Research Paper: Geometrically, Various Query Languages Has Been Developed

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¶ … geometrically, various query languages has been developed in response to help access and retrieve information of interest from these resources. Although query languages differ in terms of their functionality and applicability, they share certain commonalties and provide a useful framework in which to examine current trends and project future developments. To this end, this study provides a review of the relevant peer-reviewed and scholarly literature, as well as reliable online resources, to develop a background and overview and specifics concerning query languages and query optimization. An analysis of current trends and projections of these trends into the future is followed by a summary of the research in the conclusion.

Query Languages and Query Optimization


In the Age of Information, making sense of all of the available resources has been likened to trying to drink from a fire hose. Moreover, innovations in geographic technologies have added to the flood of information, and making sense of it all in terms of the when, where, and what aspects of an event or issue require specialized queries. Therefore, identifying the current level of technological development as well as recent trends can establish relevant benchmarks that can be used by researchers in the future, as well as providing a snapshot of these issues as they currently exist. This snapshot can be used to extend the recent trends in query language and optimization into the future given the known increases in computer processing speeds. To this end, this study provides a review of the relevant peer-reviewed and scholarly literature, as well as reliable online resources, concerning query languages and query optimization, prefaced by a background and overview section, as well as a projection of recent trends into the future in the conclusion.

Review and Analysis

Background and Overview

In this regard, Bidlack and Wellman (2010) recently observed that an increasingly wide array of information resources has driven the demand for more efficient ways to access the specific information that is needed [1]. Indeed, the efficient use of information resources has become an integral part of many business models today. For instance, according to Webster, "It is impressive to watch the rapid development of the online world, encompassing the World Wide Web, journal and reference databases, library catalogs, e-books, and other e-content. We have come to depend on this newer online world as it grows more powerful and more complex" [2].

Satisfying the need for accessing information systems in general and databases in particular involves developing and applying some type of query. For instance, Calvanese and de Giacomo report that, "Data sources have been considered simply as systems that provide data but make no further contribution to the query-answering process" [3]. With Internet browsers, this need can be satisfied by a simple and straightforward search using Google, for example, but accessing various types of databases requires specialized query techniques and languages. For instance, a database management system (DBMS) is a program that can input, edit and retrieve information from a database. A database is a collection of information organized into records and fields, and stored as files on a computer. Sometimes the term database is used to include the DBMS as well. Relational, object-oriented, network, flat and hierarchical are all types of DBMS. They differ in how they organize information for storage. Retrieval from a DBMS requires a query language, a structured way for expressing search requests. Relational DBMS alone have a standard query language called SQL (structured query language) [4]. Structured Query Language (SQL) is really a programming language designed to get information out of and then put it into a relational database. Queries are constructed from a command language that allows one to select, insert, update and locate data. SQL is a recognized standard [5]. Other query languages have more focused applications, while others are designed to provide searches in more broad-based settings and these various languages are discussed further below.

Query Languages

In order to understand how query languages work, it is important to describe the environment in which they function. Although query languages differ in terms of purpose, functionality and interface, they share a common feature with respect to access data represented in a database in some fashion and returning the aggregated results to the user. A representational schema needs to anticipate all possible queries and analysis to be performed in an information system. Since relational database management systems were dominant, respective temporal languages were developed as extensions of standard query language (SQL) [6]. Query languages can be designed to allow query computation to be performed internally and to ease users from having to remember technical operations in a query process [7].

The when, where and what (the so-called "spatio-temporal) factors related to query languages are presented in Table 1 below.

Table 1

Query Language Spatio-Temporal Factors

Query Language


Query Spatio-Temporal Information about When

This kind of query is used to obtain information on temporal objects. Answers can be obtained by referring semantic or spatial objects to temporal objects through a proper relation table. Life-oriented questions inquire when birth, death, splitting, merging or reincarnation occur in a certain period of time, while motion-oriented questions ask when a move, jump or spread takes place.

Query Spatio-Temporal Information about Where

This type of query aims at obtaining information about spatial objects for locations and spatial properties of a semantic object at a specific time. Where questions can be static (asking whereabouts or states of entities or attributes) or dynamic (asking paths of an entity changing its location through time).

Query Spatio-Temporal Information about What

This type of query seeks information about changes in which the focal information is semantic objects such as changes of supermarket services for a particular area. We first identify the area of interest, and then examine what has been changed in that area by referring to its corresponding semantic objects at that time.

Source: Frank 2001, p. 226

In recent years, database engineers have proposed the development of pure database models and query languages that can be used for representing and handling semi-structured data (SSD) in order to facilitate the processing of information exchanges and the efficiency of software systems in a broad array of applications, including genome databases, digital libraries and electronic commerce platforms [8]. According to Stefankis, "In a SSD set it is expected that there will be objects with missing attributes, objects with multiple occurrences of the same attribute, different data types associated with the same attribute in different objects, and/or semantically related information represented differently in various objects. All the above factors render traditional data models (such as the relational and the object-oriented model) inadequate to represent and handle SSD sets" [9].

Recent innovations in technological development have provided two basic alternatives for modeling semi-structured data sets, with the first alternative being created by the database community and the second alternative from software engineers who are actively involved in the development of Web-based technologies to query semi-structured data [10]. Some of the most well-known examples of such languages include the Object Exchange Model (OEM) and the Lightweight Object REpository query Language (LOREL) [11].

Some other current examples of query languages and their applications are presented in Table 2 below.

Table 2

Query Language Types

Query Language


eXtensible Markup Language (XML)

Web-based technology offers the eXtensible Markup Language (XML) and its surrounding technologies that are well suited for modeling and querying semi-structured data (SSD) sets [12]. Extensible markup language is a flexible way to create standard information formats and share both the format and the data on the World Wide Web. It improves the functionality of the Web by letting you identify your information in a more accurate, flexible, and adaptable way [13]. Prior to the introduction of XML, there was SGML (Standard Generalized Markup Language), which was developed in the early '80s and widely used for large documentation projects. The development of HTML (Hyper Text Markup Language) started in 1990. The designers of XML simply took the best parts of SGML, guided by the experience with HTML, and produced something that is no less powerful than SGML; however, it is vastly more regular and simpler to use. It must be said that SGML is mostly used for technical documentation and much less for other kinds of data; with XML, it is exactly the opposite. XML is a pared-down version of SGML, designed especially for Web documents. It allows designers to create customized TAGS (a special word inserted in a document that specifies how the document, or a portion of the document, should be formatted), enabling the definition, transmission, validation, and interpretation of data between applications and organizations [14].


Relationship networks can be queried using Simple Protocol and RDF Query Language (SPARQL -- pronounced "Sparkle"). SPARQL is a form of Structured Query Language (SQL) specifically used for querying within inference software [15].

Web Ontology Language (OWL-DL.3)

These standards-based knowledge representation mechanisms provide computationally feasible knowledge representation (KR) for business processes. (OWL) is a W3C standard for semantic knowledge representation. Web Services and… [END OF PREVIEW]

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