Technique for Transformation of Data From RDB to XML Then to RDF

This chapter will clearly show the need for better mapping techniques for Relational Database (RDB) all the way to Resource Description Framework (RDF). This includes coverage of each data model limitations and benefits for getting better results. Here, each form of data being transform has its own importance in the field of data science. As RDB is well known back end storage for information used to many kinds of applications; especially the web, desktop, remote, embedded, and network-based applications. Whereas, EXtensible Markup Language (XML) in the well-known standard for data for transferring among all computer related resources regardless of their type, shape, place, capability and capacity due to its form is in application understandable form. Finally, semantically enriched and simple of available in Semantic Web is RDF. This comes handy when with the use of linked data to get intelligent inference better and efficient. Multiple Algorithms are built to support this system experiments and proving its true nature of the study.

Download Full-text

Technique for Transformation of Data From RDB to XML Then to RDF

Information Retrieval and Management ◽

10.4018/978-1-5225-5191-1.ch046 ◽

2018 ◽

pp. 1078-1096

Author(s):

Kaleem Razzaq Malik ◽

Tauqir Ahmad

Keyword(s):

Semantic Web ◽

Relational Database ◽

Resource Description Framework ◽

Data Science ◽

True Nature ◽

Extensible Markup ◽

Description Framework ◽

Mapping Techniques ◽

Resource Description ◽

The Web

Download Full-text

Linked Open Statistical Metadata

Data Visualization and Statistical Literacy for Open and Big Data - Advances in Data Mining and Database Management ◽

10.4018/978-1-5225-2512-7.ch012 ◽

2017 ◽

pp. 297-320

Author(s):

Franck Cotton ◽

Daniel Gillman

Keyword(s):

Semantic Web ◽

Resource Description Framework ◽

Statistical Data ◽

Open Data ◽

Statistical Analyses ◽

Statistical Literacy ◽

Statistical Process ◽

Description Framework ◽

Resource Description ◽

The Web

Linked Open Statistical Metadata (LOSM) is Linked Open Data (LOD) applied to statistical metadata. LOD is a model for identifying, structuring, interlinking, and querying data published directly on the web. It builds on the standards of the semantic web defined by the W3C. LOD uses the Resource Description Framework (RDF), a simple data model expressing content as predicates linking resources between them or with literal properties. The simplicity of the model makes it able to represent any data, including metadata. We define statistical data as data produced through some statistical process or intended for statistical analyses, and statistical metadata as metadata describing statistical data. LOSM promotes discovery and the meaning and structure of statistical data in an automated way. Consequently, it helps with understanding and interpreting data and preventing inadequate or flawed visualizations for statistical data. This enhances statistical literacy and efforts at visualizing statistics.

Download Full-text

Relational Techniques for Storing and Querying RDF Data

Advanced Database Query Systems - Advances in Data Mining and Database Management ◽

10.4018/978-1-60960-475-2.ch011 ◽

2011 ◽

pp. 269-285

Author(s):

Sherif Sakr ◽

Ghazi Al-Naymat

Keyword(s):

Semantic Web ◽

Resource Description Framework ◽

Query Evaluation ◽

Evaluation Strategies ◽

Fundamental Challenge ◽

Rdf Data ◽

Description Framework ◽

Resource Description ◽

Flexible Model ◽

The Web

The Resource Description Framework (RDF) is a flexible model for representing information about resources in the Web. With the increasing amount of RDF data which is becoming available, efficient and scalable management of RDF data has become a fundamental challenge to achieve the Semantic Web vision. The RDF model has attracted attentions in the database community and many researchers have proposed different solutions to store and query RDF data efficiently. This chapter focuses on using relational query processors to store and query RDF data. It gives an overview of the different approaches and classifies them according to their storage and query evaluation strategies.

Download Full-text

Administering the Semantic Web

Techniques and Applications for Advanced Information Privacy and Security ◽

10.4018/978-1-60566-210-7.ch017 ◽

2011 ◽

pp. 262-277

Author(s):

Bhavani Thuraisingham ◽

Natasha Tsybulnik ◽

Ashraful Alam

Keyword(s):

Information Processing ◽

Semantic Web ◽

Data Quality ◽

Resource Description Framework ◽

Web Pages ◽

Markup Language ◽

Language Resource ◽

Extensible Markup ◽

Description Framework ◽

Resource Description

The Semantic Web is essentially a collection of technologies to support machine understandable Web pages as well as Information Interoperability. There has been much progress made on the Semantic Web including standards for eXtensible Markup Language, Resource Description Framework and Onotlogies. However, administration policies and techniques for enforcing them have received little attention. These policies include policies for security, privacy, data quality, integrity, trust and timely information processing. This chapter discusses administration policies for the Semantic Web as well as techniques for enforcing them. In particular, the authors will discuss an approach for ensuring confidentiality, privacy and trust for the Semantic Web. We will also discuss the inference and privacy problems within the context of administration policies.

Download Full-text

Administering the Semantic Web

Information Security and Ethics ◽

10.4018/978-1-59904-937-3.ch005 ◽

2008 ◽

pp. 72-88

Author(s):

Bhavani Thuraisingham ◽

Natasha Tsybulnik ◽

Ashraful Alam

Keyword(s):

Information Processing ◽

Semantic Web ◽

Data Quality ◽

Resource Description Framework ◽

Web Pages ◽

Markup Language ◽

Language Resource ◽

Extensible Markup ◽

Description Framework ◽

Resource Description

The Semantic Web is essentially a collection of technologies to support machine-understandable Web pages as well as Information Interoperability. There has been much progress made on the Semantic Web, including standards for eXtensible Markup Language, Resource Description Framework, and Ontologies. However, administration policies and techniques for enforcing them have received little attention. These policies include policies for security, privacy, data quality, integrity, trust, and timely information processing. This article discusses administration policies for the Semantic Web as well as techniques for enforcing them. In particular, we will discuss an approach for ensuring confidentiality, privacy, and trust for the Semantic Web. We will also discuss the inference and privacy problems within the context of administration policies.

Download Full-text

OWL

Encyclopedia of Information Science and Technology, Second Edition ◽

10.4018/978-1-60566-026-4.ch481 ◽

2011 ◽

pp. 3009-3017

Author(s):

Adélia Gouveia ◽

Jorge Cardoso

Keyword(s):

World Wide Web ◽

Semantic Web ◽

Particle Physics ◽

World Wide ◽

Visual Presentation ◽

Web Pages ◽

Markup Language ◽

Extensible Markup ◽

Description Framework ◽

The Web

The World Wide Web (WWW) emerged in 1989, developed by Tim Berners-Lee who proposed to build a system for sharing information among physicists of the CERN (Conseil Européen pour la Recherche Nucléaire), the world’s largest particle physics laboratory. Currently, the WWW is primarily composed of documents written in HTML (hyper text markup language), a language that is useful for visual presentation (Cardoso & Sheth, 2005). HTML is a set of “markup” symbols contained in a Web page intended for display on a Web browser. Most of the information on the Web is designed only for human consumption. Humans can read Web pages and understand them, but their inherent meaning is not shown in a way that allows their interpretation by computers (Cardoso & Sheth, 2006). Since the visual Web does not allow computers to understand the meaning of Web pages (Cardoso, 2007), the W3C (World Wide Web Consortium) started to work on a concept of the Semantic Web with the objective of developing approaches and solutions for data integration and interoperability purpose. The goal was to develop ways to allow computers to understand Web information. The aim of this chapter is to present the Web ontology language (OWL) which can be used to develop Semantic Web applications that understand information and data on the Web. This language was proposed by the W3C and was designed for publishing, sharing data and automating data understood by computers using ontologies. To fully comprehend OWL we need first to study its origin and the basic blocks of the language. Therefore, we will start by briefly introducing XML (extensible markup language), RDF (resource description framework), and RDF Schema (RDFS). These concepts are important since OWL is written in XML and is an extension of RDF and RDFS.

Download Full-text

Semantic E-Business Challenges and Directions

Encyclopedia of Networked and Virtual Organizations ◽

10.4018/978-1-59904-885-7.ch187 ◽

2011 ◽

pp. 1421-1428

Author(s):

Giorgos Laskaridis ◽

Konstantinos Markellos ◽

Penelope Markellou ◽

Angeliki Panayiotaki ◽

Athanasios Tsakalidis

Keyword(s):

Semantic Web ◽

World Wide ◽

Business Processes ◽

Semantic Knowledge ◽

Web Based ◽

The World ◽

Extensible Markup ◽

Description Framework ◽

Business Challenges ◽

Resource Description

The emergence of semantic Web opens up boundless new opportunities for e-business. According to Tim Berners-Lee, Hendler, and Lassila (2001), “the semantic Web is an extension of the current Web in which information is given well-defined meaning, better enabling computers and people to work in cooperation”. A more formal definition by W3C (2001) refers that, “the semantic Web is the representation of data on the World Wide Web. It is a collaborative effort led by W3C with participation from a large number of researchers and industrial partners. It is based on the resource description framework (RDF), which integrates a variety of applications using eXtensible Markup Language (XML) for syntax and uniform resource identifiers (URIs) for naming”. The capability of the semantic Web to add meaning to information, stored in such way that it can be searched and processed as well as recent advances in semantic Web-based technologies provide the mechanisms for semantic knowledge representation, exchange and collaboration of e-business processes and applications.

Download Full-text

RDF 1.1: Knowledge Representation and Data Integration Language for the Web

Symmetry ◽

10.3390/sym12010084 ◽

2020 ◽

Vol 12 (1) ◽

pp. 84 ◽

Cited By ~ 2

Author(s):

Dominik Tomaszuk ◽

David Hyland-Wood

Keyword(s):

Knowledge Representation ◽

Resource Description Framework ◽

Relational Databases ◽

Formal Definition ◽

Natural Languages ◽

Description Framework ◽

Generalized Knowledge ◽

Definition Of ◽

Resource Description ◽

The Web

Resource Description Framework (RDF) can seen as a solution in today’s landscape of knowledge representation research. An RDF language has symmetrical features because subjects and objects in triples can be interchangeably used. Moreover, the regularity and symmetry of the RDF language allow knowledge representation that is easily processed by machines, and because its structure is similar to natural languages, it is reasonably readable for people. RDF provides some useful features for generalized knowledge representation. Its distributed nature, due to its identifier grounding in IRIs, naturally scales to the size of the Web. However, its use is often hidden from view and is, therefore, one of the less well-known of the knowledge representation frameworks. Therefore, we summarise RDF v1.0 and v1.1 to broaden its audience within the knowledge representation community. This article reviews current approaches, tools, and applications for mapping from relational databases to RDF and from XML to RDF. We discuss RDF serializations, including formats with support for multiple graphs and we analyze RDF compression proposals. Finally, we present a summarized formal definition of RDF 1.1 that provides additional insights into the modeling of reification, blank nodes, and entailments.

Download Full-text

Schema-Based Mapping Approach for Data Transformation to Enrich Semantic Web

Wireless Communications and Mobile Computing ◽

10.1155/2021/8567894 ◽

2021 ◽

Vol 2021 ◽

pp. 1-15

Author(s):

Senthilselvan Natarajan ◽

Subramaniyaswamy Vairavasundaram ◽

Yuvaraja Teekaraman ◽

Ramya Kuppusamy ◽

Arun Radhakrishnan

Keyword(s):

Relational Database ◽

Resource Description Framework ◽

Data Retrieval ◽

Mapping Method ◽

Data Conversion ◽

Query Translation ◽

On Demand ◽

Conventional Methods ◽

Description Framework ◽

Resource Description

Modern web wants the data to be in Resource Description Framework (RDF) format, a machine-readable form that is easy to share and reuse data without human intervention. However, most of the information is still available in relational form. The existing conventional methods transform the data from RDB to RDF using instance-level mapping, which has not yielded the expected results because of poor mapping. Hence, in this paper, a novel schema-based RDB-RDF mapping method (relational database to Resource Description Framework) is proposed, which is an improvised version for transforming the relational database into the Resource Description Framework. It provides both data materialization and on-demand mapping. RDB-RDF reduces the data retrieval time for nonprimary key search by using schema-level mapping. The resultant mapped RDF graph presents the relational database in a conceptual schema and maintains the instance triples as data graph. This mechanism is known as data materialization, which suits well for the static dataset. To get the data in a dynamic environment, query translation (on-demand mapping) is best instead of whole data conversion. The proposed approach directly converts the SPARQL query into SQL query using the mapping descriptions available in the proposed system. The mapping description is the key component of this proposed system which is responsible for quick data retrieval and query translation. Join expression introduced in the proposed RDB-RDF mapping method efficiently handles all complex operations with primary and foreign keys. Experimental evaluation is done on the graphics designer database. It is observed from the result that the proposed schema-based RDB-RDF mapping method accomplishes more comprehensible mapping than conventional methods by dissolving structural and operational differences.

Download Full-text

Transitioning from XML to RDF: Considerations for an effective move towards Linked Data and the Semantic Web

Information Technology and Libraries ◽

10.6017/ital.v35i1.9182 ◽

2016 ◽

Vol 35 (1) ◽

pp. 51 ◽

Cited By ~ 1

Author(s):

Juliet L. Hardesty

Keyword(s):

Semantic Web ◽

Linked Data ◽

Academic Library ◽

Data Sets ◽

Markup Language ◽

Digital Repository ◽

Extensible Markup ◽

Description Framework ◽

Meaningful Relationships ◽

Resource Description

Metadata, particularly within the academic library setting, is often expressed in eXtensible Markup Language (XML) and managed with XML tools, technologies, and workflows. Managing a library’s metadata currently takes on a greater level of complexity as libraries are increasingly adopting the Resource Description Framework (RDF). Semantic Web initiatives are surfacing in the library context with experiments in publishing metadata as Linked Data sets and also with development efforts such as BIBFRAME and the Fedora 4 Digital Repository incorporating RDF. Use cases show that transitions into RDF are occurring in both XML standards and in libraries with metadata encoded in XML. It is vital to understand that transitioning from XML to RDF requires a shift in perspective from replicating structures in XML to defining meaningful relationships in RDF. Establishing coordination and communication among these efforts will help as more libraries move to use RDF, produce Linked Data, and approach the Semantic Web.

Download Full-text