Integrating Relational Databases with the Semantic Web: A Reflection

2017 ◽  
pp. 68-120 ◽  
Author(s):  
Juan F. Sequeda
Keyword(s):  
Semantic Web ◽  
Relational Databases

Organizing Multimedia Objects by Using Class Algebra

2005 ◽  
pp. 2243-2247
Author(s):  
Daniel J. Buehrer
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Relational Databases ◽  
Service Oriented Architectures ◽  
Web Based ◽  
Xml Documents ◽  
Object Relational ◽  
Service Oriented ◽  
Persistent Data ◽  
Hypertext Markup Language

Web-based applications (Web services and service-oriented architectures) can be run via a Web-based browser. There are several approaches to writing such Web-based applications. A lightweight approach is suitable for hand-held devices. In this approach, a Java servlet or a JSP page (Java 2 Platform, JSP), or an ASP application (Microsoft .NET, ASP) generates HTML (Hypertext Markup Language), XHTML, or XML documents (W3C Semantic Web Activity, XHTML, XML) to be displayed by the browser. Most browsers use an anchored URLs extension (e.g., .doc, .jpg, .xml, etc.) to choose an appropriate plug-in to display the URL when it is clicked. Besides displaying text and multimedia, Web servers and/or browsers can also execute Java applets or scripting languages to read and/or change persistent data. Previously, about 98% of these data were stored in relational or object-relational databases. However, recently more of these data are being stored in XML-based documents. Often these documents have an associated “schema” declaring the nesting of tags and the types of primitive values, or an “ontology” (Everett et al., 2002, Hunter, 2003) declaring classes, attributes, and relations that are used in the document.

scholarly journals ONTOGRATE: TOWARDS AUTOMATIC INTEGRATION FOR RELATIONAL DATABASES AND THE SEMANTIC WEB THROUGH AN ONTOLOGY-BASED FRAMEWORK

2010 ◽  
Vol 04 (01) ◽  
pp. 123-151 ◽  
Author(s):  
DEJING DOU ◽  
HAN QIN ◽  
PAEA LEPENDU
Keyword(s):  
Semantic Web ◽  
Relational Databases ◽  
Relational Data ◽  
Heterogeneous Databases ◽  
Query Translation ◽  
Automatic Integration ◽  
Mapping System ◽  
Research Problems ◽  
Comprehensive Framework ◽  
Logic Inference

Integrating existing relational databases with ontology-based systems is among the important research problems for the Semantic Web. We have designed a comprehensive framework called OntoGrate which combines a highly automatic mapping system, a logic inference engine, and several syntax wrappers that inter-operate with consistent semantics to answer ontology-based queries using the data from heterogeneous databases. There are several major contributions of our OntoGrate research: (i) we designed an ontology-based framework that provides a unified semantics for mapping discovery and query translation by transforming database schemas to Semantic Web ontologies; (ii) we developed a highly automatic ontology mapping system which leverages object reconciliation and multi-relational data mining techniques; (iii) we developed an inference-based query translation algorithm and several syntax wrappers which can translate queries and answers between relational databases and the Semantic Web. The testing results of our implemented OntoGrate system in different domains show that the large amount of data in relational databases can be directly utilized for answering Semantic Web queries rather than first converting all relational data into RDF or OWL.

UPDATE-ENABLED TRIPLIFICATION OF RELATIONAL DATA INTO VIRTUAL RDF STORES

2010 ◽  
Vol 04 (04) ◽  
pp. 423-451 ◽  
Author(s):  
SUNITHA RAMANUJAM ◽  
VAIBHAV KHADILKAR ◽  
LATIFUR KHAN ◽  
MURAT KANTARCIOGLU ◽  
BHAVANI THURAISINGHAM ◽  
...  
Keyword(s):  
Semantic Web ◽  
Relational Database ◽  
Relational Databases ◽  
Heterogeneous Data ◽  
Data Sources ◽  
Relational Data ◽  
Semantic Web Technologies ◽  
Heterogeneous Data Sources ◽  
Description Framework ◽  
Almost All

The current buzzword in the Internet community is the Semantic Web initiative proposed by the W3C to yield a Web that is more flexible and self-adapting. However, for the Semantic Web initiative to become a reality, heterogeneous data sources need to be integrated in order to enable access to them in a homogeneous manner. Since a vast majority of data currently resides in relational databases, integrating relational data sources with semantic web technologies is at the top of the list of activities required to realize the semantic web vision. Several efforts exist that publish relational data as Resource Description Framework (RDF) triples; however almost all current work in this arena is uni-directional, presenting data from an underlying relational database into a corresponding virtual RDF store in a read-only manner. An enhancement over previous relational-to-RDF bridging work in the form of bi-directionality support is presented in this paper. The bi-directional bridge proposed here allows RDF data updates specified as triples to be propagated back into the underlying relational database as tuples. Towards this end, we present various algorithms to translate the triples to be updated/inserted/deleted into equivalent relational attributes/tuples whenever possible. Particular emphasis is laid, in this paper, on the translation and update propagation process for triples containing blank nodes and reification nodes, and a platform enhanced with our algorithms, called D2RQ++, through which bi-directional translation can be achieved, is presented.

scholarly journals RDB2OWL: AN IMPROVED METHOD FOR CONVERTING RELATIONAL DATABASES INTO OWL

2017 ◽  
Vol 7 (2) ◽  
pp. 129
Author(s):  
Phạm Thị Thu Thúy
Keyword(s):  
Semantic Web ◽  
Relational Databases ◽  
Web Ontology Language ◽  
Improved Method ◽  
Ontology Language ◽  
Owl Ontology

Một trong những lợi thế của Semantic Web là để mô tả dữ liệu với một ý nghĩa rõ ràng và liên kết giữa các dữ liệu bằng cách sử dụng ngôn ngữ OWL (Web Ontology Language). Ngày nay hầu hết các dữ liệu được lưu trữ trong cơ sở dữ liệu quan hệ. Để tận dụng lại các dữ liệu này, cần thiết phải có phương pháp chuyển dữ liệu lưu trữ trong cơ sở dữ liệu quan hệ vào định dạng của OWL Ontology. Một số phương pháp đã được đề xuất, tuy nhiên, hầu hết các quy tắc chuyển đổi đã không được hoàn chỉnh. Bài báo này đề xuất một số quy tắc cải thiện trong việc chuyển đổi cơ sở dữ liệu quan hệ sang OWL Ontology. Ngoài ra, tất cả các bước chuyển đổi trong thuật toán RDB2OWL được thực hiện tự động mà không cần bất kỳ sự can thiệp của người dùng.

Nested Optional Join for Efficient Evaluation of SPARQL Nested Optional Graph Patterns

2010 ◽  
pp. 281-308
Author(s):  
Artem Chebotko ◽  
Shiyong Lu
Keyword(s):  
Semantic Web ◽  
Relational Databases ◽  
Real Life ◽  
Query Languages ◽  
Efficient Algorithms ◽  
Relational Algebra ◽  
Nested Loops ◽  
Web Data Management ◽  
Rdf Data ◽  
Rdf Query Languages

Relational technology has shown to be very useful for scalable Semantic Web data management. Numerous researchers have proposed to use RDBMSs to store and query voluminous RDF data using SQL and RDF query languages. This chapter studies how RDF queries with the so called well-designed graph patterns and nested optional patterns can be efficiently evaluated in an RDBMS. The authors propose to extend relational algebra with a novel relational operator, nested optional join (NOJ), that is more efficient than left outer join in processing nested optional patterns of well-designed graph patterns. They design three efficient algorithms to implement the new operator in relational databases: (1) nested-loops NOJ algorithm, NL-NOJ, (2) sort-merge NOJ algorithm, SM-NOJ, and (3) simple hash NOJ algorithm, SH-NOJ. Using a real life RDF dataset, the authors demonstrate the efficiency of their algorithms by comparing them with the corresponding left outer join implementations and explore the effect of join selectivity on the performance of these algorithms.

A Fuzzy Ontology Generation Framework from Fuzzy Relational Databases

2010 ◽  
pp. 221-236
Author(s):  
Z.M. Ma ◽  
Yanhui Lv ◽  
Li Yan
Keyword(s):  
Semantic Web ◽  
Relational Databases ◽  
Heterogeneous Systems ◽  
Knowledge Bases ◽  
Original Structure ◽  
Fuzzy Ontology ◽  
Ontology Generation ◽  
Ontology Structure ◽  
Rdf Data ◽  
Exchange Data

Ontology is an important part of the W3C standards for the Semantic Web used to specify standard conceptual vocabularies to exchange data among systems, provide reusable knowledge bases, and facilitate interoperability across multiple heterogeneous systems and databases. However, current ontology is not sufficient for handling vague information that is commonly found in many application domains. A feasible solution is to import the fuzzy ability to extend the classical ontology. In this article, we propose a fuzzy ontology generation framework from the fuzzy relational databases, in which the fuzzy ontology consists of fuzzy ontology structure and instances. We simultaneously consider the schema and instances of the fuzzy relational databases, and respectively transform them to fuzzy ontology structure and fuzzy RDF data model. This can ensure the integrality of the original structure as well as the completeness and consistency of the original instances in the fuzzy relational databases.

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