Semantic Services Research Articles

Logic and Event Based Semantic Relationship Evolution in Service Semantic Link Network

To facilitate reasoning and predicting service evolution relationships with incomplete, partial or uncertain knowledge for supporting an intelligent service application and to preserve the relationship consistency in the whole service networks during Web service evolution processes over time. An approach was presented for event-based relationships evolution detection and reasoning among web services by combining first-order logic and probabilistic graphical models in a single representation. The Web service relationship evolution model was constructed by using available probability information and knowledge based on the related event and their inherent service relationship dependencies. And S-MLN was taken as a logical framework for Web service relationships evolution reasoning with uncertainty to discover and predict evolutionary service relationship classification. The events and evolutionary measures of the research were found to be helpful for evaluating Web service evolution relationships. And it is effective to evaluate the quality of service set classification by SMLN based evolution relationships prediction. The study identifies the theoretical foundations of web service evolution discovery in the context of SLN. This study, based on an established theoretical foundation, will help the research community to gain a deeper understanding of the dynamic relationship in the semantic context of the web services network.

SERNOTATE: An automated approach for business service description annotation for efficient service retrieval and composition

SummaryBusiness service advertisements are today published online to convey essential information about services to customers. However, current Web search engines are unable to search and combine online service advertisements. Semantic service annotation is important for its ability to enable machines to understand the meaning of services and support in effective service retrieval and service composition. Existing research in the area of semantic service annotation has focused on the annotation of Web services in a semi‐automated approach. It cannot be applied to business service information as it is not in the form of Web Services Description Language but in free text format. Moreover, semi‐automated approaches are inappropriate for annotating a large amount of online service information which changes dynamically and they are therefore not suitable for the timely dissemination of service information to customers. To solve these issues, we propose SERNOTATE, which is an automated approach for business service description annotation for efficient service retrieval and composition. We propose new semantic‐based linking approaches, namely, Extended Case‐based Reasoning, vector‐based, and classification‐based, that automatically annotate business services to relevant service concepts. Each approach assists in the single‐label and multi‐label annotation of service terms to concept terms to provide a better representation of services. The experimental results test and validate the applicability of the proposed approaches to the automatic annotation of business service descriptions to service concepts on a real‐world dataset.

E-Government for Lowering Administrative Burden: An Empirical Research on European Rural Businesses

ABSTRACTAdministrative burden reduction is in the policy agenda in European countries and international organizations. The objectives of this article are to measure administrative burden of rural businesses in three European case studies and to assess the use of semantic electronic government services for its reduction. The main findings are that rural businesses do not perceive the administrative burden significance for entrepreneurship; public administration could implement semantic electronic government services to reduce rural businesses’ administrative burden; and future administrative burden reduction policies should take into account the type and location of businesses to achieve an efficient business environment.

Возможности использования семантических информационных сервисов в музейном деле (на примере Музея истории ПетрГУ)

<p>В статье представлен авторский подход к развитию Музея истории Петрозаводского государственного университета на основе такого вида цифровых услуг для посетителей и музейных работников, как семантические информационные сервисы. Мотивом к реализации семантических сервисов в деятельности музея стала необходимость контекстного поиска информации в музейном фонде, а также использования потенциала посетителей в пополнении фонда ранее не задействованной в экспозиции информацией и новыми экспонатами, в том числе в электронном виде. </p><p>Предложены сценарии использования сервисов, показывающие, какую информационную поддержку можно обеспечить в музее для: 1) отбора экспонатов для новых экспозиций, 2) персонализированного предоставления информации об экспонатах посетителю, 3) получения от посетителей музея новой информации о хранимых музейных экспонатах, 4) пополнения фонда музея за счет новых экспонатов в электронном виде, полученных от посетителей.</p><p>Основой предлагаемых сервисов является создаваемая в музее семантическая сеть, объединяющая как сами экспонаты музейного фонда, так и иные информационные объекты, связанные с конкретными экспонатами и историей университета и образования в целом. Особым вниманием при создании онтологии семантической сети пользуются у авторов информационные объекты, связанные с повседневной жизнью университетского сообщества.</p><p>Представленный подход может быть интересен не только музейным работникам, но и профессиональным исследователям, заинтересованным в получении и изучении новых фактов из истории повседневной жизни образовательно-научной организации. <strong></strong></p>

Semantic service provisioning for smart objects: Integrating IoT applications into the web

Internet of Things (IoT) applications residing on the Web are the next logical development of the recent effort from academia and industry to design and standardize new communication protocols for smart objects. This paper proposes the service provisioning architecture for smart objects with semantic annotation to enables the integration of IoT applications into the Web. We aim to bring smart object services to the Web and make them accessible by plenty of existing Web APIs in consideration of its constraints such as limited resources (ROM, RAM, and CPU), low-power microcontrollers, and low-bitrate communication links.

Adaptive and context-aware service composition for IoT-based smart cities

Smart Cities are advancing towards an instrumented, integrated, and intelligent living space, where Internet of Things (IoT), mobile technologies and next generation networks are expected to play a key role. In smart cities, numerous IoT-based services are likely to be available and a key challenge is to allow mobile users perform their daily tasks dynamically, by integrating the services available in their vicinity. Semantic Service Oriented Architectures (SSOA) abstract the environment’s services and their functionalities as Semantic Web Services (SWS). However, existing service composition approaches based on SSOA do not support dynamic reasoning on user tasks and service behaviours to deal with the heterogeneity of IoT domains. In this paper, we present an adaptive service composition framework that supports such dynamic reasoning. The framework is based on wEASEL, an abstract service model representing services and user tasks in terms of their signature, specification (i.e., context-aware pre-conditions, post-conditions and effects) and conversation (i.e., behaviour with related data-flow and context-flow constraints). To evaluate our composition framework, we develop a novel OWLS-TC4-based testbed by combining simple and composite services. The evaluation shows that our wEASEL-based system performs more accurate composition and allows end-users to discover and investigate more composition opportunities than other approaches.

Towards Ontological Approach on Trust-Aware Ambient Services

With various information sources (e.g., from IoT sensors to social media), it is difficult to provide users with trustworthy services in ambient environment. The aim of this paper is $i$ ) to design trust ontology for representing semantics of the ambient services and $ii$ ) to compute trust measures among users by using a personalized trust ontology. In particular, given a large amount of data collected from ambient sensors, efficient trust computation and reasoning are required for the stability and reliability. Thereby, we propose trust ontology-based framework for deriving personalized ontologies for individual users according to their preference, perspective, and purpose. To evaluate the proposed model, we have figured out a method how the degree of trust is estimated based on the trust ontology. Furthermore, we have proved that the proposed method is reliable with a case study on a social media (Twitter) for a particular domain (restaurant).

A novel service discovery algorithm via service repository centre in internet of things

In recent years, the internet of things (IoT) has attracted more and more attention, and IoT services have increased rapidly. The service discovery which has important implications for the service integration of IoT services has become more difficult in large-scale registration. In traditional matching method, in order to get a better match results, all the matching parameters for services had to be calculated together, thus it would waste a lot of computing resources and computing time. This paper propose a centralise four-layer model for service discovery via multi-stage semantic service matching to improve the performance of service discovery, namely interactive interface layer, parsing annotation layer, service matching layer and data semantic layer, so as to meet the requirement of service discovery in large-scale IoT services. We also propose a hybrid service matching degree measurement by synthetically calculating the concept logic and semantic similarity for each layer singly. Experimental analysis confirms the effectiveness of the proposed mechanism in improving the precision and recall.

A novel service discovery algorithm via service repository centre in internet of things

In recent years, the internet of things (IoT) has attracted more and more attention, and IoT services have increased rapidly. The service discovery which has important implications for the service integration of IoT services has become more difficult in large-scale registration. In traditional matching method, in order to get a better match results, all the matching parameters for services had to be calculated together, thus it would waste a lot of computing resources and computing time. This paper propose a centralise four-layer model for service discovery via multi-stage semantic service matching to improve the performance of service discovery, namely interactive interface layer, parsing annotation layer, service matching layer and data semantic layer, so as to meet the requirement of service discovery in large-scale IoT services. We also propose a hybrid service matching degree measurement by synthetically calculating the concept logic and semantic similarity for each layer singly. Experimental analysis confirms the effectiveness of the proposed mechanism in improving the precision and recall.

소비자 네트워킹 환경에서의 사용자 주도 서비스의 효율적 생성

Web 2.0 환경에서, 사용자는 사용자 (또는 소비자)와 개발자 (또는 제작자) 간의 실시간 상호 작용을 허용하는 수많은 스마트 장치 및 서비스에 노출되고 사용하게 된다. 사용자 컨텍스트 기반의 새로운 사용자 생성 서비스를 제공하기 위해서 서비스 생성 경험의 관리는 매우 중요하다. 본 논문에서는 서비스 작성을 위한 확장된 데이터 모델을 소개하고, 이 데이터 모델에 기반한 신규 서비스 생성, 서비스 생성 데이터의 관리, 그리고 내/외부 서비스 저장소에 대한 의미적 검색을 가능하게 하는 서비스 생성 관리 아키텍처를 제안한다. 또한, 홈 환경과 모바일 환경에 걸친 두 가지 시나리오를 사용하여 제안 아키텍처를 사용하는 방법에 대해서도 설명하며, 서비스 생성 데이터 관리를 위해 제안한 아키텍처는 서비스 생명주기 동안의 서비스 생성 데이터를 일관성 있게 관리할 수 있다. In a Web 2.0 context, users are exposed to numerous smart devices and services that allow real-time interaction between users (or consumers) and developers (or producers). For the provisioning of new user-created services based on user's context, the data management of service creation experiences becomes a non-trivial task. This article introduces a data model for service creation and then proposes a service creation management architecture which enables new service creation using the data model, the management of the service creation data, and the semantic service discovery across internal/external service repositories. The article also explains the use of the proposed architecture with two different scenarios: home and mobile environments. The proposed architecture for service creation data management offers consistent and seamless handling of the service creation data throughout its usage lifecycle.

Semantic Agent-Based Service Middleware and Simulation for Smart Cities.

With the development of Machine-to-Machine (M2M) technology, a variety of embedded and mobile devices is integrated to interact via the platform of the Internet of Things, especially in the domain of smart cities. One of the primary challenges is that selecting the appropriate services or service combination for upper layer applications is hard, which is due to the absence of a unified semantical service description pattern, as well as the service selection mechanism. In this paper, we define a semantic service representation model from four key properties: Capability (C), Deployment (D), Resource (R) and IOData (IO). Based on this model, an agent-based middleware is built to support semantic service enablement. In this middleware, we present an efficient semantic service discovery and matching approach for a service combination process, which calculates the semantic similarity between services, and a heuristic algorithm to search the service candidates for a specific service request. Based on this design, we propose a simulation of virtual urban fire fighting, and the experimental results manifest the feasibility and efficiency of our design.

Semantics-based Web service classification using morphological analysis and ensemble learning techniques

With the emergence of the Programmable Web paradigm, the World Wide Web is evolving into a Web of Services, where data and services can be effectively reused across applications. Given the wide diversity and scale of published Web services, the problem of service discovery is a big challenge for service-based application development. This is further compounded by the limited availability of intelligent categorization and service management frameworks. In this paper, an approach that extends service similarity analysis by using morphological analysis and machine learning techniques for capturing the functional semantics of real-world Web services for facilitating effective categorization is presented. To capture the functional diversity of the services, different feature vector selection techniques are used to represent a service in vector space, with the aim of finding the optimal set of features. Using these feature vector models, services are classified as per their domain, using ensemble machine learning methods. Experiments were performed to validate the classification accuracy with respect to the various service feature vector models designed, and the results emphasize the effectiveness of the proposed approach.

Service Discovery in Mobile Ad-Hoc Networks of Android OS Devices

ad-hoc networks have been deployed for communication where infrastructure based communications are not available (or desirable). Android OS ad-hoc networks can be employed in development of collaborative applications such as entertainment systems and mobile gaming. In addition, they facilitate ubiquitous computing in areas such as home applications where wireless sensors and actuators are embedded in consumer electronics. This paper presents an implementation of Service Discovery middleware for Android Mobile ad-hoc networks. The implementation overlays a Mobile Ad-hoc Network implementation. It further describes a routing implementation that is based on the Ad-hoc On-Demand Distance Vector protocol, with modifications to reduce control message overhead. An implementation of a Semantic approach for description of services on mobile devices, that facilitates semantic service discovery in Android OS Mobile Ad Hoc Networks is also presented. The implementation was tested by simulating the routing implementation. An Android based prototype was developed and tested on a range of devices.

Integration for Heterogeneous Manufacturing Information Systems Based on Semantic Entity

To support semantic integration for heterogeneous information systems in manufacturing enterprises, based on semantic gateway, the concept of semantic entity is defined, and the semantic entity-based integration method is studied. Semantic entity sets up conceptual structure by aggregating semantic concept from semantic gateway, and builds dynamic conceptual structure through adding or removing its general concept. By means of key business data, semantic entity identifies business object and obtains business data from its application system, and then instantiates concept structure. Based on instantiation, semantic service can obtain parameters data from business object instant, and satisfies the interface contract. Semantic entity captures data changes of business object, and then establishes status-based integration rules, defines algorithm logic of rules. By instantiating concept structure aimed to specific application system and invoking semantic service, the integration activities among information systems come true. This work has been verified by prototype system, and attained expected integration effect.

BlogSearch: Semantic Services for Aggregating and Searching Blog Articles

The advent of new web technologies and the explosion of available information online led to an information overload. During this information revolution blogs have become considerably mainstream as a media of providing news. Although there are several arguments about their validity and credibility the large amount of blogs currently available require the usage of advanced techniques for the collection, analysis, mining and efficient querying of the available information. To this direction we present BlogSearch, a novel platform allowing aggregating, indexing and searching blog articles. The information is modelled using a novel RDF/S Ontology named Blogs Ontology and published as Linked Open Data. In addition, two sets of APIs are provided for inserting, updating and searching information whereas the platform provides also graphical user interfaces (GUIs) for searching and inserting information. To the best of our knowledge our platform is the only one currently available publishing blog articles as Linked Open Data and simultaneously providing APIs and GUIs for aggregating, inserting and searching articles.

The MASSIF platform: a modular and semantic platform for the development of flexible IoT services

In the Internet of Things (IoT), data-producing entities sense their environment and transmit these observations to a data processing platform for further analysis. Applications can have a notion of context awareness by combining this sensed data, or by processing the combined data. The processes of combining data can consist both of merging the dynamic sensed data, as well as fusing the sensed data with background and historical data. Semantics can aid in this task, as they have proven their use in data integration, knowledge exchange and reasoning. Semantic services performing reasoning on the integrated sensed data, combined with background knowledge, such as profile data, allow extracting useful information and support intelligent decision making. However, advanced reasoning on the combination of this sensed data and background knowledge is still hard to achieve. Furthermore, the collaboration between semantic services allows to reach complex decisions. The dynamic composition of such collaborative workflows that can adapt to the current context, has not received much attention yet. In this paper, we present MASSIF, a data-driven platform for the semantic annotation of and reasoning on IoT data. It allows the integration of multiple modular reasoning services that can collaborate in a flexible manner to facilitate complex decision-making processes. Data-driven workflows are enabled by letting services specify the data they would like to consume. After thorough processing, these services can decide to share their decisions with other consumers. By defining the data these services would like to consume, they can operate on a subset of data, improving reasoning efficiency. Furthermore, each of these services can integrate the consumed data with background knowledge in its own context model, for rapid intelligent decision making. To show the strengths of the platform, two use cases are detailed and thoroughly evaluated.

Automated knowledge discovery and semantic annotation for network and web services

With the rise of the Internet of things, the smart environmental issue is becoming increasingly important. Sensor web is one of the best solutions to this issue and provides the advantages of sensor networks and web services. Ontology web language for services (OWL-S) is an OWL-based web services ontology, which provides the ability to describe the semantics of web services and their capabilities in a formal and machine-processable manner. Moreover, it aids semantic service matching, selection and composition. However, automatically annotating semantic web services is a highly complicated and tedious task. In this study, we propose a methodology to uncover information in the history data and profiles of web services and then semantically annotate them. With the proposed approach, semantic relationships between web services could be extracted via a combination of association rules and input/output matching. Our results show that this hybrid automated knowledge-discovery approach works better than traditional approaches do. We also provide a scenario to explain how the proposed methodology works.

PRAGMATICS DRIVEN LAND COVER SERVICE COMPOSITION UTILIZING BEHAVIOR-INTENTION MODEL

Web service composition is one of the key issues to develop a global land cover (GLC) information service portal. Aiming at the defect that traditional syntax and semantic service compositionare difficult to take pragmatic information into account, the paper firstly analyses three tiers of web service language and their succession relations, discusses the conceptual model of pragmatic web service, and proposes the idea of pragmatics-oriented adaptive composition method based on the analysis of some examples. On this basis it puts forward the pragmatic web service model based on Behavior-Intention through presetting and expression of service usability, users' intention, and other pragmatic information, develops the on-demand assembly method based on the agent theory and matching and reconstruction method on heterogeneous message, solves the key technological issue of algorithm applicability and heterogeneous message transformation in the process of covering web service composition on the ground, applies these methods into service combination, puts forward the pragmatic driven service composition method based on behavior-intention model, and effectively settles the issue of coordination and interaction of composite service invocation.

PRAGMATICS DRIVEN LAND COVER SERVICE COMPOSITION UTILIZING BEHAVIOR-INTENTION MODEL

Abstract. Web service composition is one of the key issues to develop a global land cover (GLC) information service portal. Aiming at the defect that traditional syntax and semantic service compositionare difficult to take pragmatic information into account, the paper firstly analyses three tiers of web service language and their succession relations, discusses the conceptual model of pragmatic web service, and proposes the idea of pragmatics-oriented adaptive composition method based on the analysis of some examples. On this basis it puts forward the pragmatic web service model based on Behavior-Intention through presetting and expression of service usability, users' intention, and other pragmatic information, develops the on-demand assembly method based on the agent theory and matching and reconstruction method on heterogeneous message, solves the key technological issue of algorithm applicability and heterogeneous message transformation in the process of covering web service composition on the ground, applies these methods into service combination, puts forward the pragmatic driven service composition method based on behavior-intention model, and effectively settles the issue of coordination and interaction of composite service invocation.

A Semantic Registry Method Using Sensor Metadata Ontology to Manage Heterogeneous Sensor Information in the Geospatial Sensor Web

Efficient information management and precise discovery of heterogeneous sensors in the Geospatial Sensor Web (GSW) are a major challenge. Intelligent sensor management requires a registry service to store and process sensor information efficiently. In this paper, we propose a Sensor Metadata Ontology (SMO) to achieve a unified semantic description for heterogeneous sensors that is used to express sensor semantics. Through mapping between the sensor registry information model and the SMO, the sensor metadata could be stored with semantic information for the registry. The framework of a Sensor Semantic Registry Service (SSRS) has been successfully implemented for the registration and discovery of heterogeneous sensors. The results of GEOSENSOR-SSRS experiments show that the proposed semantic registry method can be used to enable sharing in an open distributed sensor network as well as to promote accuracy and efficiency of discovery.