Query languages

AZoM —The AtoZ of Materials. URL http //www.azom.com/. While not specific to biomaterials, this is an extensive resource for materials, suppliers, and experts. Searchable by keyword, application, industry, material property, and natiiral language query. Customizable newsletter includes the latest news and technical information on materials of particular interest. 

Smart Methods Index Supports natural language query of database to identify analytical methods for particular waste site pollutants (prototype) PROLOG Micro R. Olivero/Lockheed D. Bottrell/EPA/EMSL... 

The TAMBIS Project (Transparent Access to Multiple Bioinformatics Information Sources) [Baker et al. 1991] started in the late 1990s at the University of Manchester and has developed a powerful data model together with a knowledge base affording near-natural language queries to federated distributed biological databases. 

Among many approaches to manipulating a relational database, the most prevalent one is a language called SQL (Structured Query Language) [2]. 

If the query provides thousands of hits, the analyze features are particularly advantageous. One method is to analyze the results by any of the criteria that arc listed, c.g., by language (default), author names, journals, puhlication year, and so on. If one specification is selected and the choice is modified, the hit list will be updated. A more specific analysis is available with the Refine" option. where the user has the opportunity to choose one of eight criteria (including the search topics above) with further individual input. Several refinements of the hit list can reduce the result to a concise list of literature. To read the abstract of an article, the microscope button (to the right of the citation) has to be pressed (Figure 5-15). 

Another important feature of a LIMS DBMS is the abiUty to perform ad hoc database queries. It is impossible to predict all the forms in which LIMS users will want to display their data while the LIMS is being designed. As a result, it is desirable to select a LIMS which allows users to define their own reports. Most commercial DBMS have a standard query language (SQL) interface. SQL is a simple database query tool which is based on... 

English-language commands. This sample SQL query says, "Give me all sample request data containing John Smith as the customer."... 

Most clinical data management systems used for clinical trials today store their data in relational database software such as Oracle or Microsoft SQL Server. A relational database is composed of a set of rectangular data matrices called tables that relate or associate with one another by certain key fields. The language most often used to work with relational databases is structured query language (SQL). The SAS/ACCESS SQL Pass-Through Facility and the SAS/ACCESS LIBNAME engine are the two methods that SAS provides for extracting data from relational databases. 

An interpreter, or explanation system, forms the interface between the user and the core software. It interprets queries from the user so that the inference engine can make sense of them and presents the conclusions of the inference engine in language appropriate to the needs and level of knowledge of the user. It is also responsible for generating explanations of the reasoning that... 

The data model is highly normalised, which suits data integrity and manipulation via the SQL language, but creates difficulties for the end-user in terms of accessing the data. Straightforward queries may involve numerous tables which have to be joined together. As a practical work-around, the database includes several very large denormalized tables. 

Do not use language primitive casts to access other interfaces of a component, because they would understand only language-level objects. Instead, there is a prescribed explicit query protocol for getting to other interfaces. 

We hope that the next generation of component-aware languages can make an assembly of objects appear as one, with intelligent query of object identity and interfaces. 

Query languages include declarative access and querying using SQL. 

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. 

With federation, databases can become part of the same information system because they share common communication language(s). Each database in a federated data system is free to establish and maintain its own data model. The utility of such a system is critically dependent upon the ability of each participating database to process queries using common protocols. It is only required that databases in such a system understand the languages that are appropriate for their local data model. It is not required (nor particularly desirable) that all databases understand all query languages. 

In contrast, the idea of federating disparate information sources is very straightforward. Each information source can be organized to represent its kind of data in the most natural and expressive manner for that specific kind of information. Given query languages that are adequately expressive, a federation of such databases can appear to be a single integrated information system. 

SMARTS Substructure query language (developed by Daylight Inc.)... 

Both the nucleic acid sequences and the protein sequences derived from the biological information are collected in most such databases. Large amounts of data in these databases need to be sorted, stored, retrieved, and analyzed. Selection of subsets of data for particular analysis should also be done. IT providers designed such a data warehouse and developed an interface that provides an important benefit to researchers by making it easy to access the existing information and also to submit new entries (i.e., datamining) (Table 5.6). Middlewares and structured query language (SQL) softwares were developed for this purposes. The former one is used... 

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