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

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 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 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 An E-Commerce Platform for Industrialized Construction Procurement Based on BIM and Linked Data

2018 ◽  
Vol 10 (8) ◽  
pp. 2613
Author(s):  
Dandan He ◽  
Zhongfu Li ◽  
Chunlin Wu ◽  
Xin Ning
Keyword(s):  
Data Integration ◽  
Construction Industry ◽  
Resource Description Framework ◽  
Linked Data ◽  
Query Language ◽  
Rapid Development ◽  
Data Sources ◽  
Product Data ◽  
Description Framework ◽  
Resource Description

Industrialized construction has raised the requirements of procurement methods used in the construction industry. The rapid development of e-commerce offers efficient and effective solutions, however the large number of participants in the construction industry means that the data involved are complex, and problems arise related to volume, heterogeneity, and fragmentation. Thus, the sector lags behind others in the adoption of e-commerce. In particular, data integration has become a barrier preventing further development. Traditional e-commerce platform, which considered data integration for common product data, cannot meet the requirements of construction product data integration. This study aimed to build an information-integrated e-commerce platform for industrialized construction procurement (ICP) to overcome some of the shortcomings existing platforms. We proposed a platform based on Building Information Modelling (BIM) and linked data, taking an innovative approach to data integration. It uses industrialized construction technology to support product standardization, BIM to support procurement process, and linked data to connect different data sources. The platform was validated using a case study. With the development of an e-commerce ontology, industrialized construction component information was extracted from BIM models and converted to Resource Description Framework (RDF) format. Related information from different data sources was also converted to RDF format, and Simple Protocol and Resource Description Framework Query Language (SPARQL) queries were implemented. The platform provides a solution for the development of e-commerce platform in the construction industry.

scholarly journals PRIOR ONTOLOGY SELECTION AND QUERY TRANSLATION FOR INFORMATION SEARCH

2017 ◽  
Vol 10 (13) ◽  
pp. 499
Author(s):  
Poornima N ◽  
Shivam Agrawal ◽  
Shivam Agrawal ◽  
Saleena B ◽  
Saleena B
Keyword(s):  
Information Retrieval ◽  
Resource Description Framework ◽  
Information Search ◽  
Query Language ◽  
Retrieval Process ◽  
Query Translation ◽  
User Intention ◽  
Description Framework ◽  
Ontology Selection ◽  
Resource Description

Objective: Most of the current search engines follow informal keyword based search. Finding the user intention and improving the relevancy of results are the major issues faced by the current traditional keyword based search. Targeting to solve the problems of traditional search and to boost the retrieval process, a framework for semantic based information retrieval is planned. Methods: Social and wine ontologies are used to find the user intention and retrieving it. User’s natural language queries are translated into SPARQL (SPARQL Protocol and Resource Description Framework query language) query for finding related items from those ontologies.Results: The proposed method makes a significant improvement over traditional search in terms of some searches required for searching a particular number of pages using performance graph.Conclusion: Semantic based search can understand the user intention and gives better results than traditional search.

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

2016 ◽  
Vol 31 (4) ◽  
pp. 391-413 ◽  
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.

scholarly journals AN APPROACH TO EXTENDING QUERY SENTENCE FOR SEMANTIC ORIENTED SEARCH ON KNOWLEDGE GRAPH

2021 ◽  
Vol 50 (02) ◽  
Author(s):  
TẠ DUY CÔNG CHIẾN
Keyword(s):  
Relational Databases ◽  
Question Answering ◽  
Query Language ◽  
Knowledge Graph ◽  
Web Information Retrieval ◽  
Ontology Language ◽  
Description Framework ◽  
The Relationship ◽  
Resource Description ◽  
Terminological Confusion

There are many applications related to semantic web, information retrieval, information extraction, and question answering applying ontologies in recent years. To avoid the conceptual and terminological confusion, an ontology is built as a taxonomy ontology which identifies and distinguishes concepts as well as terminology. It accomplishes this by specifying a set of generic concepts that characterizes the domain as well as their definitions and interrelationships. There are some methods to represent ontologies, such as Resource Description Framework (RDF), Web Ontology Language (OWL), databases etc. depending on the characteristic of data. RDF, OWL usually is used the cases when data structure is objects which the relationship among the objects is simple. But if the relationship among the objects is more complex, using databases for storing ontologies is an approach to be better. However, using relational databases do not sufficiently support the semantic orientated search by Structured Query Language (SQL) and the searching speed is slow. Therefore, this paper introduces an approach to extending query sentences for semantic oriented search on knowledge graph.

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.

Sign in / Sign up

Export Citation Format

Share Document