between local and cloud hosted data sets.
SciServer is being developed by the Institute for Data-Intensive Engineering and Science (IDIES) at Johns Hopkins University, with funding from a five-year award from the National Science Foundation. Submitted:
