Stigmergic Multi-Agent Systems in the Semantic Web of Things

The Internet of Things (IoT) is being applied for stovepipe solutions, since it presents a semantic description limited to a specific domain. IoT needs to be pushed towards a more open, interoperable and collaborative IoT. The first step has been the Web of Things (WoT). WoT evolves the IoT with a common stack based on web services. But, even when a homogeneous access is reached through web protocols, a common understanding is not yet acquired. For this purpose, the Semantic Web of Things (SWoT) is proposed for the integration of the semantic web on the WoT. This work analyses the SWoT, presenting its different levels to offer an IoT convergence. Specifically, we analyse the trends for capillary networks and for cellular networks with standards such as IPSO, ZigBee, OMA, and the oneM2M initiative. This work also analyses the impact of the semantic-annotations/metadata in the performance of the resources.

This paper reports on the early-stage development of an analytics framework to support the semantic integration of dynamic surveillance data across multiple scales to inform decision making for malaria eradication. We propose using the Semantic Web of Things (SWoT), a combination of Internet of Things (IoT) and semantic web technologies, to support the evolution and integration of dynamic malaria data sources and improve interoperability between different datasets generated through relevant IoT assets (e.g. computers, sensors, persons, and other smart objects and devices).

Internet of Things (IoT) is considered very widely spread in these days application and technology, which means a huge amount of data will need to be exchanged between devices and applications domains., For example, a weather application needs to communicate with a traffic application. Data between both applications need to be interpreted and to be interoperable in both applications. These applications are based on domain-specific, which means there is no domain interoperability. As a result, some developers and users took the web approach to find an easy solution that can be offered from the web itself, which leads to the Web of Things (WoT). But as with most recommendations in the web community, if data interoperability is needed as part of your implementation, you need to use Semantic Web as an approach that leads to a combined approach called Semantic Web of Things (SWoT). However, not every developer and user are having experience with Semantic Web standards such as RDF, Turtle, RDF/XML, SPARQL, OWL, etc. This paper proposes WOTJD for WoT using JavaScript Object Notation Linked Data (JSON-LD). WOTJD helps IoT users to overcome the main challenges of data interoperability in WOT by helping in (1) Design and integrate WOT applications, (2) IoT data parsing and annotation, and (3) Linking domains with each other (by using domain knowledge expertise), A case study of solving interoperability between smart cars and weather domain through a mobile application is presented, and performance evaluation has been performed, Experimental results show how fast is WOTJD framework against the sensor data size.

The book consists of 29 chapters which have been selected and invited from the submissions to the 1st International Conference on Collective Intelligence - Semantic Web, Social Networks & Multiagent Systems (ICCCI 2009). All chapters in the book discuss various examples of applications of computational collective intelligence and related technologies to such fields as semantic web, information systems ontologies, social networks, agent and multiagent systems. The editors hope that the book can be useful for graduate and Ph.D. students in Computer Science, in particular participants to courses on Soft Computing, Multi-Agent Systems and Robotics. This book can also be useful for researchers working on the concept of computational collective intelligence in artificial populations. It is the hope of the editors that readers of this volume can find many inspiring ideas and use them to create new cases intelligent collectives. Many such challenges are suggested by particular approaches and models presented in particular chapters of this book.

The Semantic Web of Things (SWoT) merges the Internet of Things with knowledge representation and reasoning techniques borrowed from the Semantic Web, in order to improve resource management and discovery. This paper proposes a SWoT framework in Wireless Sensor Networks (WSNs) enabling cooperative discovery of sensors and actuators. A backward-compatible extension of the Constrained Application Protocol (CoAP) makes possible to use semantic matchmaking via non-standard reasoning to better characterize the resource discovery. The framework also integrates nimble data stream mining to detect and annotate high-level events through raw data gathered from the environment. A cooperative environmental monitoring case study in Hybrid Sensor and Vehicular Networks (HSVN) is presented together with experiments on a real testbed to assess feasibility and benefits of proposal.

Internet of Things (IoT) is the growing invention in the current development of different domains like industries, e-health, and education, etc. Semantic web of things (SWoT) is an extension of IoT that enhance the communication by behaving intelligently. SWoT comprises 7 layered architecture. The perception layer is an important layer for collecting data from devices and to communicate with its associated layer. The data loss at the perception layer is very common due to inadequate resources, unpredictable link, noise, collision, and unexpected damage. To address this problem, we propose a method based on Compressive Sensing which recovers and estimates sensory data from a low-rank structure. The contribution of this paper is three folds. Firstly, we determine the problem of data acquisition and data loss at semantic sensory nodes in SWoT. Secondly, we introduce a compressive sensing based framework for SWoT that recovers the data accurately using low-rank features. Thirdly, the data estimation method is utilized to reduce the volume of the data. Proposed Compressive Sensing based Data Recoverability and Estimation (CS-RE) method is evaluated and compared with the existing reconstruction methods. The simulation results on real sensory datasets depict that the proposed method significantly outperforms existing methods in terms of error ratio and data recoverability accuracy.

Smart cities are becoming more and more popular. Currently, there is no unified and interoperable system which could be reused and redeployed in future smart cities. Having an interoperable: (1) system, (2) architecture, (3) workflow to process IoT data, (4) interoperable applications and services, and (5) secure access to data is becoming essential to reduce development cost in smart cities and ensure interoperability among vertical IoT applications (i.e., domain-specific). Firstly, we survey existing work integrating semantic web technologies to Internet of Things, also called 'Semantic Web of Things' and applying it to smart cities. Secondly, we share in this paper, our vision of Semantic Web of Things applied to smart cities and highlight main research challenges. Finally, the main contribution of this work is the semantic engine applied to IoT and smart cities. Moreover, the proposed semantic engine is applied to three use cases: Machine-to-Machine Measurement (M3) framework, FIESTA-IOT EU project and VITAL EU project.

The Web, as we know it, is a collection of human readable pages that are virtually unintelligible to computer programs. For that reason, it has been called the “eyeball” Web. While the Web emerged as a World Wide repository of digitized information, by and large, the very same information is not available for automatic computation. In recent years two parallel efforts emerged that have the potential of overcoming this paradox: the first effort is the Semantic Web which provides the tools for the explicit markup of the content of Web pages; the second effort is the development of Web Services which results in a Web where programs act as independent agents to become the producers and consumers of information and enable automation of business transactions.In this talk I will focus on research that attempts to bridge the gap between the Web as we know it, the Semantic Web and Web services. Under this approach, I propose the vision of Web services as autonomous goal-directed agents which select other agents to interact with, and flexibly negotiate their interaction model, acting at times in client server mode, or at other times in peer to peer mode. The resulting Web services, that I call Autonomous Semantic Web services, utilize ontologies and semantically annotated Web pages to automate the fulfillment of tasks and transactions with other Web agents. In particular, Autonomous Semantic Web services use the Semantic Web to support capability based discovery and interoperation at run time. A first step towards this vision is the development of formal languages and inference mechanisms for representing and reasoning with core concepts of Web services. DAML-S (the Darpa Agent Markup Language for Services) is the first attempt to define such a language. I will give a brief overview of DAML-S and its relations with the Semantic Web and Web services. In addition, I will provide concrete examples of computational models of how DAML-S can be viewed as the first step in bridging the gap between the Semantic Web and current proposed industry standards for Web services. I will provide concrete examples of DAML-S in action, discuss challenges still open in the bridging between the Semantic Web and Web services and provide a roadmap to get us from today’s Web to the Web of autonomous Semantic Web services.KeywordsFormal LanguageCore ConceptDigitize InformationAutomatic ComputationBusiness TransactionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

A Semantic Web of Things (SWoT) brings together the Semantic Web and the Web of Things (WoT), associating semantically annotated information to web-enabled physical devices, services and their data, towards seamless data integration and better understanding of real-world information. A missing element in order to realize SWoT is a standardized, scalable and flexible way to globally discover in (near) real time web-connected embedded devices, as well as their semantic data. To address this gap, we propose WOT Semantic Search Engine (WOTS2E), which is a search engine for the SWoT, based on web crawling, being able to discover Linked Data endpoints and, through them, WoT-enabled devices and their services. In this paper, we describe the design, development and implementation of WOTS2E, as well as an evaluation procedure showing its operation and performance across the web.

Semantic Web research relies on a number of key methodologies such as knowledge representation languages or reasoning algorithms. As a research community, however, we could not progress based on these methodologies exclusively, but require tools and systems that realize our research results as key technologies for the Semantic Web. There would be no Linked Data without repositories to store them, no Semantic Web applications without application programming interfaces to load and edit ontologies, and no semanticsbased user interfaces without reasoners. Consequently, some of these technologies are research enablers in their own rights. Unfortunately, the developers of such software— often researchers themselves—rarely get appropriate credit for their work. Attempts to publish papers describing their software systems frequently provoke reviews and decision letters questioning their ’conceptual contribution’. This criticism may be correct, be it because the conceptual underpinnings have been published previously, or because there may in fact be little conceptual underpinnings apart from excellent software engineering. As a result, developers of key research enabling software often have considerable difficulties publishing their work in high-quality journals. In turn, paradoxically, researchers using these systems within their own work lack a primary citation source for the used software, and may have to settle for a URL, a short demo paper, or for a workshop contribution as citation. These outlets, however, can not provide the rigid quality criteria and visibility compared to journal publications. There is a need for publishing Tools and Systems papers in primary journals. The criteria applied to evaluate such papers have to differ from those applied to classical research articles. Unfortunately, these alternative evaluation criteria are often not spelled out in detail and therefore not consistently taken into account by reviewers and editors. As a consequence, the Semantic Web journal has adopted the Tools and Systems article as one of its regular paper types and provides crisp criteria for their evaluation: Reports on tools and systems—short papers describing mature Semantic Web related tools and systems. These reports should be brief and pointed, indicating clearly the capabilities of the described tool or system. It is strongly encouraged, that the described tools or systems are free, open, and accessible on the Web. If this is not possible, then they have to be made available to the reviewers. For commercial tools and systems, exceptions can be arranged through the editors. These submissions will be reviewed along the following dimensions: (1) Quality, importance, and impact of the described tool or system (convincing evidence must be provided). (2) Clarity, illustration, and readability of the describing paper, which shall convey to the reader both the capabilities and the limitations of the tool. The impact of the described tool or system is indeed decisive. Authors are asked to provide evidence for a substantial number of researchers using their software for research and applications. In exceptional cases, authors may also argue about the potential future impact of their software given that they can provide clear evidence for this. Clearly, software prototypes which were only implemented as proof-of-concepts, or software which is closely tied to a particular (externally funded) project, are out of scope. Originality or novelty—which are decisive dimensions for high-quality research articles—are not mentioned among the evalu-

The common access to the broadband Internet allows small and medium enterprises (SME) simpler participation in various supply chains [3]. However the main problem still is lack of consistency between processes which are undertaken by various supply chain participants. The aim of this paper is to propose the concept of broader cooperation between manufacturing companies based on semantic web and multi-agent system. The background of this paper refers to previous experiences of the authors by implementation of the CORELOG project. It promotes cooperation in logistics services among manufacturing companies located in the Bologna metropolitan area in order to increase companies’ competitiveness as well as environmental sustainability through the rationalization of the logistics processes. The application of semantic web and multi-agent system in the above mentioned project allows the efficient automatic data collection about logistics services providers and their resources, as presented in the Internet.

Development of agent systems is naturally a complex task due to the fundamental characteristics of agents. In addition, agent internals and inter-agent behavior models inside Multi-agent Systems (MAS) may become even more difficult to implement when interactions of agents with web services on the Semantic Web are taken into account. Our approach consists of the utilization of a Domain-specific Modeling Language (DSML) during MAS development in order to cope with the abovementioned challenge. This paper describes how the formal semantics of this DSML can be defined by especially focusing on its viewpoint on agent-semantic service interactions and discusses the use of this semantics definition on MAS validation. Determined semantic rules are both defined and implemented by using Alloy specification language which has a strong description capability based on both relational and first-order logic.

IntroductionDrug utilization is currently assessed through traditional data sources such as big electronic medical records (EMRs) databases, surveys, and medication sales. Social media and internet data have been reported to provide more accessible and more timely access to medications' utilization.ObjectiveThis review aims at providing evidence comparing web data on drug utilization to other sources before the COVID-19 pandemic.MethodsWe searched Medline, EMBASE, Web of Science, and Scopus until November 25th, 2019, using a predefined search strategy. Two independent reviewers conducted screening and data extraction.ResultsOf 6,563 (64%) deduplicated publications retrieved, 14 (0.2%) were included. All studies showed positive associations between drug utilization information from web and comparison data using very different methods. A total of nine (64%) studies found positive linear correlations in drug utilization between web and comparison data. Five studies reported association using other methods: One study reported similar drug popularity rankings using both data sources. Two studies developed prediction models for future drug consumption, including both web and comparison data, and two studies conducted ecological analyses but did not quantitatively compare data sources. According to the STROBE, RECORD, and RECORD-PE checklists, overall reporting quality was mediocre. Many items were left blank as they were out of scope for the type of study investigated.ConclusionOur results demonstrate the potential of web data for assessing drug utilization, although the field is still in a nascent period of investigation. Ultimately, social media and internet search data could be used to get a quick preliminary quantification of drug use in real time. Additional studies on the topic should use more standardized methodologies on different sets of drugs in order to confirm these findings. In addition, currently available checklists for study quality of reporting would need to be adapted to these new sources of scientific information.

In this demonstration, we present our Semantic Web of Things~(SWoT) prototyping toolkit called SWoTSuite. It is a set of tools supporting an easy and fast prototyping of end-to-end SWoT applications. SWoTSuite facilitates - (i) automation of application development life-cycle, (ii) reducing the amount of time and effort required for developing WoT applications and (iii) an easy integration of semantic web technologies within WoT applications.

Semantic Web is the name of the next generation World Wide Web, that has been recently proposed by Tim Berners-Lee and the World Wide Web Consortium (W3C)1. In this new Web architecture, information and Web services will be easily understandable and usable by both humans and computers. The objective is not to make computers understand the human language, but to define a universal model for the expression of the information and a set of inference rules that machines can easily use in order to process and relate the information as if they really understood it (Berners-Lee, 1998). Though, as the current Web provided sharing of documents among previously incompatible computers, the Semantic Web intends to go beyond, allowing stovepipe systems, hardwired computers, and other devices to share contents embedded in different documents. The most known architecture for Semantic Web is based on a stack of related technologies, each one being a whole research area by itself (Berners-Lee, Hendler, & Lassila. 2001; Pereira & Freire, 2005). Accomplishment of the Semantic Web is considered a great challenge, not only due to the complexity of implementation but also because of the vast applicability in several areas. In spite of this, Semantic Web is still one of the most promising research areas among those which aim to define a new architecture for the Web. Semantic Web goes far beyond previous information retrieval and knowledge representation projects, presenting a non-centralized way to represent and contextualize real-world concepts, unambiguously, for several areas of knowledge. Semantic Web-enabled machines will handle information at our communication level. It is clear that the ability to interpret reality is still very primitive, however, Semantic Web points a way towards machine interaction and learning (Pereira et al., 2005). Semantic Web will integrate, interact with, and bring benefits to most human activities. Its full potential will go beyond the Web to real-world machines, providing increased interaction between machines and with humans—smarter phones, radios, and other electronic devices. Semantic Web will bring a different kind of approach in the understanding of reality by the machines and will constitute a mark in the evolution of human knowledge (Pereira et al., 2005).