Prototype Implementation of Web and Desktop Applications for ALMA Science Verification Data and the Lessons Learned

TL;DR

This paper presents the development of web and desktop applications for ALMA data analysis, highlighting techniques to reduce network traffic and lessons learned from implementation challenges.

Contribution

It introduces new GUI tools for ALMA data visualization and discusses effective data management strategies for handling TB-scale astronomical data.

Findings

Network traffic remains a bottleneck for large data distribution.

Pre-processed compressed FITS files aid in reducing network load.

Alternative data containers are needed for faster data processing.

Abstract

ALMA is estimated to generate TB scale data during only one observation; astronomers manage to identify which part of the data they are really interested in. Now we have been developing new GUI software for this purpose utilizing the VO interface: ALMA Web Quick Look System (ALMAWebQL) and ALMA Desktop Application (Vissage). The former is written in JavaScript and HTML5 generated from Java codes by Google Web Toolkit, and the latter is in pure Java. An essential point of our approach is how to reduce network traffic: we prepare, in advance, "compressed" FITS files of 2x2x1 (horizontal, vertical, and spectral directions, respectively) binning, 2x2x2 binning, 4x4x2 binning data, and so on. These files are hidden from users, and Web QL automatically choose proper one by each user operation. Through this work, we find that network traffic in our system is still a bottleneck towards TB scale data distribution. Hence we have to develop alternative data containers for much faster data processing. In this paper, I introduce our data analysis systems, and describe what we learned through the development.