Showing posts with label database. Show all posts
Showing posts with label database. Show all posts

Tuesday, October 5, 2010

Advanced Database Technology and Design (Artech House Computer Library)

Advanced Database Technology and Design (Artech House Computer Library) Review


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Advanced Database Technology and Design (Artech House Computer Library) Feature

An introduction to developments in database systems design presented from an applications point of view. Featuring contributions from experts in the field, it pays special attention to issues raised by new trends in database design, and how these developments affect the programmer and database administrator.


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Thursday, June 17, 2010

Web-based tools for data analysis and quality assurance on a life-history trait database of plants of Northwest Europe [An article from: Environmental Modelling and Software]

Web-based tools for data analysis and quality assurance on a life-history trait database of plants of Northwest Europe [An article from: Environmental Modelling and Software] Review


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Web-based tools for data analysis and quality assurance on a life-history trait database of plants of Northwest Europe [An article from: Environmental Modelling and Software] Feature

This digital document is a journal article from Environmental Modelling and Software, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
Most data mining techniques have rarely been used in ecology. To address the specific needs of scientists analysing data from a plant trait database developed during the LEDA project, a web-based data mining tool has been developed. This paper presents the DIONE data miner and the project it has been developed in. It addresses the nature of plant trait data from a data mining perspective and points out problems that arise when preparing data for this process. The availability of a large amount of high quality data is an essential prerequisite for successful data mining. To ensure this, a software aided reviewing process has been integrated into the LEDA Traitbase system. The process enables third-party contributors to easily commit their data to LEDA, while assuring adherence of the data to the LEDA standard. The paper concludes with information about data mining results on plant trait data achieved so far and gives an outlook on the applicability of data mining to the fields of ecology.


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Friday, April 30, 2010

Developing Quality Complex Database Systems: Practices, Techniques and Technologies

Developing Quality Complex Database Systems: Practices, Techniques and Technologies Review


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Developing Quality Complex Database Systems: Practices, Techniques and Technologies Feature

The objective of Developing Quality Complex Database Systems is to provide opportunities for improving today's database systems using innovative development practices, tools and techniques. Each chapter of this book will provide insight into the effective use of database technology through models, case studies or experience reports. An emphasis is placed on organizational and management issues associated with the use of such technology inclusive of lessons learned and best practices.


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Saturday, January 2, 2010

Quality Information of the Software Development Process: Setting up a quality database for analysis of Software Development Process Information

Quality Information of the Software Development Process: Setting up a quality database for analysis of Software Development Process Information Review


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Quality Information of the Software Development Process: Setting up a quality database for analysis of Software Development Process Information Feature

Thorough the execution of a software development process, several databases are used, where data related to every activity is stored. As the data could lack the appropriate quality, the information products retrieved from them could also not be as useful as it is necessary. Such products are essential to make estimations for the involved project, or detect errors that can be corrected in order to improve what is wrong with the development process performance. The method proposed in this book can be used to carry out a quality enhancement of data related to the software process. It is based on a research made on existent literature about quality management of information in data bases, and it relies on the concept of quality dimensions. The method is helpful for teams as well as for companies dedicated to software development, which can apply it to improve the quality of the information related to their software process, and consequently increase its efficiency. It is appropriate for the creation of new databases and for analyzing and increasing the quality of information stored in existent databases. It thus, constitutes a valuable tool in the software construction field.


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