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Titlebook: Big Scientific Data Management; First International Jianhui Li,Xiaofeng Meng,Zhihui Du Conference proceedings 2019 Springer Nature Switzer

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发表于 2025-3-21 18:51:57 | 显示全部楼层 |阅读模式
期刊全称Big Scientific Data Management
期刊简称First International
影响因子2023Jianhui Li,Xiaofeng Meng,Zhihui Du
视频video
学科分类Lecture Notes in Computer Science
图书封面Titlebook: Big Scientific Data Management; First International  Jianhui Li,Xiaofeng Meng,Zhihui Du Conference proceedings 2019 Springer Nature Switzer
影响因子.This book constitutes the refereed proceedings of the First International Conference on Big Scientific Data Management, BigSDM 2018, held in Beijing, Greece, in November/December 2018...The 24 full papers presented together with 7 short papers were carefully reviewed and selected from 86 submissions. The topics involved application cases in the big scientific data management, paradigms for enhancing scientific discovery through big data, data management challenges posed by big scientific data, machine learning methods to facilitate scientific discovery, science platforms and storage systems for large scale scientific applications, data cleansing and quality assurance of science data, and data policies..
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书目名称Big Scientific Data Management影响因子(影响力)




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书目名称Big Scientific Data Management网络公开度




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书目名称Big Scientific Data Management被引频次




书目名称Big Scientific Data Management被引频次学科排名




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书目名称Big Scientific Data Management年度引用学科排名




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书目名称Big Scientific Data Management读者反馈学科排名




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An Efficient Parallel Framework to Analyze Astronomical Sky Survey Data,nthetic data with raw files and HBase entries as data sources and result formats, reduced the analyze cost for scientists not familiar with parallel programming while needs to handle a mass of data. We integrate time series anomaly detection algorithms with our parallel dispatching module to achieve
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Automated and Intelligent Data Migration Strategy in High Energy Physical Storage Systems,ning algorithm model to predict the evolution trend of data access heat. This paper discussed the implementation of some initial parts of the system. Then some preliminary experiments are conducted with these parts.
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Using Hadoop for High Energy Physics Data Analysis,the local file system on data nodes instead of using Hadoop data streaming interface. This makes HEP jobs run on Hadoop possible. We also develop diverse MapReduce model for HEP jobs such as Corsika simulation, ARGO detector simulation and Medea++ reconstruction. And we develop a toolkit for users t
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Multi-dimensional Index over a Key-Value Store for Semi-structured Data, unit of the range partitioned Key-value store) to utilize distributed computing and data locality. Our prototype of MD-Index is built on HBase, the standard Key-value database. Experimental results reveal that MD-Index is capable of storing and retrieving trillions of semi-structured data and achie
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