2011

  • Levon Vanyan
  • Arthur Reymers
  • Armen Hovhannisyan
25.01.2011
  • Levon Vanyan
  • Karen Arakelyan
  • Armen Hovhannisyan
  • Anush Hakobyan 
  • Levon Vanyan



Seminar at CRD Monday, February 28, 16:00

Advanced Data Extraction Infrastructure (ADEI): Status report and future development

  Suren Chilingaryan
  Karlsruhe Institute of Technology


ADEI is a web interface developed to facilitate user-friendly access to huge databases recorded by long-running experiments in cosmic ray and high energy physics fields. In order to provide fast interactive access the data is aggregated over time slices of few predefined lengths. The aggregated values are stored in the temporary caching database and, then, are used to create generalizing data plots. These plots may include indication of data quality and are generated within few hundreds of milliseconds even if very high data rates are involved. The extensible export subsystem provides data in multiple formats including CSV, Excel, ROOT, and TDMS. The search engine can be used to find periods of time where the stored values are falling into the specified ranges. Utilization of caching database allows performing most of such lookups within a second.

The future development of ADEI project is closely related with the current developments in web technologies. Using new features of HTML5 it is possible to move all data processing and chart rendering to the client side. The data first will be transferred to the client PC and stored in the Web SQL database. Then,the user can select one of the available visualization algorithms to analyze the data.

Multi-dimensional data can be visualized in 3D using WebGL and video  play-back can be used to enhance presentation of dynamic processes. The analysis part will be based on user-supplied scripts processing the chunks of data in the local web database. Using technologies like Google Native Client, it is possible to develop sophisticated data mining and analysis applications running in the browser at full speed. Having the data already on client side, the algorithms from analysis toolkits like ROOT and ANI can be used to extract and present user-desired information in a custom way.

Following this approach and using the client-resources it will possible to serve a big scientific community world-wide at a good speed and without need of large-scale computer facilities at the home lab.