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Data knowledge base for the ATLAS collaborationстатья Исследовательская статья Электронная публикация
- Авторы: Golosova M.V., Aulov V.A., Grigorieva M.A., Kaida A.Y.
- Сборник: 2267
- Год издания: 2018
- Место издания: CEUR Workshop Proceedings Aachen, Germany
- Первая страница: 486
- Последняя страница: 492
- Аннотация: ATLAS experiment at the CERN LHC is one of the most data-intensive modern scientific apparatus. To manage all the experimental and modelling data, multiple information systems were created during the experiment's lifetime (more than 25 years). Each such system addresses one or several tasks of data and workload management, as well as information lookup, using specific sets of metadata (data about data). Growing data volumes and the computing infrastructure complexity require from researchers more and more complicated integration of different bits of metadata from different systems using different conditions. A common problem is multi-system join queries, which are not easy to implement in a timely manner and, obviously, are less efficient than a query to a single system with integrated and pre-processed information would be. To address this issue, ajoint team of researchers and developers from Kurchatov Institute and Tomsk Polytechnic University has initiated the Data Knowledge Base (DKB) R&D project in 2016. This project is aimed at knowledge acquisition and metadata integration, providing fast response for a variety of complicated queries, such as finding articles based on same or similar data samples (search by links between objects), summary reports and monitoring tasks (aggregation queries), etc. In this paper we will discuss main features and applications of the DKB prototype implemented by now, its integration with the ATLAS Workflow Management, and future perspectives of the project. © 2018 Marina Golosova, Vasily Aulov, Maria Grigorieva, Anastasiia Kaida.
- Добавил в систему: Григорьева Мария Александровна