Survey of directly mapping SQL databases to the Semantic Web

2011 ◽  
Vol 26 (4) ◽  
pp. 445-486 ◽  
Author(s):  
Juan F. Sequeda ◽  
Syed Hamid Tirmizi ◽  
Oscar Corcho ◽  
Daniel P. Miranker
Keyword(s):  
Semantic Web ◽  
Resource Description Framework ◽  
Information Sources ◽  
The Internet ◽  
Web Ontology Language ◽  
Ontology Language ◽  
Description Framework ◽  
Resource Description ◽  
Semantic Properties ◽  
Rdf Schema

AbstractThe Semantic Web anticipates integrated access to a large number of information sources on the Internet represented as Resource Description Framework (RDF). Given the large number of websites that are backed by SQL databases, methods that automate the translation of those databases to RDF are crucial. One approach, taken by a number of researchers, is to directly map the SQL schema to an equivalent Web Ontology Language (OWL) or RDF Schema representation, which in turn, implies an RDF representation for the relational data. This paper reviews this research, and derives a consolidated, overarching set of translation rules expressible as a stratified Datalog program. We present all the possible key combinations in an SQL schema and consider their implied semantic properties. We review the approaches and characterize them with respect to the scope of their coverage of SQL constructs.

scholarly journals Semantic Web in the expansion of E Commerce

2019 ◽  
Vol 8 (3) ◽  
pp. 3820-3827
Keyword(s):  
Semantic Web ◽  
Resource Description Framework ◽  
Search Engines ◽  
Web Ontology Language ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Semantic Enrichment ◽  
Ontology Language ◽  
Description Framework ◽  
Resource Description

This study focuses on the enhancing the potential of the e-commerce websites with various Semantic web technologies. The involvement of semantic enrichment gives more meaning to the data and makes content more easily discoverable by both search engines and users. Daily thousands of people try searching for a product they are willing to buy and due to the system inefficiency, customers waste a lot of their precious time and resources and also there are a lot of problems with the current e-commerce systems. So, semantic web has certain technologies/languages specifically established for data, i.e. RDF (Resource description framework), OWL (Web ontology language) and XML, etc. which can help overcome the problems and accelerate the business to a higher level where e-commerce websites will be playing an important role.

scholarly journals Logical Foundations of RDF(S) with Datatypes

2010 ◽  
Vol 38 ◽  
pp. 535-568 ◽  
Author(s):  
J. De Bruijn ◽  
S. Heymans
Keyword(s):  
Semantic Web ◽  
Lower Bounds ◽  
Resource Description Framework ◽  
Description Logic ◽  
Upper Bounds ◽  
Logical Foundations ◽  
Ontology Language ◽  
Description Framework ◽  
Resource Description ◽  
Rdf Schema

The Resource Description Framework (RDF) is a Semantic Web standard that provides a data language, simply called RDF, as well as a lightweight ontology language, called RDF Schema. We investigate embeddings of RDF in logic and show how standard logic programming and description logic technology can be used for reasoning with RDF. We subsequently consider extensions of RDF with datatype support, considering D entailment, defined in the RDF semantics specification, and D* entailment, a semantic weakening of D entailment, introduced by ter Horst. We use the embeddings and properties of the logics to establish novel upper bounds for the complexity of deciding entailment. We subsequently establish two novel lower bounds, establishing that RDFS entailment is PTime-complete and that simple-D entailment is coNP-hard, when considering arbitrary datatypes, both in the size of the entailing graph. The results indicate that RDFS may not be as lightweight as one may expect.

scholarly journals Sistem Berbasis Pengetahuan Tumbuhan Obat Pusat Studi Biofarmaka

2019 ◽  
Vol 4 (1) ◽  
pp. 17-27
Author(s):  
Aini Fazriani ◽  
Wisnu Ananta Kusuma ◽  
Irmanida Batubara
Keyword(s):  
Life Cycle ◽  
Resource Description Framework ◽  
Web Ontology Language ◽  
Ontology Language ◽  
Ontology Building ◽  
Description Framework ◽  
Building Life Cycle ◽  
Resource Description

Jamu terdiri atas berbagai macam tumbuhan obat yang diolah. Tumbuhan obat memiliki kandungan senyawa metabolit sekunder yang berperan sebagai khasiat. Pengetahuan tumbuhan obat beserta senyawanya perlu dikembangkan lagi menjadi pengetahuan eksplisit yang lebih spesifik dan mudah dimengerti sehingga berguna untuk masyarakat. Maka dari itu perlu mengembangkan sistem untuk digunakan oleh masyarakat sehingga pengobatan dengan tanaman obat lebih populer di kalangan masyarakat luas. Penelitian yang dilakukan mengenai manajemen pengetahuan berbasis ontologi terkait dengan tumbuhan obat dan senyawa. Penelitian ini menggunakan pendekatan proses manajemen pengetahuan model SECI, selain itu pengembangan ontologi menggunakan metode Ontology building life cycle, sedangkan bahasa representasi yang digunakan adalah Resource Description Framework (RDF) dan Web Ontology Language (OWL) dengan toolsProtégé5.0. Pengembangan model ontologi dengan bahasa representasi RDF/OWL dapat menghasilkan pengetahuan dengan melakukan query menggunakan SPARQL. Hasil query tersebut dapat digunakan untuk diimplementasikan pada mobile.

Sistem Berbasis Pengetahuan Tumbuhan Obat Pusat Studi Biofarmaka

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Aini Fazriani ◽  
Wisnu Ananta Kusuma ◽  
Irmanida Batubara
Keyword(s):  
Life Cycle ◽  
Resource Description Framework ◽  
Web Ontology Language ◽  
Ontology Language ◽  
Ontology Building ◽  
Description Framework ◽  
Building Life Cycle ◽  
Resource Description

Jamu terdiri atas berbagai macam tumbuhan obat yang diolah. Tumbuhan obat memiliki kandungan senyawa metabolit sekunder yang berperan sebagai  khasiat. Pengetahuan tumbuhan obat beserta senyawanya perlu dikembangkan lagi menjadi pengetahuan eksplisit yang lebih spesifik dan mudah dimengerti sehingga berguna untuk masyarakat.   Maka dari itu perlu  mengembangkan sistem untuk digunakan oleh masyarakat sehingga pengobatan dengan tanaman obat lebih populer di kalangan masyarakat luas. Penelitian yang  dilakukan mengenai manajemen pengetahuan berbasis ontologi terkait dengan tumbuhan obat dan senyawa. Penelitian ini menggunakan pendekatan proses manajemen pengetahuan model SECI, selain itu pengembangan ontologi menggunakan metode Ontology building life cycle, sedangkan bahasa representasi yang digunakan adalah Resource Description Framework  (RDF) dan Web Ontology Language (OWL) dengan tools Protege 5.0. Pengembangan model ontologi dengan bahasa representasi RDF/OWL dapat menghasilkan pengetahuan dengan melakukan query menggunakan SPARQL. Hasil query tersebut dapat digunakan untuk diimplementasikan pada mobile.

scholarly journals Pengembangan Sistem Ontologi untuk Morfologi Tumbuhan Obat

2016 ◽  
Vol 3 (2) ◽  
pp. 84 ◽  
Author(s):  
Hani Zulfia Zahro ◽  
Yeni Herdiyeni ◽  
Irman Hermadi
Keyword(s):  
Resource Description Framework ◽  
Query Language ◽  
Web Ontology Language ◽  
Ontology Language ◽  
Description Framework ◽  
Resource Description

Penelitian ini mengusulkan tentang desain baru dari ontologi untuk tanaman obat Indonesia berdasarkan konsep morfologi. Morfologi adalah studi yang mempelajari tentang karakteristik tumbuhan. Dalam penelitian ini menggunakan morfologi sebagai konsep pengetahuan. Ontologi merupakan model pengetahuan yang mendefinisikan hubungan dan klasifikasi dari beberapa konsep dalam domain tertentu. <em>Resource description framework</em> (RDF) dan <em>web ontology language</em> (OWL) digunakan dalam merepresentasikan ontologi. SPARQL protocol and <em>RDF query language</em> (SPARQL) digunakan untuk <em>query</em> data. Protégé 4.3 digunakan untuk memodelkan ontologi tanaman obat. Hasil dari pemodelan ontologi tumbuhan obat dapat diterapkan ke sistem semantik web tanaman obat Indonesia.<br /><br />Kata kunci: morfologi, ontologi, tumbuhan obat

scholarly journals Petri nets on the semantic web guidelines and infrastructure

2004 ◽  
Vol 1 (2) ◽  
pp. 127-151 ◽  
Author(s):  
Dragan Gasevic
Keyword(s):  
Semantic Web ◽  
Petri Net ◽  
Ontology Language ◽  
Uml Profiles ◽  
Community Effort ◽  
Model Sharing ◽  
Petri Net Markup Language ◽  
Description Framework ◽  
Definition Of ◽  
Resource Description

This paper gives the Petri net ontology as the most important element in providing Petri net support for the Semantic Web. Available Petri net formal descriptions are: metamodels, UML profiles, ontologies and syntax. Metamodels are useful, but their main purpose is for Petri net tools. Although the current Petri-net community effort Petri Net Markup Language (PNML) is XML-based, it lacks a precise definition of semantics. Existing Petri net ontologies are partial solutions specialized for a specific problem. In order to show current Petri net model sharing features we use P3 tool that uses PNML/XSLT-based approach for model sharing. This paper suggests developing the Petri net ontology to represent semantics appropriately. This Petri net ontology is described using UML, Resource Description Framework (Schema) RDF(S) and the Web Ontology Language-OWL.

Linked Open Statistical Metadata

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.

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

2017 ◽  
pp. 70-91 ◽  
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.

Data Confidentiality on the Semantic Web

2008 ◽  
pp. 3309-3320
Author(s):  
Csilla Farkas
Keyword(s):  
Semantic Web ◽  
Formal Semantics ◽  
Future Research ◽  
Semantic Web Technologies ◽  
Inference Problem ◽  
Web Technologies ◽  
Ontology Language ◽  
Future Research Directions ◽  
Description Framework ◽  
Resource Description

This chapter investigates the threat of unwanted Semantic Web inferences. We survey the current efforts to detect and remove unwanted inferences, identify research gaps, and recommend future research directions. We begin with a brief overview of Semantic Web technologies and reasoning methods, followed by a description of the inference problem in traditional databases. In the context of the Semantic Web, we study two types of inferences: (1) entailments defined by the formal semantics of the Resource Description Framework (RDF) and the RDF Schema (RDFS) and (2) inferences supported by semantic languages like the Web Ontology Language (OWL). We compare the Semantic Web inferences to the inferences studied in traditional databases. We show that the inference problem exists on the Semantic Web and that existing security methods do not fully prevent indirect data disclosure via inference channels.

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