scholarly journals Semantic Representation and Internet of Things in Cultural Heritage Preventive Conservation

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Konstantinos Michalakis ◽  
Efthymia Moraitou ◽  
John Aliprantis ◽  
George Caridakis
Keyword(s):  
Internet Of Things ◽  
Semantic Web ◽  
Cultural Heritage ◽  
Semantic Representation ◽  
Environmental Parameters ◽  
Streaming Data ◽  
Sensor Data ◽  
Physical Interaction ◽  
Semantic Web Technologies ◽  
Preventive Conservation

Preservation of Cultural Heritage (CH) collections in the best possible condition for the longest time possible is a crucial part of CH Institutions activity, since it ensures artefacts’ effective function in perpetuity. In this context, preservation processes that do not include any physical interaction with an object or collection can be regarded as preventive conservation. Preventive conservation measures and activities include among others the monitoring and management of environmental factors, in order to reduce potential risks of collections condition. The advent of the Internet of Things (IoT) can help towards this goal by automating the collection of data through sensors deployed in the cultural space and providing available services based on the IoT ecosystem. IoT technologies can facilitate the preventive conservation of tangible CH by exploiting streaming data produced by networks of sensors that keep track of changes in environmental parameters of a particular museum, in order to monitor the condition of its collections. Moreover, Semantic Web (SW) technologies could increase the efficiency of sensed data management by introducing reasoning mechanisms that will result in useful inferences regarding the combination of long-term or short-term records of sensed data and material decay. This work summarizes current state-of-the-art frameworks and monitoring systems that collect data from sensors in CH environments and the use of semantic web technologies for the efficient management of conservation and sensor data. Based on this study, it proposes an IoT infrastructure with semantic tools, which aims to enhance preventive conservation science.

How Industry 4.0 Can Benefit From Semantic Web Technologies and Artefacts

2021 ◽  
Vol 13 (4) ◽  
pp. 64-74
Author(s):  
Leila Zemmouchi-Ghomari
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Semantic Web ◽  
Industry 4.0 ◽  
The Internet ◽  
Time Data ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Real Time Data ◽  
The Internet Of Things

Industry 4.0 is a technology-driven manufacturing process that heavily relies on technologies, such as the internet of things (IoT), cloud computing, web services, and big real-time data. Industry 4.0 has significant potential if the challenges currently being faced by introducing these technologies are effectively addressed. Some of these challenges consist of deficiencies in terms of interoperability and standardization. Semantic Web technologies can provide useful solutions for several problems in this new industrial era, such as systems integration and consistency checks of data processing and equipment assemblies and connections. This paper discusses what contribution the Semantic Web can make to Industry 4.0.

scholarly journals A Mobile Matchmaker for the Ubiquitous Semantic Web

2016 ◽  
pp. 994-1017 ◽  
Author(s):  
Floriano Scioscia ◽  
Michele Ruta ◽  
Giuseppe Loseto ◽  
Filippo Gramegna ◽  
Saverio Ieva ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Decision Support ◽  
Internet Of Things ◽  
Semantic Web ◽  
Knowledge Bases ◽  
Semantic Web Technologies ◽  
Experimental Performance ◽  
Web Technologies ◽  
Constrained Environments ◽  
And Performance

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.

scholarly journals Editorial: Special issue on Semantic Web for Cultural Heritage

Semantic Web ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 163-167
Author(s):  
Antonis Bikakis ◽  
Eero Hyvönen ◽  
Stéphane Jean ◽  
Béatrice Markhoff ◽  
Alessandro Mosca
Keyword(s):  
Semantic Web ◽  
Cultural Heritage ◽  
Linked Data ◽  
Wide Spectrum ◽  
Special Issue ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Editorial Special Issue ◽  
Major Application ◽  
Application Fields

Cultural Heritage and Digital Humanities have become major application fields of Linked Data and Semantic Web technologies. This editorial introduces the special issue of the Semantic Web (SWJ) journal on Semantic Web for Cultural Heritage. In total 30 submissions for the call of papers were received, of which 11 were selected for publication. The papers cover a wide spectrum of modelled topics related to language, reading and writing, narratives, historical events and cultural artefacts, while describing reusable methodologies and tools for cultural data management. This issue indicates and demonstrates the high potential of Semantic Web technologies for applications in the Cultural Heritage domain.

scholarly journals Large-Scale Real-Time Semantic Processing Framework for Internet of Things

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Xi Chen ◽  
Huajun Chen ◽  
Ningyu Zhang ◽  
Jue Huang ◽  
Wen Zhang
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Semantic Processing ◽  
Large Scale ◽  
Sensor Data ◽  
Sensor Technology ◽  
Semantic Web Technologies ◽  
Computing Platform ◽  
Iot Applications ◽  
Processing Framework

Nowadays, the advanced sensor technology with cloud computing and big data is generating large-scale heterogeneous and real-time IOT (Internet of Things) data. To make full use of the data, development and deploy of ubiquitous IOT-based applications in various aspects of our daily life are quite urgent. However, the characteristics of IOT sensor data, including heterogeneity, variety, volume, and real time, bring many challenges to effectively process the sensor data. The Semantic Web technologies are viewed as a key for the development of IOT. While most of the existing efforts are mainly focused on the modeling, annotation, and representation of IOT data, there has been little work focusing on the background processing of large-scale streaming IOT data. In the paper, we present a large-scale real-time semantic processing framework and implement an elastic distributed streaming engine for IOT applications. The proposed engine efficiently captures and models different scenarios for all kinds of IOT applications based on popular distributed computing platform SPARK. Based on the engine, a typical use case on home environment monitoring is given to illustrate the efficiency of our engine. The results show that our system can scale for large number of sensor streams with different types of IOT applications.

scholarly journals A Mobile Matchmaker for the Ubiquitous Semantic Web

2014 ◽  
Vol 10 (4) ◽  
pp. 77-100 ◽  
Author(s):  
Floriano Scioscia ◽  
Michele Ruta ◽  
Giuseppe Loseto ◽  
Filippo Gramegna ◽  
Saverio Ieva ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Decision Support ◽  
Internet Of Things ◽  
Semantic Web ◽  
Knowledge Bases ◽  
Semantic Web Technologies ◽  
Experimental Performance ◽  
Web Technologies ◽  
Constrained Environments ◽  
And Performance

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.

scholarly journals Enabling Interoperability in the Internet of Things

2017 ◽  
Vol 13 (1) ◽  
pp. 147-167 ◽  
Author(s):  
Alfredo D'Elia ◽  
Fabio Viola ◽  
Luca Roffia ◽  
Paolo Azzoni ◽  
Tullio Salmon Cinotti
Keyword(s):  
Internet Of Things ◽  
Semantic Web ◽  
Smart Cities ◽  
The Internet ◽  
Semantic Web Technologies ◽  
Public Authorities ◽  
Web Technologies ◽  
Data Store ◽  
Rdf Graphs ◽  
The Internet Of Things

Semantic Web technologies act as an interoperability glue among different formats, protocols and platforms, providing a uniform vision of heterogeneous devices and services in the Internet of Things (IoT). Semantic Web technologies can be applied to a broad range of application contexts (i.e., industrial automation, automotive, health care, defense, finance, smart cities) involving heterogeneous actors (i.e., end users, communities, public authorities, enterprises). Smart-M3 is a semantic publish-subscribe software architecture conceived to merge the Semantic Web and the IoT domains. It is based on a core component (SIB, Semantic Information Broker) where data is stored as RDF graphs, and software agents using SPARQL to update, retrieve and subscribe to changes in the data store. This article describes a OSGi SIB implementation extended with a new persistent SPARQL update primitive. The OSGi SIB performance has been evaluated and compared with the reference C implementation. Eventually, a first porting on Android is presented.

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