Distributed and Parallel Databases
Supporting Dynamic Interactions among Web-Based Information Sources
IEEE Transactions on Knowledge and Data Engineering
Novel mediator architectures for Grid information systems
Future Generation Computer Systems
Improving Scientific Data Extraction Using Metadata Classification
ISPAN '09 Proceedings of the 2009 10th International Symposium on Pervasive Systems, Algorithms, and Networks
| Hi-index | 0.00 |
Data extraction and information retrieval from a great volume of data set always is a tedious and difficult work Therefore, an effective and efficient technology for searching for desired data becomes increasingly important Due to metadata with certain attributes characterizing the data files, to extract data with help of metadata can be expectably to simplify the work In our previous work, we have proposed a Metadata Classification (MC) to improve significantly the performance of scientific data extraction In this paper, we will propose a scientific data extraction architecture that is based on the assistance of classified metadata The architecture is built by utilizing mediator/wrapper to develop a scientific data extracting system to help oceanographer to analyze the ocean's ecology by means of temperature, salinity and other information The result shows that the architecture with the help of metadata classification can extract user's desired data effectively and efficiently.