Research Paper on "Geometrically, Various Query Languages Has Been Developed"
Research Paper 16 pages (4443 words) Sources: 16
[EXCERPT] . . . .
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
Introduction
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, concerni
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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
Description
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
Description
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].
SPARQL
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… READ MORE
Quoted Instructions for "Geometrically, Various Query Languages Has Been Developed" Assignment:
VERY IMPORTANT! Please follow the exact steps list below : 10 STEPS
FYI - I THOUGHT Data Consistency, Integrity, and Security would make a great topic since thats the area i*****'m studying i.e is Information Security
EXPECTATION: do a comprehensive literature search and survey, select and study a specific topic in one subject area of database systems, and write a technical paper on the selected topic. The technical paper you are asked to write can be a detailed comprehensive survey on some specific topic or the original research work that will have been done
by yourself.
REQUIREMENTS and Instructions for the TECHNICAL PAPER:
1. The objective of the paper should be very clear about subject, scope, domain, and the goals to be
achieved.
2. The paper should address the important advanced and critical issues in a specific area of database systems. Your research paper should emphasize not only breadth of coverage, but also depth of coverage in the specific area.
3. IMPORTANT! The research paper should give the measurable conclusions and future research directions (this is your contribution).
4. It might be beneficial to review or browse through about 20 to 30 relevant technical articles before you make decision on the topic of the research project.
5. The research paper should reflect the quality at certain academic research level.
6. The paper should be about at least 16 to 20 pages (double space) in length.
7. IMPORTANT! The paper should include adequate abstraction or introduction, and reference list.
8. IMPORTANT! Please write the paper in your words and statements, and please give the names of references,
citations, and resources of reference materials if you want to use the statements from other reference articles.
9. From the systematic study point of view, you may want to read a list of technical papers from relevant magazines, journals, conference proceedings and theses in the area of the topic you choose.
10. For the format and style of your research paper, please make reference to either ACM , IEEE journal articles or SCIS Dissertation Guide (I CAN SEND YOU THIS LATER IF YOU PREFER),
POSSIBLE TOPICS FOR WRITTEN REPORTS
Data Consistency, Integrity, and Security
Data Models and Data Modeling
File Structures and Access Methods
Index Structures
Integrity Conditions or Constraints
Query Languages and Query Optimization
Security and Authorizations
Storage Managers
Transaction Processing and Management
Hierarchical Database Systems
Network Database Systems
Relational Database Systems
Object-***** Database Systems
DATABASE RESEARCHES:
Active Databases
Distributed Databases
Distributed Object-***** Databases
Extensible Databases
Federated Databases or Heterogeneous Databases
Object-***** and Object-Relational Databases
Multidatabase Systems
Parallel Databases
High Performance Databases
Trusted Database Management Systems
DATABASE APPLICATIONS:
Audio/Video Database Systems
CAD/CAE/CAM/CAP/CASE/CIM Databases
Client/Server Database Systems
Engineering Databases
Genomic Databases
Geographical Databases and Information Systems
Hypertext/Hypermedia Databases (Object)
Historical Databases
Image, Pictorial and Visual Databases
Mobile Data Management and Communication
Multimedia Databases and Information Systems
Real Time Database Systems
Scientific Databases
Software Engineering Databases
Spatial Databases
Spatiotemporal Databases
Statistical Database
DATA MODELS and DATABASE MODELING:
Entity-Relationship Model
Extended ER Model
Enhanced ER Model
Complex Data Model
Extended Relational Data Model
Functional Data Model
Non First Normal Data Model (NF2)
Object-***** Data Model
Semantic Data Model
Universal Modeling Language
OTHERS:
Client/Server SQL
Complex and Composite Objects
Data Dictionary
Data Streaming
Data Warehousing
Database Compression
Database Design Methodologies
Database Design Automation and Database Design Tools
Database Security and Recovery
Distributed Objects
Graphical and Intelligent Database Interfaces
Grid Computing
Heterogeneous Systems and Interoperability
Incomplete, Imprecise or Uncertain Information
Information Engineering
JDBC, ODBC
Knowledge and Expert Database Systems Applications
Knowledge Representation in Artificial Intelligence and its Connections with
Knowledge Discovery and Machine Learning in Database Systems
On-Line Analytical Processing (OLAP)
Referential Integrity Constraints and Applications
Rules and Triggers
Semantic Data Models and Modeling
Semantic Web
Semi-Structural Data and XML
Single and Multidimensional Index Schema
SQL Standards and Standardization
Stored Procedure
Transaction Processing Benchmark
Work Flow Management *****
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