JavaScript ROOT

Several data samples from a Belle II experiment will be available to the public as a part of the experiment outreach activities. A Belle2Lab tool is designed as an interactive graphical user interface to reconstructed particles, offering users basic particle selection tools. The tool is based on a Blockly JavaScript graphical code generator and can be run in an HTML5 capable browser. It allows a description of different particle decays by selecting and combining particles from the data file, easy histogramming tools and a display of the results by using the JSROOT library. During the analysis, the user has the possibility to apply cuts to the selected variables. A pseudo-code generated by the user interface is sent to the execution server which returns the histograms, that can also be interactively fitted. The Belle2Lab is accessible in two ways: hosted on a single public web server or as a part of the virtual appliance which consists of an Ubuntu 16.04 LTS operating system, a data sample, an analysis framework, and a private web server. The public web server can be used for a single access while the virtual appliance is more suited for a use in a classroom. *

Section: Methodsmentioning

confidence: 99%

Belle2Lab - An Interactive Tool for a Public Analysis of the Belle II Data

Pestotnik

2019

“…But still they are just ROOT objects and cannot be displayed on the user's computers without ROOT framework installed. That is why the jsROOT [9] library is used which is capable of converting ROOT objects into html ones. This scheme works as follows: the js script inside the user's browser requests the ROOT object from the monitoring process, receives it and draws it using the jsROOT library, repeats this cycle instantly as the new events come.…”

Section: Frontendmentioning

confidence: 99%

Development of the BM@N Web Monitoring

Gabdrakhmanov

Merts

2020

The BM@N experiment is a fixed target experiment and the first stage of the NICA project. Its development is of great importance for the NICA experiment as a whole. In order to effectively conduct the experiment, a convenient and unified monitoring tool is needed. The monitoring system backend is based on the FairRoot package while its frontend uses the CERN jsROOT library. The user is able to monitor any detector subsystem, select specific detector station, plane, time or strip profile histograms in 1/2/3D view. The QA functions currently are presented by reference run auto-selecting and consequent overlaying histograms.

“…The web application back end is written in Python and is built with the Flask microframework [12]. The front end is built on top of Google's Polymer library [13] and JSRoot [14,15]. Within a selected run and subsystem, the data are displayed according to their previously classified groups, along with any information extracted from the displayed object.…”

Section: Alice Overwatchmentioning

confidence: 99%

Alice Overwatch: Online Monitoring and Data Quality Assurance Using Hlt Data

Ehlers

Mulligan

2019

ALICE Overwatch is a project started in late 2015 to provide augmented online monitoring and data quality assurance utilizing time-stamped QA histograms produced by the ALICE High Level Trigger. The system receives the data via ZeroMQ, stores it for later review, enriches it with detector specific functionality, and visualizes it via a web application. These provided capabilities are complementary to the existing Data Quality Monitoring system. In addition to basic visualization, additional processing options are accessible to the user, including requests for data within a particular time range or reprocessing of a particular run with different processing parameters. For example, the first ten minutes of a particular run could be investigated for a transient hot trigger channel. Due to similarities between the Overwatch architecture and that which will be used for Quality Control (QC) in LHC Run 3 and beyond, Overwatch will also be utilized to develop and test various QC components during LHC Run 2. Some of the areas of QC development include a new trending and alarm framework. We report on the project's design, development, and status.