METHODOLOGY FOR DATA CONVERSION FROM XML DOCUMENTS TO RELATIONS USING EXTENSIBLE STYLESHEET LANGUAGE TRANSFORMATION

2009 ◽  
Vol 19 (02) ◽  
pp. 249-281 ◽  
Author(s):  
JOSEPH FONG ◽  
HERBERT SHIU ◽  
JENNY WONG
Keyword(s):  
Relational Databases ◽  
Transformation Process ◽  
Xml Schema ◽  
Conversion Process ◽  
Relational Data ◽  
Data Conversion ◽  
Tree Model ◽  
Relational Structures ◽  
Xml Documents ◽  
Schema Translation

Extensible Markup Language (XML) has been used for data-transport and data-transformation while the business sector continues to store critical business data in relational databases. Extracting relational data and formatting it into XML documents, and then converting XML documents back to relational structures, becomes a major daily activity. It is important to have an efficient methodology to handle this conversion between XML documents and relational data. This paper aims to perform data conversion from XML documents into relational databases. It proposes a prototype and algorithms for this conversion process. The pre-process is schema translation using an XML schema definition. The proposed approach is based on the needs of an Order Information System to suggest a methodology to gain the benefits provided by XML technology and relational database management systems. The methodology is a stepwise procedure using XML schema definition and Extensible Stylesheet Language Transformations (XSLT) to ensure that the data constraints are not scarified after data conversion. The implementation of the data conversion is performed by decomposing the XML document of a hierarchical tree model into normalized relations interrelated with their artifact primary keys and foreign keys. The transformation process is performed by XSLT. This paper will also demonstrate the entire conversion process through a detailed case study.

An Interpreter Approach for Exporting Relational Data into XML Documents with Structured Export Markup Language

2012 ◽  
Vol 23 (1) ◽  
pp. 49-77 ◽  
Author(s):  
Joseph Fong ◽  
Herbert Shiu
Keyword(s):  
Relational Databases ◽  
Complete Solution ◽  
Relational Data ◽  
Data Conversion ◽  
Markup Language ◽  
Xml Databases ◽  
Xml Documents ◽  
Business Operations ◽  
Almost All ◽  
User Friendly

Almost all enterprises use relational databases to handle real time business operations and most need to generate various XML documents for data exchanges internally among various departments and externally with business partners. Exporting data in a relational database to an XML document can be considered a data conversion process. Based on the four approaches for data conversion: Customized program, Interpretive transformer, Translator generator, and Logical level translation, this paper proposes a new interpretive approach using Structured Export Markup Language (SEML) interpreter for converting relational data into XML documents. The frameworks and languages proposed by other researchers are neither generic nor able to generate arbitrary XML documents. Therefore, SEML interpreter is a simple, user friendly, and complete solution with a new mark-up language ? SEML ? for data conversion. The solution can be used as a generic tool for extracting, transforming, and loading (ETL) purposes. In other words, the SEML interpreter is a solution for relational databases similar to what X-Query is for XML databases.

XRecursive

2013 ◽  
pp. 281-292
Author(s):  
Mohammed Adam Ibrahim Fakharaldien ◽  
Jasni Mohamed Zain ◽  
Norrozila Sulaiman ◽  
Tutut Herawan
Keyword(s):  
General Solution ◽  
Relational Database ◽  
Relational Databases ◽  
Xml Schema ◽  
Xml Data ◽  
Xml Documents ◽  
Extra Effort ◽  
Extensible Markup ◽  
Promising Solution ◽  
Reconstruction Time

Storing XML documents in a relational database is a promising solution because relational databases are mature and scale very well. They have the advantages that in a relational database XML data and structured data can coexist making it possible to build application that involve both kinds of data with little extra effort. This paper proposes an alternative method named Xrecursive for mapping XML (eXtensible Markup Language) documents to RDB (Relational Databases). The Xrecursive method does not need a DTD (Document Text Definition) or XML schema. Further, it can be applied as a general solution for any XML data. The steps and algorithm of Xrecursive are given in details to describe how to use the storing structure to storage and query XML documents in relational database. The authors report their experimental results on a real database, showing that the performance of their Xrecursive algorithm achieves better results in terms of storage size, insertion time, mapping time, and reconstruction time as compared with that SUCXENT and XParent methods. In overall, Xrecursive performs better in term of query performances as compared to the both methods.

TRANSLATING RELATIONAL SCHEMA WITH CONSTRAINTS INTO XML SCHEMA

2006 ◽  
Vol 16 (02) ◽  
pp. 201-243 ◽  
Author(s):  
JOSEPH FONG ◽  
ANTHONY FONG ◽  
H. K. WONG ◽  
PHILIP YU
Keyword(s):  
Relational Database ◽  
Xml Schema ◽  
Data Type ◽  
Relational Data ◽  
The Internet ◽  
Conceptual Schema ◽  
Root Element ◽  
Xml Documents ◽  
Type Definition ◽  
Xml Document

With XML adopted as the technology trend on the Internet, and with investment in the current relational database systems, companies must convert their relational data into XML documents for data transmission on the Internet. In the process, to preserve the users' relational data requirements of data constraints into the converted XML documents, we must define a meaningful root element for each XML document. The construction of an XML document is based on the root element and its relevant elements. The root element can be selected from a relational entity table in the existing relational database, which depends on the requirements to present the business behind. The relevant elements are mapped from the related entities, based on the navigability of the chosen entity. The derived root and relevant elements can form a Data Type Definition Graph (DTD-graph) of an XML conceptual schema diagram which can be mapped into a Data Type Definition (DTD) of an XML schema. The result is a translated XML schema with semantic constraints transferred from a relational conceptual schema of an Extended Entity Relationship (EER) model. The data conversion from relational data to the XML documents can be done after the schema translation. The relational data are loaded into XML documents according to the translated DTD.

Effects of geographic information system vector–raster–vector data conversion on landscape indices

1996 ◽  
Vol 26 (8) ◽  
pp. 1416-1425 ◽  
Author(s):  
Pete Bettinger ◽  
Gay A. Bradshaw ◽  
George W. Weaver
Keyword(s):  
Information System ◽  
Fractal Dimension ◽  
Geographic Information System ◽  
Cell Size ◽  
Grid Cell ◽  
Conversion Process ◽  
Data Conversion ◽  
Edge Density ◽  
Gis Data ◽  
Landscape Level

The effects of geographic information system (GIS) data conversion on several polygon-and landscape-level indices were evaluated by using a GIS vegetation coverage from eastern Oregon, U.S.A. A vector–raster–vector conversion process was used to examine changes in GIS data. This process is widely used for data input (digital scanning of vector maps) and somewhat less widely used for data conversion (output of GIS data to specific formats). Most measures were sensitive to the grid cell size used in the conversion process. At the polygon level, using the conversion process with grid cell sizes of 3.05, 6.10, and 10 m produced relatively small changes to the original polygons in terms of ln(polygon area), ln(polygon perimeter), and 1/(fractal dimension). When grid cell size increased to 20 and 30 m, however, polygons were significantly different (p < 0.05) according to these polygon-level indices. At the landscape level, the number of polygons, polygon size coefficient of variation (CV), and edge density increased, while mean polygon size and an interspersion and juxtaposition index (IJI) decreased. The youngest and oldest age-class polygons followed the trends of overall landscape only in terms of number of polygons, mean polygon size, CV, and IJI. One major side effect of the conversion process was that many small polygons were produced in and around narrow areas of the original polygons. An alleviation process (referred to as the dissolving process) was used to dissolve the boundaries between similarly attributed polygons. When we used the dissolving process, the rate of change for landscape-level indices slowed; although the number of polygons and CV still increased with larger grid cell sizes, the increase was less than when the dissolving process was not used. Mean polygon size, edge density, and fractal dimension decreased after use of the dissolving process. Trends for the youngest and oldest age-class polygons were similar to those for the total landscape, except that IJI was greater for these age-classes than for the total landscape.

Research on XML Documents and Relational Database Mapping Based on XML Schema

2014 ◽  
Vol 599-601 ◽  
pp. 1683-1687
Author(s):  
Xia Zhou
Keyword(s):  
Relational Database ◽  
Mapping Method ◽  
Xml Schema ◽  
Xml Documents

In order to implement the mapping between XML documents and relational database, this paper proposes the mapping method based on XML documents and relational database. On the basis of keeping documents ’hierarchy, order and uniqueness, this method can mapping XML documents to the corresponding relational database very quickly and implement the reconstruction of XML documents.

Controlling Access to XML Documents over XML Native and Relational Databases

2009 ◽  
pp. 122-141 ◽  
Author(s):  
Lazaros Koromilas ◽  
George Chinis ◽  
Irini Fundulaki ◽  
Sotiris Ioannidis
Keyword(s):  
Relational Databases ◽  
Xml Documents

GuessXQ

2013 ◽  
pp. 57-76
Author(s):  
Daniela Morais Fonte ◽  
Daniela da Cruz ◽  
Pedro Rangel Henriques ◽  
Alda Lopes Gancarski
Keyword(s):  
Information Retrieval ◽  
Learning Process ◽  
Web Application ◽  
Relational Databases ◽  
Query Language ◽  
General Purpose ◽  
Considerable Effort ◽  
Document Structure ◽  
Query By Example ◽  
Xml Documents

XML is a widely used general-purpose annotation formalism for creating custom markup languages. XML annotations give structure to plain documents to interpret their content. To extract information from XML documents XPath and XQuery languages can be used. However, the learning of these dialects requires a considerable effort. In this context, the traditional Query-By-Example methodology (for Relational Databases) can be an important contribution to leverage this learning process, freeing the user from knowing the specific query language details or even the document structure. This chapter describes how to apply the Query-By-Example concept in a Web-application for information retrieval from XML documents, the GuessXQ system. This engine is capable of deducing, from an example, the respective XQuery statement. The example consists of marking the desired components directly on a sample document, picked-up from a collection. After inferring the corresponding query, GuessXQ applies it to the collection to obtain the desired result.

Research Background

2013 ◽  
pp. 187-200
Author(s):  
Ibrahim Dweib ◽  
Joan Lu
Keyword(s):  
Data Storage ◽  
Relational Database ◽  
Query Languages ◽  
Xml Schema ◽  
Application Program Interface ◽  
Database Model ◽  
Xml Documents ◽  
Similarities And Differences ◽  
Schema Languages ◽  
Program Interface

In this chapter, the research background is discussed. This includes XML model, XML query languages, XML schema languages, XML Application Program Interface, XML documents types, XML data storage approaches, relational database model, and the similarities and differences between XML model and relational database model. Finally the chapter summary is given.

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