Application of Semantic Web technologies in Informatics Education (short paper) (original) (raw)

A Hands-on Project for Teaching Semantic Web Technologies in an Undergraduate AI Course

Journal of Machine Intelligence and Data Science, 2021

The latest advances in Semantic Web technologies suggest an accelerating emergence of new exciting Artificial Intelligence applications that are expected to dramatically extend and improve current web services. Yet, these new technologies are outside the scope of undergraduate computer science curriculum. This paper presents our experience with introducing a hands-on project intended to teach Linked Data and Semantic Web as part of an undergraduate Artificial Intelligence course. The project is intended to achieve the following: 1.) Demonstrate the evolution of Knowledge Engineering into Ontological Engineering; 2.) Introduce students to Semantic Web technologies and tools such as ontology editor Protégé, Web Ontology Language (OWL), Semantic Web Rule Language (SWRL), and query language SPARQL; 3.) Extend the topic on reasoning into Description Logics and demonstrate the advantages of their inferencing capabilities; 4.) Use OWL and SWRL to compare descriptive and rule-based reasoning frameworks and show how their integration can improve the efficiency and the semantic adequacy of applications; 5.) Illustrate the Linked Data principles in a practical setting. Limited assessment of the pedagogical value of this project based on student learning outcomes suggests that it enhances students' understanding of the core AI topics, boosts their engagement and interest in the course, but more importantly introduces them to the newest advances in web application development.

Principles and Practice of Semantic Web Reasoning

Lecture Notes in Computer Science, 2004

Attempto Controlled English (ACE)-a subset of English that can be unambiguously translated into first-order logic-is a knowledge representation language. To support automatic reasoning in ACE we have developed the Attempto Reasoner RACE (Reasoning in ACE). RACE proves that one ACE text is the logical consequence of another one, and gives a justification for the proof in ACE. Variations of the basic proof procedure permit query answering and consistency checking. Reasoning in RACE is supported by auxiliary first-order axioms and by evaluable functions. The current implementation of RACE is based on the model generator Satchmo.

Reasoning on the semantic web: Beyond ontology languages and reasoners

2005

Abstract This article discusses forms of reasoning (beyond ontology reasoning), and reasoning languages (beyond ontology languages), that are needed for a full deployment of the Semantic Web. We first outline a motivating application scenario, then discuss the logic languages needed on the Semantic Web and related issues. The views reported about in this article underly and have been developed within the EU research project REWERSE (REasoning on the WEb with Rules and SEmantics, cf. http://rewerse. net).

Automated reasoning on the web

… of Applied Logic, 2004

Automated reasoning is becoming an essential issue in many Web systems and applications, especially in emerging Semantic Web applications. This article first discusses reasons for this evolution. Then, it presents research issues currently investigated towards automated reasoning on the Web and it introduces into selected applications demonstrating the practical impact of the approach. Finally, it introduces a research endeavor called REWERSE (cf.

Classroom for the Semantic Web

A Semantic Web Perspective

This chapter emphasizes integration of Semantic Web technologies in intelligent learning systems by giving a proposal for an intelligent learning management system (ILMS) architecture we named Multitutor. This system is a Web-based environment for the development the e-learning courses and for the use of them by the students. Multitutor is designed as a Web-classroom client-server system, ontologically founded, and is built using modern intelligent and Web-related technologies. This system enables the teachers to develop tutoring systems for any course. The teacher has to define the metadata of the course: chapters, the lessons and the tests, the references of the learning materials. We also show how the Multitutor system can employed to develop learning systems that use ontologically created learning materials as well as Web services. As an illustration we describe a simple Petri net teaching system that is based on the Petri net infrastructure for the Semantic Web.

Semantic Web and Comparative Analysis of Inference Engines

2012

— Semantic Web is an emerging technology for efficient reasoning support over the knowledge represented on the Web. This paper presents the semantic web standards and survey a number of Inference Engines that supports reasoning with OWL. Also analyzed the reasoner with set of ontologies and based on supported features.

Semantic Web: An approach for Effective Teaching and Learning

2016

Semantic web represents a potential technology for realizing e-Learning requirements. Research works in the field of e-Learning are represented by a wide range of applications, ranged from virtual classrooms to remote courses or distance learning. However, studies show that still it demands more effective approach. Semantic web has played an important role in designing such applications by either extending already existing applications to semantic web or creating new applications that are completely semantic web based. Use of semantic web techniques is a step further towards increasing the efficiency of applications by providing s of the knowledge as these are more effective in expressing an idea. Semantic Web enhances the capability of the semantic Web technology to access and process data from websites, databases, XML documents, and other systems to increase the amount of useful data retrieved exponentially. During the last few years semantic web has achieved long milestones and a...

Using semantics in INES, an Intelligent Educational System

2009 39th IEEE Frontiers in Education Conference, 2009

prototype of an online learning platform, which combines three essential capabilities related to e-learning activities. These capabilities are those related to Learning Management Systems, Learning Content Management Systems, and Intelligent Tutoring Systems. To carry out all these functionalities, our system, as a whole, comprises a set of different tools and technologies, as follows: an intelligent chatterbot which is able to communicate with students in natural language, an intelligent agent based on BDI (Believes, Desires, Intentions) technology which acts as the brain of the system, an inference engine based on JESS (a rule engine for the Java platform), and an ontology. At the present paper we will focus on this ontology, which is used in the platform to provide semantic support for system users (administrators, teachers, and students), their activities, and the learning contents. We will specifically address the architecture and performance of the ontology, and their contribution to INES.

A web service reasoner for the semantic web

Proceedings of the …, 2007

Web Services offer a standard interface for describing the available services on the Web. Common applications of Web Services are B2B communications and ecommerce, mainly because they are platform and network-independent, easily deployable and offer great reusability. Moreover, the Semantic Web initiative proposes technologies and languages for annotating information on the Web, so that it can be understood, interpreted and exploited by software agents. For the realization of such architecture, agents should be able to reason over the annotated information, in order to make decisions and to successfully cooperate with each other. To this end, logic and rules play an important role, enabling the description of assertions that can be used to derive new knowledge and the implementation of agent behaviour. In this paper we describe the Web Service implementation of a rule-based RDF reasoner, called DR-DEVICE. The deployment of the reasoner as a Web Service enables other applications to use the system over the Internet, by exploiting the well-defined interface that Web Service technology offers. Agents can use the service by interchanging messages, based on standards (SOAP) and already existing Internet protocols (HTTP), in order to enrich their functionality with reasoning capabilities. Furthermore, the system can serve as a software component of a more complex and distributed framework that would compose a variety of Web Services in order to achieve a new functionality. DR-DEVICE supports both deductive and defeasible rules and can be extended to the proof layer of the Semantic Web architecture, for validating the derivations stemming from the inferential logic activity. The service is available to end users through a Web interface.

Intelligent Tutoring in the Semantic Web and Web 2.0 Environments

2008

The paper presents an approach to solving problems pertinent to intelligent tutoring in the Semantic Web/Web 2.0 environments within the TEx-Sys (Tutor Expert System) model, an evolving series of ITSs our group has been developing for the last 15 years, following all Web technology generations being used in this period. We describe the way in which assigning intelligent tutoring tasks to personal agents enables solving the problems, additionally extending intelligent tutoring through the mobile, collaborative and social dimensions in the Semantic Web and Web 2.0 environments.