N3Logic: A logical framework for the World Wide Web

AbstractThe Semantic Web drives toward the use of the Web for interacting with logically interconnected data. Through knowledge models such as Resource Description Framework (RDF), the Semantic Web provides a unifying representation of richly structured data. Adding logic to the Web implies the use of rules to make inferences, choose courses of action, and answer questions. This logic must be powerful enough to describe complex properties of objects but not so powerful that agents can be tricked by being asked to consider a paradox. The Web has several characteristics that can lead to problems when existing logics are used, in particular, the inconsistencies that inevitably arise due to the openness of the Web, where anyone can assert anything. N3Logic is a logic that allows rules to be expressed in a Web environment. It extends RDF with syntax for nested graphs and quantified variables and with predicates for implication and accessing resources on the Web, and functions including cryptographic, string, math. The main goal of N3Logic is to be a minimal extension to the RDF data model such that the same language can be used for logic and data. In this paper, we describe N3Logic and illustrate through examples why it is an appropriate logic for the Web.

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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.

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Can Bibliographic Data be Put Directly onto the Semantic Web?

Information Technology and Libraries ◽

10.6017/ital.v28i2.3175 ◽

2009 ◽

Vol 28 (2) ◽

pp. 55 ◽

Cited By ~ 5

Author(s):

Martha M. Yee

Keyword(s):

Semantic Web ◽

Resource Description Framework ◽

Data Model ◽

Community Resource ◽

Work In Progress ◽

Library Community ◽

Bibliographic Data ◽

Rdf Data ◽

Description Framework ◽

Resource Description

<span>This paper is a think piece about the possible future of bibliographic control; it provides a brief introduction to the Semantic Web and defines related terms, and it discusses granularity and structure issues and the lack of standards for the efficient display and indexing of bibliographic data. It is also a report on a work in progress—an experiment in building a Resource Description Framework (RDF) model of more FRBRized cataloging rules than those about to be introduced to the library community (Resource Description and Access) and in creating an RDF data model for the rules. I am now in the process of trying to model my cataloging rules in the form of an RDF model, which can also be inspected at </span><a href="http://myee.bol.ucla.edu/">http://myee.bol.ucla.edu/</a><span>. In the process of doing this, I have discovered a number of areas in which I am not sure that RDF is sophisticated enough yet to deal with our data. This article is an attempt to identify some of those areas and explore whether or not the problems I have encountered are soluble—in other words, whether or not our data might be able to live on the Semantic Web. In this paper, I am focusing on raising the questions about the suitability of RDF to our data that have come up in the course of my work.</span>

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Towards Massive RDF Storage in NoSQL Databases

Advances in Data Mining and Database Management - Emerging Technologies and Applications in Data Processing and Management ◽

10.4018/978-1-5225-8446-9.ch013 ◽

2019 ◽

pp. 263-284 ◽

Cited By ~ 2

Author(s):

Zongmin Ma ◽

Li Yan

Keyword(s):

Data Storage ◽

Large Scale ◽

Future Research ◽

Nosql Databases ◽

Current State ◽

Data Store ◽

Rdf Data ◽

Description Framework ◽

Resource Description ◽

The Web

The resource description framework (RDF) is a model for representing information resources on the web. With the widespread acceptance of RDF as the de-facto standard recommended by W3C (World Wide Web Consortium) for the representation and exchange of information on the web, a huge amount of RDF data is being proliferated and becoming available. So, RDF data management is of increasing importance and has attracted attention in the database community as well as the Semantic Web community. Currently, much work has been devoted to propose different solutions to store large-scale RDF data efficiently. In order to manage massive RDF data, NoSQL (not only SQL) databases have been used for scalable RDF data store. This chapter focuses on using various NoSQL databases to store massive RDF data. An up-to-date overview of the current state of the art in RDF data storage in NoSQL databases is provided. The chapter aims at suggestions for future research.

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A Review of RDF Storage in NoSQL Databases

Advances in Systems Analysis, Software Engineering, and High Performance Computing - Managing Big Data in Cloud Computing Environments ◽

10.4018/978-1-4666-9834-5.ch009 ◽

2016 ◽

pp. 210-229 ◽

Cited By ~ 2

Author(s):

Zongmin Ma ◽

Li Yan

Keyword(s):

Data Storage ◽

Large Scale ◽

Future Research ◽

Nosql Databases ◽

Current State ◽

Data Store ◽

Rdf Data ◽

Description Framework ◽

Resource Description ◽

The Web

The Resource Description Framework (RDF) is a model for representing information resources on the Web. With the widespread acceptance of RDF as the de-facto standard recommended by W3C (World Wide Web Consortium) for the representation and exchange of information on the Web, a huge amount of RDF data is being proliferated and becoming available. So RDF data management is of increasing importance, and has attracted attentions in the database community as well as the Semantic Web community. Currently much work has been devoted to propose different solutions to store large-scale RDF data efficiently. In order to manage massive RDF data, NoSQL (“not only SQL”) databases have been used for scalable RDF data store. This chapter focuses on using various NoSQL databases to store massive RDF data. An up-to-date overview of the current state of the art in RDF data storage in NoSQL databases is provided. The chapter aims at suggestions for future research.

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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.

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

Web Semantics for Textual and Visual Information Retrieval - Advances in Data Mining and Database Management ◽

10.4018/978-1-5225-2483-0.ch004 ◽

2017 ◽

pp. 70-91 ◽

Cited By ~ 1

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

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.

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Analysis of RDF Syntaxes for Semantic Web Development

Applied Computer Systems ◽

10.1515/acss-2015-0017 ◽

2015 ◽

Vol 18 (1) ◽

pp. 33-42 ◽

Cited By ~ 1

Author(s):

Yevgeny Gryaznov ◽

Pavel Rusakov

Keyword(s):

Semantic Web ◽

Directed Graph ◽

Resource Description Framework ◽

Formal Model ◽

Information Representation ◽

Web Development ◽

Rdf Data ◽

Description Framework ◽

Rdf Graphs ◽

Resource Description

Abstract In this paper authors perform a research on possibilities of RDF (Resource Description Framework) syntaxes usage for information representation in Semantic Web. It is described why pure XML cannot be effectively used for this purpose, and how RDF framework solves this problem. Information is being represented in a form of a directed graph. RDF is only an abstract formal model for information representation and side tools are required in order to write down that information. Such tools are RDF syntaxes – concrete text or binary formats, which prescribe rules for RDF data serialization. Text-based RDF syntaxes can be developed on the existing format basis (XML, JSON) or can be an RDF-specific – designed from scratch to serve the only purpose – to serialize RDF graphs. Authors briefly describe some of the RDF syntaxes (both XML and non-XML) and compare them in order to identify strengths and weaknesses of each version. Serialization and deserialization speed tests using Jena library are made. The results from both analytical and experimental parts of this research are used to develop the recommendations for RDF syntaxes usage and to design a RDF/XML syntax subset, which is intended to simplify the development and raise compatibility of information serialized with this RDF syntax.

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A Review of RDF Storage in NoSQL Databases

Big Data ◽

10.4018/978-1-4666-9840-6.ch005 ◽

2016 ◽

pp. 85-104

Author(s):

Zongmin Ma ◽

Li Yan

Keyword(s):

Data Storage ◽

Large Scale ◽

Future Research ◽

Nosql Databases ◽

Current State ◽

Data Store ◽

Rdf Data ◽

Description Framework ◽

Resource Description ◽

The Web

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Storing massive Resource Description Framework (RDF) data: a survey

The Knowledge Engineering Review ◽

10.1017/s0269888916000217 ◽

2016 ◽

Vol 31 (4) ◽

pp. 391-413 ◽

Cited By ~ 21

Author(s):

Zongmin Ma ◽

Miriam A. M. Capretz ◽

Li Yan

Keyword(s):

Data Storage ◽

Resource Description Framework ◽

Relational Databases ◽

Query Language ◽

Current State ◽

Rdf Data ◽

Description Framework ◽

Resource Description ◽

Flexible Model ◽

The Web

AbstractThe Resource Description Framework (RDF) is a flexible model for representing information about resources on the Web. As a W3C (World Wide Web Consortium) Recommendation, RDF has rapidly gained popularity. With the widespread acceptance of RDF on the Web and in the enterprise, a huge amount of RDF data is being proliferated and becoming available. Efficient and scalable management of RDF data is therefore of increasing importance. RDF data management has attracted attention in the database and Semantic Web communities. Much work has been devoted to proposing different solutions to store RDF data efficiently. This paper focusses on using relational databases and NoSQL (for ‘not only SQL (Structured Query Language)’) databases to store massive RDF data. A full up-to-date overview of the current state of the art in RDF data storage is provided in the paper.

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A Query Search Technique for Semantic Web Based on The Dynamic Distribution of Backjumping Method

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.f8223.088619 ◽

2019 ◽

Vol 8 (6) ◽

pp. 899-904

Keyword(s):

Semantic Web ◽

Fuzzy Graph ◽

Search Technique ◽

Description Language ◽

Web Based ◽

Dynamic Distribution ◽

Rdf Data ◽

Description Framework ◽

Matching Techniques ◽

Resource Description

In the resource description language of the semantic web, vagueness of Resource Description Framework (RDF) data is playing an important role. The effective querying of the RDF data is increasing importance in semantic web. In this research, the Dynamic Distribution of BackJumping (DDBJ) algorithm is proposed in the fuzzy graph due to the ability of the algorithm to maintain its autonomy in the data. The fuzzy graph is generated from the triplets in the RDF and the vertices, edges are extracted from pattern matching techniques. The vertices and edges are applied in the DDBJ to suggest the query in the semantic web. To analyze the effectiveness of the proposed DDBJ, the two real datasets are used. The proposed DDBJ method has the f-measure of 59 %, while the state-of-art method such as backtracking has achieved 56 %. The result shows that the DDBJ method has the higher performance than existing method in query processing.

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