Jan 29 – 31, 2018
AGH Computer Science Building D-17
Europe/Zurich timezone

Session

User Voice: Novel Applications

Jan 29, 2018, 11:30 AM
AGH Computer Science Building D-17

AGH Computer Science Building D-17

AGH WIET, Department of Computer Science, Building D-17, Street Kawiory 21, Krakow

Description

Format: prime time presentations, 25 minutes + 10 minutes QA.

There is an increasing number of scientific-, engineering-, collaborative- and office applications closely integrated with CS3 services (cloud storage and file sync/share services). This session is designed for (power-)users of such novel applications to share their experience with synchronized-, online- and offline-storage: benefits and areas for improvement of CS3 services in their respective application domains. This session is an opportunity for service and technology providers to understand opportunities and new requirements but also shortcomings of existing CS3 implementations from the most important perspective: the one of the user.

Application domain examples:

  • Image collection, processing and analysis
  • Educational applications
  • Scientific notebooks for data processing
  • Collaboration and communication in teams
  • Decision support systems
  • Problem solving environments
  • Data curation and publication workflows

Presentation materials

There are no materials yet.
Mr Grzegorz Bogdał (AGH University of Science and Technology), Mr Piotr Gawryś (AGH University of Science and Technology), Mr Paweł Nowak (AGH University of Science and Technology), Mr Łukasz Plewnia (AGH University of Science and Technology), Leszek Grzanka (AGH University of Science and Technology (PL)), Maciej Malawski (AGH University of Science and Technology)
1/29/18, 11:30 AM
Presentation

Data analysis in High Energy Physics experiments requires processing of large amounts of data. As the main objective is to find interesting events from among those recorded by detectors, the typical operations involve data filtering by applying cuts and producing of histograms. The typical offline data analysis scenario for TOTEM experiment at LHC, CERN involves processing of 100s of ROOT...

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