Mini-ME Matchmaker and Reasoner for the Semantic Web of Things

Author(s):  
Floriano Scioscia ◽  
Michele Ruta ◽  
Giuseppe Loseto ◽  
Filippo Gramegna ◽  
Saverio Ieva ◽  
...  

The Semantic Web of Things (SWoT) aims to support smart semantics-enabled applications and services in pervasive contexts. Due to architectural and performance issues, most Semantic Web reasoners are often impractical to be ported: they are resource consuming and are basically designed for standard inference tasks on large ontologies. On the contrary, SWoT use cases generally require quick decision support through semantic matchmaking in resource-constrained environments. This paper describes Mini-ME (the Mini Matchmaking Engine), a mobile inference engine designed from the ground up for the SWoT. It supports Semantic Web technologies and implements both standard (subsumption, satisfiability, classification) and non-standard (abduction, contraction, covering, bonus, difference) inference services for moderately expressive knowledge bases. In addition to an architectural and functional description, usage scenarios and experimental performance evaluation are presented on PC (against other popular Semantic Web reasoners), smartphone and embedded single-board computer testbeds.

Author(s):  
Floriano Scioscia ◽  
Michele Ruta ◽  
Giuseppe Loseto ◽  
Filippo Gramegna ◽  
Saverio Ieva ◽  
...  

The Semantic Web and Internet of Things visions are converging toward the so-called Semantic Web of Things (SWoT). It aims to enable smart semantic-enabled applications and services in ubiquitous contexts. Due to architectural and performance issues, it is currently impractical to use existing Semantic Web reasoners. They are resource consuming and are basically optimized for standard inference tasks on large ontologies. On the contrary, SWoT use cases generally require quick decision support through semantic matchmaking in resource-constrained environments. This paper presents Mini-ME, a novel mobile inference engine designed from the ground up for the SWoT. It supports Semantic Web technologies and implements both standard (subsumption, satisfiability, classification) and non-standard (abduction, contraction, covering) inference services for moderately expressive knowledge bases. In addition to an architectural and functional description, usage scenarios are presented and an experimental performance evaluation is provided both on a PC testbed (against other popular Semantic Web reasoners) and on a smartphone.


2014 ◽  
Vol 10 (4) ◽  
pp. 77-100 ◽  
Author(s):  
Floriano Scioscia ◽  
Michele Ruta ◽  
Giuseppe Loseto ◽  
Filippo Gramegna ◽  
Saverio Ieva ◽  
...  

The Semantic Web and Internet of Things visions are converging toward the so-called Semantic Web of Things (SWoT). It aims to enable smart semantic-enabled applications and services in ubiquitous contexts. Due to architectural and performance issues, it is currently impractical to use existing Semantic Web reasoners. They are resource consuming and are basically optimized for standard inference tasks on large ontologies. On the contrary, SWoT use cases generally require quick decision support through semantic matchmaking in resource-constrained environments. This paper presents Mini-ME, a novel mobile inference engine designed from the ground up for the SWoT. It supports Semantic Web technologies and implements both standard (subsumption, satisfiability, classification) and non-standard (abduction, contraction, covering) inference services for moderately expressive knowledge bases. In addition to an architectural and functional description, usage scenarios are presented and an experimental performance evaluation is provided both on a PC testbed (against other popular Semantic Web reasoners) and on a smartphone.


Semantic Web ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 885-886
Author(s):  
Dhavalkumar Thakker ◽  
Pankesh Patel ◽  
Muhammad Intizar Ali ◽  
Tejal Shah

Welcome to this special issue of the Semantic Web (SWJ) journal. The special issue compiles four technical contributions that significantly advance the state-of-the-art in Semantic Web of Things for Industry 4.0 including the use of Semantic Web technologies and techniques in Industry 4.0 solutions.


Author(s):  
Patrick Maué ◽  
Sven Schade

Geospatial decision makers have to be aware of the varying interests of all stakeholders. One crucial task in the process is to identify relevant information available from the Web. In this chapter the authors introduce an application in the quarrying domain which integrates Semantic Web technologies to provide new ways to discover and reason about relevant information. The authors discuss the daily struggle of the domain experts to create decision-support maps helping to find suitable locations for opening up new quarries. After explaining how semantics can help these experts, they introduce the various components and the architecture of the software which has been developed in the European funded SWING project. In the last section, the different use cases illustrate how the implemented tools have been applied to real world scenarios.


2016 ◽  
Vol 42 (6) ◽  
pp. 851-862 ◽  
Author(s):  
Mario Andrés Paredes-Valverde ◽  
Rafael Valencia-García ◽  
Miguel Ángel Rodríguez-García ◽  
Ricardo Colomo-Palacios ◽  
Giner Alor-Hernández

The semantic Web aims to provide to Web information with a well-defined meaning and make it understandable not only by humans but also by computers, thus allowing the automation, integration and reuse of high-quality information across different applications. However, current information retrieval mechanisms for semantic knowledge bases are intended to be only used by expert users. In this work, we propose a natural language interface that allows non-expert users the access to this kind of information through formulating queries in natural language. The present approach uses a domain-independent ontology model to represent the question’s structure and context. Also, this model allows determination of the answer type expected by the user based on a proposed question classification. To prove the effectiveness of our approach, we have conducted an evaluation in the music domain using LinkedBrainz, an effort to provide the MusicBrainz information as structured data on the Web by means of Semantic Web technologies. Our proposal obtained encouraging results based on the F-measure metric, ranging from 0.74 to 0.82 for a corpus of questions generated by a group of real-world end users.


Author(s):  
Ismail Nadim ◽  
Yassine El ghayam ◽  
Abdelalim Sadiq

<p class="western" style="margin-top: 0.21cm; margin-bottom: 0cm;" lang="en-US" align="justify"><span style="color: #000000;"><span style="font-size: small;">Information and communication technologies (ICT) know a significant development especially in terms of hardware miniaturization, cost reduction and energy consumption optimization. This advancement enables the interconnection of a large number of physical objects namely using the Internet, forming what is called the Internet of Things (IoT). The IoT provides the opportunity to interact with these objects through sensors, actuators and smart applications which may help users in several areas such as transport, logistics, health care, agriculture, etc. However, building the IoT requires a strong interoperability between thousands of heterogeneous devices and services. In this context, the SWoT (Semantic Web of Things) uses semantic Web technologies to enrich these devices and services with semantic annotations which enables the semantic interoperability. However, the development of SWOT-based systems on a large scale faces many challenges especially due to the large number of devices and services, their geographical distribution as well as their mobility. These challenges - which may affect the system performance as a whole - require innovative industry and research efforts. The current paper proposes a SWoT framework architecture that take into account the main SWoT challenges.</span></span></p>


Author(s):  
Felix Ocker ◽  
Birgit Vogel-Heuser ◽  
Christiaan J. J. Paredis

In the product development process, as it is currently practiced, production is still often neglected in the early design phases, leading to late and costly changes. Using the knowledge of product designers concerning production process design, this paper introduces an ontological framework that enables early feasibility analyses. In this way, the number of iterations between product and process design can almost certainly be reduced, which would accelerate the product development process. Additionally, the approach provides process engineers with possible production sequences that can be used for process planning. To provide feasibility feedback, the approach presented relies on semantic web technologies. An ontology was developed that supports designers to model the relations among products, processes, and resources in a way that allows the use of generic Sparql Protocol And RDF Query Language (SPARQL) queries. Future applicability of this approach is ensured by aligning it with the top-level ontology Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE). We also compare the ontology’s universals to fundamental classes of existing knowledge bases from the manufacturing and the batch processing domains. This comparison demonstrates the approach’s domain-independent applicability. Two proofs of concept are described, one in the manufacturing domain and one in the batch processing domain.


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