Mobile Context-Addressable Messaging with DL-Lite Domain Model

Koziuk, Michal; Domaszewicz, J.; Schoeneich, Radosław Olgierd; Jablonowski, Marcin; Boetzel, Piotr

doi:10.1007/978-3-540-88793-5_13

Cited by 9 publications

(11 citation statements)

References 7 publications

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“…µJena is one of the first tools to manage ontologies and RDF stored in mobile devices [38]. LOnt implements Jena API for mobile devices [39]. Gu et al proposed a mobile framework for ontology processing and reasoning.…”

Section: B Semantic Technologiesmentioning

confidence: 99%

Distribution of Semantic Reasoning on the Edge of Internet of Things

Riekki

et al. 2018

2018 IEEE International Conference on Pervasive Computing and Communications (PerCom)

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Semantics associates meaning with Internet of Things (IoT) data and facilitates the development of intelligent IoT applications and services. However, the big volume of the data generated by IoT devices and resource limitations of these devices have given rise to challenges for applying semantic technologies. In this article, we present Cloud and edge based IoT architectures for semantic reasoning. We report three experiments that demonstrate how edge computing can facilitate IoT systems in terms of data transfer and semantic reasoning. We also analyze how distributing reasoning tasks between the Cloud and edge devices affects system performance.

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Section: B Semantic Technologiesmentioning

confidence: 99%

Distribution of Semantic Reasoning on the Edge of Internet of Things

Riekki

et al. 2018

2018 IEEE International Conference on Pervasive Computing and Communications (PerCom)

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“…LOnt [86] is another effort of implementing Jena API for mobile devices. Gu et al [87] proposed a mobile framework for ontology processing and reasoning.…”

Section: Related Work About Semantic Technologies For Pervasive Compumentioning

confidence: 99%

Lightweight data and knowledge exchange for pervasive environments1

2017

AIS

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Pervasive environments are physical spaces saturated with devices collecting data, controlling the environment, and interacting with users. These environments support human users in their everyday tasks so that the users can focus on their own tasks and access services and resources whenever and wherever they want. Such environments are also called smart spaces. Knowledgebased systems would enable realizing a variety of intelligent applications for pervasive environments. Generally, such systems recognize the situation in the environment from sensor data and utilize automated reasoning techniques to respond to the situation and the needs of the users.However, building knowledge-based systems for pervasive environments presents challenges. This dissertation focuses on the challenge of data and knowledge representations. Knowledgebased systems utilize expressive knowledge representations that are verbose and require sufficient resources in order to use them. Most devices in pervasive environments cannot handle these representations as the devices have limited resources for computation, storage, and communication. The main aim of this dissertation is to tackle this challenge. That is, on the one hand, pervasive environments demand data and knowledge representations that do not require many resources from the resource-constrained devices; and on the other hand, the representations should be compatible with the knowledge-based systems. Specifically, a general solution is required that enables many applications to use the same data with minimal effort from application developers.This dissertation presents a novel representation, Entity Notation (EN), to tackle these challenges. EN is designed as a general lightweight representation for data and knowledge. EN expresses entities, their properties, and property values. This structure resembles the triple structure of Resource Description Framework (RDF) and Web Ontology Language (OWL). Hence, sensor data in EN syntax can be transformed into common knowledge models in a straightforward manner and utilized with ease by knowledge-based systems. EN Schema is designed for transferring advanced knowledge models. Moreover, EN also offers an approach to shorten the format with templates and prefixes. This way, EN can be utilized by resourceconstrained devices and environments. Our evaluation verifies that small devices can utilize EN to transfer data and knowledge to devices realizing intelligent functions, such as inference. Moreover, the expressive power of EN is comparable with the alternative representations. Finally, resource consumption is verified by prototypes. Based on the evaluation, we can conclude that EN can facilitate harnessing the full potential of pervasive environments.Keywords: Entity Notation, knowledge-based systems, ontology, reasoning, Resource Description Framework, resourceconstrained devices, semantics Su, Xiang, Kevyen datan ja tietämyksen esitystavat jokapaikan tietotekniikan sovelluksille.Oulun yliopiston tutkijakoulu; Oulun yliopisto, Tieto-...

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“…Crivellaro et al [5] developed [iJena, which serves to manage ontologies stored in mobile devices although does not face ontological reasoning. LOnt [6] is another custom implementation of Jena API for mobile devices. Its main features are its small size and low memory fingerprint, which make it suitable to be used in J2ME mobile devices.…”

Section: State-of-the-art: Mobile Reasoning Systemsmentioning

confidence: 99%

“…Although future extensions are planned, at present it just can read OWL ontologies coded in N-TRIPLE syntax. No report about the performance of this syntax in mobile devices has been found, but updated references regarding this issue ( [6], [7]) point out to Manchester or KRSS syntax as some of the most appropriate for resourceconstrained devices. In addition, [üena lacks support to any rule or query language standard; besides, it does not allow external ontologies to be imported.…”

Section: Vil Dlscussion and Future Workmentioning

confidence: 99%

A Light Reasoning Infrastructure to Enable Context-aware Mobile Applications

Iglesias

Bernardos

Alvarez

et al. 2010

2010 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing

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-This paper presents a light inference system for context management, ready to perform reasoning tasks in resource-constrained devices. The inference system is part of a service-oriented mobile software framework which runs on Javaenabled handheld devices. This framework serves to facilítate the creation of context-aware applications, as it decouples sensor's data acquisition and context processing from the application logic itself. The inference architecture is composed by different modules; some of them encapsulate existing tools (ujena and Bossam) that have been adapted to the mobile working environment. The (rule-based) reasoning is prepared to use a general ontology. Both applications and the framework's components may configure the query set in order to retrieve the information they need from the inference system. In the paper, a validation example shows how this process is done.

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Mobile Context-Addressable Messaging with DL-Lite Domain Model

Cited by 9 publications

References 7 publications

Distribution of Semantic Reasoning on the Edge of Internet of Things

Distribution of Semantic Reasoning on the Edge of Internet of Things

Lightweight data and knowledge exchange for pervasive environments1

A Light Reasoning Infrastructure to Enable Context-aware Mobile Applications

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