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Special Issue "Semantics for Sensors, Networks and Things"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: 30 November 2019.

Special Issue Editors

Dr. Danh Le Phuoc
E-Mail Website
Guest Editor
TU Berlin,10623 Berlin, Germany
Dr. Arne Bröring
E-Mail Website
Guest Editor
Siemens AG — Corporate Technology, Munich, Germany
Interests: internet of things, semantic web technologies, the sensor web, participatory sensing, as well as mobile and location based services
Dr. Jeff Z. Pan
E-Mail Website
Guest Editor
Department of Computing Science, The University of Aberdeen, AB24 3UE Aberdeen, UK
Interests: artificial intelligence; knowledge graph; approximate reasoning; learning and reasoning
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Semantics is becoming an appealing instrument for enabling the interoperability and composability at high-level information abstraction for sensors and networks in the Internet of Things/Everything. There have been several disconnected research communities and standardisation bodies that have proposed various semantic-based approaches in the interest of sharing common understandings among human (users, knowledge engineers, developers, etc.) and physical things (sensors, networks, things, etc.). The most active of these is Semantic Web, which advocates the use of ontologies and knowledge graphs (backed by Description Logics, Datalog, etc.) as core ingredients for modelling data as well as network and system design. Interestingly, the experts in sensor network and networking technologies also proposed the use of logic programming such as Prolog and Datalog for better abstractions of data, constraints, and system compositions. In parallel, sensor fusion and knowledge fusion seem to be the big topics of many communities, as they will be considerably beneficial for semantic abstractions (ontologies or taxonomies such as W3C/OGC Sensor Network Ontology, Thing Description Ontology of W3C Web of Things, ETSI OneM2M Ontology, Schema.org) in association with emerging achievements in building knowledge graphs. At the system perspective, the pervasive and autonomous computing community has shown interest in using ontologies for modelling contextual information, and now this community is coming back with new incarnations of edge/fog computing and autonomous systems (autonomous vehicles, Industry 4.0, smart cities, large-scale cyber-physical-systems) which need semantic abstractions as the decoupling design paradigm in order to enable dynamic integration in real time.

In this context, we welcome submissions from any area that touches a subset of the aforementioned aspects on semantics in sensors, networks, multimedia objects, and things in general. Beyond usual research and survey papers, the submission of papers that apply novel approaches in industry use cases are highly welcome. These papers should demonstrate validated (measureable) advantages of the applied approach in comparison to current industry solutions (if any) or clearly showcase the gained advantages in real-world setups. We also encourage the submission of papers that discuss benefits and challenges of large-scale pilots and industrial-grade testbeds. Applications may lay in domains such as (but not limited to) smart cities, environmental monitoring, manufacturing (Industry 4.0), mobility and automotive, building automation, eHealth, and energy distribution.

Dr. Danh Le Phuoc
Dr. Arne Bröring
Dr. Jeff Z. Pan
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (1 paper)

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Research

Open AccessArticle
EAGLE—A Scalable Query Processing Engine for Linked Sensor Data
Sensors 2019, 19(20), 4362; https://doi.org/10.3390/s19204362 - 09 Oct 2019
Abstract
Recently, many approaches have been proposed to manage sensor data using semantic web technologies for effective heterogeneous data integration. However, our empirical observations revealed that these solutions primarily focused on semantic relationships and unfortunately paid less attention to spatio–temporal correlations. Most semantic approaches [...] Read more.
Recently, many approaches have been proposed to manage sensor data using semantic web technologies for effective heterogeneous data integration. However, our empirical observations revealed that these solutions primarily focused on semantic relationships and unfortunately paid less attention to spatio–temporal correlations. Most semantic approaches do not have spatio–temporal support. Some of them have attempted to provide full spatio–temporal support, but have poor performance for complex spatio–temporal aggregate queries. In addition, while the volume of sensor data is rapidly growing, the challenge of querying and managing the massive volumes of data generated by sensing devices still remains unsolved. In this article, we introduce EAGLE, a spatio–temporal query engine for querying sensor data based on the linked data model. The ultimate goal of EAGLE is to provide an elastic and scalable system which allows fast searching and analysis with respect to the relationships of space, time and semantics in sensor data. We also extend SPARQL with a set of new query operators in order to support spatio–temporal computing in the linked sensor data context. Full article
(This article belongs to the Special Issue Semantics for Sensors, Networks and Things)
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