Evaluating non-relational storage technology for HEP metadata and meta-data catalog; Journal of Physics: Conference Series; Vol. 762, iss. 1 : Advanced Computing and Analysis Techniques in Physics Research (ACAT2016)
| Parent link: | Journal of Physics: Conference Series Vol. 762, iss. 1 : Advanced Computing and Analysis Techniques in Physics Research (ACAT2016).— 2016.— [012017, 5 p.] |
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| Autor Corporativo: | |
| Outros autores: | , , , , , |
| Summary: | Title screen For the purpose of testing and the search for new drug compounds, designed to heal many human diseases, it is necessary to investigate the deformation of experimental tissue samples under influence of these drugs. For this task a precision force sensor for measuring the mechanical tension, produced by isolated ring segments of blood vessels and airways was created. The hardware and software systems for the study of changes in contractile responses of the airway smooth muscles and blood vessels of experimental animals was developed.Large-scale scientific experiments produce vast volumes of data. These data are stored, processed and analyzed in a distributed computing environment. The life cycle of experiment is managed by specialized software like Distributed Data Management and Workload Management Systems. In order to be interpreted and mined, experimental data must be accompanied by auxiliary metadata, which are recorded at each data processing step. Metadata describes scientific data and represent scientific objects or results of scientific experiments, allowing them to be shared by various applications, to be recorded in databases or published via Web. Processing and analysis of constantly growing volume of auxiliary metadata is a challenging task, not simpler than the management and processing of experimental data itself. Furthermore, metadata sources are often loosely coupled and potentially may lead to an end-user inconsistency in combined information queries. To aggregate and synthesize a range of primary metadata sources, and enhance them with flexible schema-less addition of aggregated data, we are developing the Data Knowledge Base architecture serving as the intelligence behind GUIs and APIs. |
| Idioma: | inglés |
| Publicado: |
2016
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| Subjects: | |
| Acceso en liña: | http://dx.doi.org/10.1088/1742-6596/762/1/012017 |
| Formato: | Electrónico Capítulo de libro |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=654300 |
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| 200 | 1 | |a Evaluating non-relational storage technology for HEP metadata and meta-data catalog |f M. A. Grigorjeva (Grigorieva) [et al.] | |
| 203 | |a Text |c electronic | ||
| 300 | |a Title screen | ||
| 320 | |a [References: 7 tit.] | ||
| 330 | |a For the purpose of testing and the search for new drug compounds, designed to heal many human diseases, it is necessary to investigate the deformation of experimental tissue samples under influence of these drugs. For this task a precision force sensor for measuring the mechanical tension, produced by isolated ring segments of blood vessels and airways was created. The hardware and software systems for the study of changes in contractile responses of the airway smooth muscles and blood vessels of experimental animals was developed.Large-scale scientific experiments produce vast volumes of data. These data are stored, processed and analyzed in a distributed computing environment. The life cycle of experiment is managed by specialized software like Distributed Data Management and Workload Management Systems. In order to be interpreted and mined, experimental data must be accompanied by auxiliary metadata, which are recorded at each data processing step. Metadata describes scientific data and represent scientific objects or results of scientific experiments, allowing them to be shared by various applications, to be recorded in databases or published via Web. Processing and analysis of constantly growing volume of auxiliary metadata is a challenging task, not simpler than the management and processing of experimental data itself. Furthermore, metadata sources are often loosely coupled and potentially may lead to an end-user inconsistency in combined information queries. To aggregate and synthesize a range of primary metadata sources, and enhance them with flexible schema-less addition of aggregated data, we are developing the Data Knowledge Base architecture serving as the intelligence behind GUIs and APIs. | ||
| 461 | 1 | |0 (RuTPU)RU\TPU\network\3526 |t Journal of Physics: Conference Series | |
| 463 | 1 | |t Vol. 762, iss. 1 : Advanced Computing and Analysis Techniques in Physics Research (ACAT2016) |o 17th International Workshop, 18-22 January 2016, Valparaiso, Chile |o [proceedings] |v [012017, 5 p.] |d 2016 | |
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| 610 | 1 | |a метаданные | |
| 701 | 1 | |a Grigorjeva (Grigorieva) |b M. A. |c specialist in the field of informatics and computer technology |c Researcher of Tomsk Polytechnic University |f 1983- |g Mariya Aleksandrovna |3 (RuTPU)RU\TPU\pers\38423 | |
| 701 | 1 | |a Golosova |b M. V. |g Marina Vladimirovna | |
| 701 | 1 | |a Gubin |b M. Yu. |c specialist in the field of informatics and computer technology |c Lead programmer of Tomsk Polytechnic University |f 1985- |g Maksim Yurjevich |3 (RuTPU)RU\TPU\pers\38455 | |
| 701 | 1 | |a Klimentov |b A. A. |c mathematician |c The Head of the Laboratory of Tomsk Polytechnic University |f 1959- |g Aleksey Anatoljevich |3 (RuTPU)RU\TPU\pers\37345 | |
| 701 | 1 | |a Osipova |b V. V. |c specialist in the field of informatics and computer technology |c programmer, associate Professor of Tomsk Polytechnic University, candidate of technical Sciences |f 1984- |g Viktoriya Viktorovna |3 (RuTPU)RU\TPU\pers\35513 |9 18695 | |
| 701 | 1 | |a Ryabinkin |b E. A. |g Evgeny Aleksandrovich | |
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