Retrieval methods, data collection

The core of the EntityDictionaryDao is in the retrieve...() methods. Here we assume the entity dictionaries are stored in a relational database. They can also be accessed from other types of data sources, such as web service, XML, and flat files. The point is to transform them into something that can be accessed easily and quickly by CRS. Take a closer look at the retrievePersonnel() method. Like most other retrieve...() methods, retrievePersonnel() returns a Map. What is in the Map depends on what kind of lookups the clients want to use to access the personnel dictionary. In the context of CRS, the personnel data can be accessed by its entirety, the research site where the person is located, person id, person s full name, or person s username. Therefore, the Map that retrievePersonnel() returns has four Collections—an entire personnel list, a site-people map, a person id-person map, a person s full name-person map, and a username-person map. 

The sorts of information listed above are usefui only if they are stored in a systematic manner and there are suitable mechanisms for the retrieval of the relevant data. Similar considerations apply when the data come, not from an outside source, but from within the organisation. For example, accident data (both injury and damage), sick absence and product complaints are all internally generated data. It is necessary to set up systematic methods of collecting, storing and retrieving these data if the best use is to be made of them. 

For this retrieval method to be valuable, the conformations of the 3D models stored in the CIR system must have intrinsic meaning. One example of a data collection in which this is true would be the CSD, which contains experimentally determined X-ray structures of organic molecules whose representation retains inter-molecular non-bonded associations. In this context, rigid 3D search has proven quite useful. The same holds true for the IDITIS format of the PDB. 

The RMDB consists of two mayor sections computer data storage and retrieval system, and backup microfilm data bank file. The computer data storage and retrieval system is used for die standard reliability and maintainability data listing, special calculations, and searches. This data bank system has been established to facilitate remote terminal access compatible with the GIDEP remote terminal programs. The microfilm data bank file is used for storage and distribution of supplier s documents, failure analysis curves, description of methods used in the collection of the data, and additional background information too extensive to include in the computer data bank. 

Webster s definition for database is a large collection of data in a computer, organized so that it can be expanded, updated, and retrieved rapidly for various uses. An LC/MS database established for drug impurities contains multi-dimensional information such as relative retention times, UV spectra, molecular mass and substructural information. In order for the information to be updated and expanded, the methods used for information collection need to be unified. A generic LC/MS method allows relevant information to be collected in a consistent... 

In the bioinformatics realm, SRS (Sequence Retrieval System) [2] is a popular system, which uses a centralized collection of data resources primarily in flat text file form and, more recently, handles XML (Extensible Markup Language) files as well. Data resources are treated in a federated manner since each is maintained in its original form. However, SRS contains a large number of cross-references between corresponding fields in various data sources, so that keyword searches can be done across them. SRS thus performs more structured searches across the information than what a simple text search provides (such as web indexes perform, for example). Even though the data model implicit in the cross-reference tables is not very deep, SRS provides a useful way for users to browse and do simple queries across a large number of data sources as well as to integrate results from some computational methods. 

ASPEN is supported by a versatile set of physical property correlations representing the current state-of-the-art. Physical property monitors control the property calculations in accordance with methods and models specified by the user. The user is allowed to specify different combinations of physical property calculation methods in different parts of the process. For specialized components such as coal or limestone, a collection of non-conventional property models is available. ASPEN includes data banks from which the required physical property constants and correlation parameters can be retrieved automatically at run... 

As measured data are collected, efficient methods are needed for their storage and retrieval. Compact storage or compression can be achieved by eliminating irrelevant and redundant contributions in the data. These contributions are usually high frequency, low amplitude noise that contaminate the important features and transients in the data. Therefore, the compression problem is similar to filtering in the sense that both rely on noise removal to extract the important features in the data. Some of the popular compression teehniques used in the ehemieal manufacturing industry include the box car... 

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