A Personalized Biological Data Management System Based on BSML

2006 ◽  
pp. 362-371 ◽  
Author(s):  
Kwang Su Jung ◽  
Sunshin Kim ◽  
Keun Ho Ryu
Keyword(s):  
Data Management ◽  
Management System ◽  
Biological Data ◽  
Data Management System ◽  
Biological Data Management

scholarly journals qPortal – A science gateway for biomedical applications

2017 ◽  
Author(s):  
Christopher Mohr ◽  
Andreas Friedrich ◽  
David Wojnar ◽  
Erhan Kenar ◽  
Aydin Can Polatkan ◽  
...  
Keyword(s):  
Data Management ◽  
Management System ◽  
High Performance ◽  
Workflow Management ◽  
Computing System ◽  
Heterogeneous Data ◽  
Biological Data ◽  
Data Management System ◽  
User Interactions ◽  
Science Gateway

Modern biomedical research aims at drawing biological conclusions from large, highly complex biological datasets. Nowadays, it is common practice to make extensive use of high-throughput technologies that produce big amounts of heterogeneous data. In addition to the ever-improving accuracy, methods are getting faster and cheaper, resulting in a steadily increasing need for large amounts of storage, data management, and easily accessible means of analysis. We present qPortal, a web-based science gateway providing users with an intuitive way to manage and analyze quantitative biological data. Pre-programmed analysis pipelines, quality control workflows, and visualization tools are offered to the user. Through intensive user interactions, appropriate data models have been developed. These models build the biological data management system and provide possibilities to annotate data, query existing metadata for statistics and future re-analysis on a high-performance computing system via a coupling to gUSE, a workflow management system.

scholarly journals qPortal – A science gateway for biomedical applications

2017 ◽  
Author(s):  
Christopher Mohr ◽  
Andreas Friedrich ◽  
David Wojnar ◽  
Erhan Kenar ◽  
Aydin Can Polatkan ◽  
...  
Keyword(s):  
Data Management ◽  
Management System ◽  
High Performance ◽  
Workflow Management ◽  
Computing System ◽  
Heterogeneous Data ◽  
Biological Data ◽  
Data Management System ◽  
User Interactions ◽  
Science Gateway

Modern biomedical research aims at drawing biological conclusions from large, highly complex biological datasets. Nowadays, it is common practice to make extensive use of high-throughput technologies that produce big amounts of heterogeneous data. In addition to the ever-improving accuracy, methods are getting faster and cheaper, resulting in a steadily increasing need for large amounts of storage, data management, and easily accessible means of analysis. We present qPortal, a web-based science gateway providing users with an intuitive way to manage and analyze quantitative biological data. Pre-programmed analysis pipelines, quality control workflows, and visualization tools are offered to the user. Through intensive user interactions, appropriate data models have been developed. These models build the biological data management system and provide possibilities to annotate data, query existing metadata for statistics and future re-analysis on a high-performance computing system via a coupling to gUSE, a workflow management system.

Risk Management on Information Security in ABC Company

2017 ◽  
Vol 4 (1) ◽  
pp. 62-66
Author(s):  
Luyen Ha Nam
Keyword(s):  
Risk Management ◽  
Information Security ◽  
Data Management ◽  
Management System ◽  
Risk Mitigation ◽  
Data Management System ◽  
Data Centre ◽  
Long Time ◽  
Mitigation Action ◽  
Better Than

From long, long time ago until nowadays information still takes a serious position for all aspect of life, fromindividual to organization. In ABC company information is somewhat very sensitive, very important. But how wekeep our information safe, well we have many ways to do that: in hard drive, removable disc etc. with otherorganizations they even have data centre to save their information. The objective of information security is to keep information safe from unwanted access. We applied Risk Mitigation Action framework on our data management system and after several months we have a result far better than before we use it: information more secure, quickly detect incidents, improve internal and external collaboration etc.

Benchmarking and Analyzing the Energy Consumption of Cloud Data Management System

2014 ◽  
Vol 36 (7) ◽  
pp. 1485-1499 ◽  
Author(s):  
Jie SONG ◽  
Tian-Tian LI ◽  
Zhi-Liang ZHU ◽  
Yu-Bin BAO ◽  
Ge YU
Keyword(s):  
Energy Consumption ◽  
Data Management ◽  
Management System ◽  
Data Management System ◽  
Cloud Data ◽  
Cloud Data Management

The UNC Graph Server: A Distributed Hypermedia Data Management System

1991 ◽  
Author(s):  
Douglas E. Shackelford ◽  
John B. Smith ◽  
Joan Boone ◽  
Barry Elledge
Keyword(s):  
Data Management ◽  
Management System ◽  
Data Management System
Sign in / Sign up

Export Citation Format

Share Document