A real time data visualization and analysis environment, scientific data management of large weather radar archives

Author(s):  
M Toussaint ◽  
M Malkomes ◽  
M Hagen ◽  
H Höller ◽  
P Meischner
Author(s):  
Muhammad Febrian Rachmadhan Amri ◽  
I Made Sukarsa ◽  
I Ketut Adi Purnawan

The online business era causes the form of transactions to occur so quickly that the information stored in the data warehouse becomes invalid. Companies are required to have a strong system, which is a system that is real time in order to be able to perform data loading into the media repository that resides on different hosts in the near-real time. Data Warehouse is used as a media repository of data that has the nature of subject-oriented, integrated, time-variant, and is fixed. Data Warehouse can be built into real time management with the advantages possessed and utilize Change Data Capture. Change Data Capture (CDC) is a technique that can be used as problem solution to build real time data warehousing (RTDW). The binary log approach in change data capture is made to record any data manipulation activity that occurs at the OLTP level and is managed back before being stored into the Data Warehouse (loading process). This can improve the quality of data management so that the creation of the right information, because the information available is always updated. Testing shows that Binary Log approach in Change Data Capture (BinlogCDC) is able to generate real time data management, valid current information, dynamic communication between systems, and data management without losing any information from data manipulation.


Author(s):  
Peter Wozniak ◽  
Oliver Vauderwange ◽  
Nicolas Javahiraly ◽  
Dan Curticapean

2009 ◽  
Vol 8 (3) ◽  
pp. 212-229 ◽  
Author(s):  
George Chin ◽  
Mudita Singhal ◽  
Grant Nakamura ◽  
Vidhya Gurumoorthi ◽  
Natalie Freeman-Cadoret

For scientific data visualizations, real-time data streams present many interesting challenges when compared to static data. Real-time data are dynamic, transient, high-volume and temporal. Effective visualizations need to be able to accommodate dynamic data behavior as well as Abstract and present the data in ways that make sense to and are usable by humans. The Visual Content Analysis of Real-Time Data Streams project at the Pacific Northwest National Laboratory is researching and prototyping dynamic visualization techniques and tools to help facilitate human understanding and comprehension of high-volume, real-time data. The general strategy of the project is to develop and evolve visual contexts that will organize and orient high-volume dynamic data in conceptual and perceptive views. The goal is to allow users to quickly grasp dynamic data in forms that are intuitive and natural without requiring intensive training in the use of specific visualization or analysis tools and methods. Thus far, the project has prototyped five different visualization prototypes that represent and convey dynamic data through human-recognizable contexts and paradigms such as hierarchies, relationships, time and geography. We describe the design considerations and unique features of these dynamic visualization prototypes as well as our findings in the exploration and evaluation of their use.


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