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Background: Smartphones are a fundamental require for everybody since smartphones can offer assistance someone's work through different highlights and certain innovation contained within the smartphone. Some people's need for information about smartphones makes people confused in choosing smartphone products because there are many smartphone brands available on the market, as a result, many people still buy smartphones that do not suit their needs and preferences. That is why ontology-based knowledge representation is becoming increasingly important in the field of smartphone technology to improve data organization, data retrieval, and interoperability. Objective: This research aims to develop a smartphone ontology using the Apache Jena Fuseki server which functions as a data collection tool and facilitates knowledge management about smartphones. Methods: This ontology was built using the methontology method, namely an ontology development method that is superior in providing a detailed description of each required activity. This smartphone ontology was developed using the Protégé 5.5.0 application which consists of 4 classes, 9 object properties, 15 data properties, and 92 individuals. Results: The research results show that the ontology built can help users search for smartphones that suit their criteria and needs. This research also succeeded in developing an android and semantic web-based application that allows users to search for smartphones more easily and efficiently, strengthening the benefits of the developed ontology in supporting smartphone purchasing decisions. Conclusion: The contribution of this research is to help customers, by providing recommendation the smartphone that best meets the requirements or best fits the given knowledge representation.

Linked open data (LOD) is an essential component in semantic web architecture and is becoming increasingly important over time due to its ability to share and re-use structured data which is both human and computer readable over the web. Currently, many libraries, archives, museums etc. are using open source digital library software to manage and preserve their digital collections. They may also intend to publish their e-resources as "Linked Open Datasets" for further usage. LOD enables the libraries or information centers to publish and share the structured metadata that is generated and maintained with their own bibliographic and authority data in such a way that the other libraries and general community across the world can consume, interact, enrich and share. In this context, the key issue is to convert the library bibliographic data which is commonly known as metadata into LOD dataset. The purpose of this paper is to provide a methodology and technical aspects to design and publish a structured LOD dataset of bibliographic information from a digital repository developed with DSpace digital library software so that other libraries can link their repositories with these LOD for providing additional relevant resources to their end-users. The paper shows the process of integration and configuration of Apache Jena Fuseki (a tool for SPARQL Endpoint interface) with DSpace for converting metadata into Resource Description Framework (RDF) triple model and make them available in various RDF formats. It also discusses a model for building a LOD framework to convert and store RDF graph and RDF triple. Finally, it tests the accessibility of the inked open dataset by querying RDF data through a SPARQL endpoint interface. [ABSTRACT FROM AUTHOR]

The current methods of searching and information retrieval are imprecise, often yielding results in tens of thousands of web pages. Extraction of the actual information needed often requires extensive manual browsing of retrieved documents. In order to address these drawbacks, this paper introduces an implementation in the field of food science of the ontology-based information retrieval system, and comparison is made with conventional information systems. The ontology of Food Semantic Web Knowledge Base (FSWKB) was built using the Protégé framework which supports two main models of ontology through the editors Protégé-Frames and Protégé-OWL. The FSWKB is composed of two heterogeneous ontologies, and these are merged and processed on a separate server application making use of the Apache Jena Fuseki an SPARQL server offering SPARQL endpoint. The experimental results indicated that ontology-based information systems are more effective in terms of their retrieval capability compared to the more conventional information retrieval systems. The retrieval effectiveness was measured in terms of precision and recall. The results of the work showed that traditional search results in average precision and recall levels of 0.92 and 0.18. The ontology-based test for precision and recall has average rates of 0.96 and 0.97. [ABSTRACT FROM AUTHOR]