Pengembangan Onti Measures Berbasis Web dengan Pengujian Data Ontology Virus dan Penyakit

Penggunaan dokumen ontology pada kasus COVID-19 adalah sebuah contoh begitu dibutuhkannya inconsistency measure untuk OWL ontology. Ontology adalah representasi pengetahuan pada teknologi web semantik yang merupakan ekstensi dari website. Peran inconsistency measure menjadi penting untuk memastikan bahwa seluruh informasi pada sebuah ontology konsisten. Penelitian dalam makalah ini bertujuan membangun program aplikasi bernama Onti Measures berbasis web yang merupakan pengembangan dari sebuah prototipe program inconsistency measures berbasis ontology yang telah dibuat pada penelitian sebelumnya. Prototipe tersebut memiliki beberapa kelemahan, di antaranya prototipe hanya berupa kode program dan tidak ada antarmuka pengguna, sehingga program tidak dapat diakses oleh umum. Pengumpulan data dilakukan melalui studi pustaka, sedangkan metode pengembangan sistemnya adalah metode waterfall. Sampel pengujian dalam makalah ini adalah berkas ontology kasus virus dan penyakit yang dijadikan sebagai masukan program Onti Measures dengan pemakaian tiga jenis OWL reasoner. Keluaran program adalah informasi nilai inkonsistensi, running time, beserta ukuran ontology. Pengujian dilakukan dengan metode whitebox testing dan blackbox testing.

A Methodology for an Auto-Generated and Auto-Maintained HL7 FHIR OWL Ontology for Health Data Management

The process of maintenance of an underlying semantic model that supports data management and addresses the interoperability challenges in the domain of telemedicine and integrated care is not a trivial task when performed manually. We present a methodology that leverages the provided serializations of the Health Level Seven International (HL7) Fast Health Interoperability Resources (FHIR) specification to generate a fully functional OWL ontology along with the semantic provisions for maintaining functionality upon future changes of the standard. The developed software makes a complete conversion of the HL7 FHIR Resources along with their properties and their semantics and restrictions. It covers all FHIR data types (primitive and complex) along with all defined resource types. It can operate to build an ontology from scratch or to update an existing ontology, providing the semantics that are needed, to preserve information described using previous versions of the standard. All the results based on the latest version of HL7 FHIR as a Web Ontology Language (OWL-DL) ontology are publicly available for reuse and extension.

Mapping Relational Database to OWL Ontology Based on MDE Settings

Ontology is an important aspect of the semantic web, which is why semantic web developers are interested in constructing ontology in various applications based on domain experts. By transforming an existing application database into ontology, we many construct ontologies without having to hire an expert in the field. Model-driven engineering is the foundation of the suggested strategy (MDE). In a nutshell, the technique is divided into two phases, the first of which attempts to prepare the data needed for the transformation in the form of a model with a database. A compliance relationship between this model and its meta-model is required. Phase (2) applies a set of rules written in the Atlas Transformational Language to change the model produced in the first phase into another model, which is an OWL ontology (ATL). We tested our solution using a set of databases created specifically for this purpose and built it in an eclipse environment using an EMF and ATL transform language. The acquired findings demonstrate the strength and efficacy of the recommended strategy.

An Extended Rule of the SysML Requirement Diagram Transformation into OWL Ontologies

The System Modeling Language (SysML) used the Requirement Diagram to model non-functional requirements, such as response time, size, or system functionality, which cannot be accommodated in the Unified Modeling Language (UML). SysML Requirement Diagram, in its implementation, integrates with several diagrams describing the requirements, which are referred to as additional elements. The absence of transformation rules for these additional elements to become OWL ontology causes difficulties in reading, understanding, and tracking the requirements. In this research, an extended rule of the Requirement Diagram transformation is proposed to solve the problems. First, some transformation rules are defined to make requirements easier to trace and realize the ontology generation's automatic transformation. Second, the time required during transformation processing to prepare and generate the OWL file shows the proposed model's performance. The ontology components produced from this research, such as class, subclass, object property, and data property, can be viewed in Protégé.

Ontology-Based Travel Recommender System

Recommender systems are designed to suggest information to users according to their preferences. The items could be movies, books, or various kinds of products. Most of the existing recommender systems are based on a database with limited advantages. However, in this chapter, the authors propose a knowledge-driven travel recommender system to integrate semantic data built using web ontology language (OWL) ontology to allow users to find suitable destinations that fulfil users' travel preferences. This work aims to develop a travel recommendation tool and to examine the reliability, the usability of the system, and satisfaction rate of users. They are also able to demonstrate that users can obtain desired results through queries on the ontology-based system. The overall evaluation of the system shows that users are happy and satisfied with the recommendation results.