Ontology-based Service Research Articles

Ontology-Based Service Level Agreements for Cloud Services and Cloud Security

Bulut bilişim, günümüzdeki en önemli teknolojik gelişim ve dönüşümlerinden biri olarak kabul edilmektedir. Bu teknolojinin gelişmesi ile veri tabanı servislerinin, sunucu ve depolama hizmetlerinin yönetimi ve kullanımı kolaylaşmış ve daha düşük maliyetler ile gerçekleştirilebilir bir hale gelmiştir. Son kullanıcılardan büyük ölçekli işletmelere kadar geniş bir kullanıcı kitlesine sahip olan bulut bilişimin popülerleşmesi bulut güvenliği kaygılarını da beraberinde getirmektedir. Farklı bulut servislerinin farklı hizmet katmanlarını karşılaması, atak yüzeylerinin geleneksel yöntemlerden çok daha fazla olması gibi sebepler, bulut güvenliğinin yönetimini zorlaştırmaktadır. Bulut servislerinin yönetimini ve bulut güvenliğini sağlamak amacı ile, bulut hizmetleri kullanıcılarının ve bulut sağlayıcılarının hizmetlerin güvenlik, kullanılabilirlik, yanıt verme düzeyleri gibi kritik özellikleri garanti eden Hizmet Düzeyi Sözleşmeleri (Service Level Agreements, SLAs) bulunur. Bu sözleşmelere uyumluluk ve sözleşme ihlallerin kontrolü üzerine bulut servisleri ve bulut güvenliği için geliştirilen ontoloji yapısı, bulut servisleri ve bulut güvenliği kavramlarının arasındaki ilişkileri tanımlamaktadır. Bu ontolojik tanımlama, SLA’ların daha iyi anlaşılmasını, yönetilmesini ve sürekli kontrol için otomasyonunu sağlamaktadır. Bu çalışmada, bulut servisleri ve bulut güvenliği kapsamında geliştirilen SLA ontolojileri üzerine kapsamlı bir araştırma ve inceleme sunulmaktadır. Gerçekleştirilen çalışma sonucunda, alandaki mevcut durum ve yaklaşımlar incelenerek kullanılan teknolojiler ve gelecek çalışmalara yönelik fırsatlar değerlendirilmektedir.

Ontology-based services for software vulnerability detection: a survey

Ontologies, as formal specifications of conceptualisation, are widely used in software engineering to manage software development, maintenance and security concerns. Recently, some ontology services were proposed for software vulnerability detection and showed to be effective. Some could detect more bugs compared to static analysis tools; some could predict hidden bugs based on ontology reasoning. In this paper, we review existing ontology-based services for vulnerability detection techniques, describe their main ideas and design principles, and provide background knowledge for further research in this area.

Implementation of Ontology-based Service by Exploiting Massive Crime Investigation Records: Focusing on Intrusion Theft

Implementation of Ontology-based Service by Exploiting Massive Crime Investigation Records: Focusing on Intrusion Theft

SIFR annotator: ontology-based semantic annotation of French biomedical text and clinical notes

BackgroundDespite a wide adoption of English in science, a significant amount of biomedical data are produced in other languages, such as French. Yet a majority of natural language processing or semantic tools as well as domain terminologies or ontologies are only available in English, and cannot be readily applied to other languages, due to fundamental linguistic differences. However, semantic resources are required to design semantic indexes and transform biomedical (text)data into knowledge for better information mining and retrieval.ResultsWe present the SIFR Annotator (http://bioportal.lirmm.fr/annotator), a publicly accessible ontology-based annotation web service to process biomedical text data in French. The service, developed during the Semantic Indexing of French Biomedical Data Resources (2013–2019) project is included in the SIFR BioPortal, an open platform to host French biomedical ontologies and terminologies based on the technology developed by the US National Center for Biomedical Ontology. The portal facilitates use and fostering of ontologies by offering a set of services –search, mappings, metadata, versioning, visualization, recommendation– including for annotation purposes. We introduce the adaptations and improvements made in applying the technology to French as well as a number of language independent additional features –implemented by means of a proxy architecture– in particular annotation scoring and clinical context detection. We evaluate the performance of the SIFR Annotator on different biomedical data, using available French corpora –Quaero (titles from French MEDLINE abstracts and EMEA drug labels) and CépiDC (ICD-10 coding of death certificates)– and discuss our results with respect to the CLEF eHealth information extraction tasks.ConclusionsWe show the web service performs comparably to other knowledge-based annotation approaches in recognizing entities in biomedical text and reach state-of-the-art levels in clinical context detection (negation, experiencer, temporality). Additionally, the SIFR Annotator is the first openly web accessible tool to annotate and contextualize French biomedical text with ontology concepts leveraging a dictionary currently made of 28 terminologies and ontologies and 333 K concepts. The code is openly available, and we also provide a Docker packaging for easy local deployment to process sensitive (e.g., clinical) data in-house (https://github.com/sifrproject).

An ontology-based cloud infrastructure service discovery and selection system

In recent years, due to global economic downfall, many of the organisations have resorted to downsizing their Information Technology (IT) expenses by adopting innovative computing models like cloud computing, which allows business houses to reduce their fixed IT costs by promising a greener, scalable, cost-effective alternative to utilise the IT resources. A growing number of pay-per-use cloud services are now available on the web in the form of Software as a Service (SaaS), Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). With the increase in the number of services, there has also been an increase in demand and adoption of cloud services making cloud service identification and discovery a challenging task. This is due to varied service, descriptions, non-standardised naming conventions, heterogeneity in type and features of cloud services. Thus, selecting an appropriate cloud service according to consumer requirements is a daunting task, especially for applications that use a composition of different cloud services. In this paper, we have designed an ontology-based cloud infrastructure service discovery and selection system that defines functional and non-functional concepts, attributes and relations of infrastructure services. We have shown how the system enables one to discover appropriate services optimally as requested by consumers.

Ontology-Based Human-Computer Cloud for Decision Support

A variety of information processing and decision support tasks (especially in the context of smart city or smart tourist destination) rely both on the automated and human-based procedures. The article proposes a multi-layer cloud environment that, first, unifies various kinds of resources used by these information processing and decision-support scenarios (hardware, software, and human), and second, implements an ontology-based automatic service composition procedures that can be used to build ad hoc decision-support services for problems unknown in advance. The service composition is based on uniform description of all parts of the environment with a help of ontologies. The article describes the architecture and models of the novel human-computer cloud environment. It also describes several scenarios of decision support in tourism leveraging the proposed human-computer cloud concept.

Automatic cloud service monitoring and management with prediction-based service provisioning

As the number of users is increasing day by day over the cloud environment, service providers might be unable to offer service as per the agreement. Hence, cloud services being offered should be monitored to detect service level agreement violation. Most existing cloud service monitoring frameworks are developed to support the service provider only, which raises the question of correctness and fairness. On the other hand, if monitoring is applied at user side, then it creates overhead to the clients. To manage such issue, ontology-based automatic cloud services monitoring and management with prediction-based service provisioning approach is proposed in this paper. In this approach, monitoring is performed at cloud broker, which is an intermediate entity between the user and service provider. When service level agreement violation is detected, it sends alert to both clients and service providers, and broker automatically reschedules the tasks to reduce the further violations.

Planteome: ontology-based services for querying and mining plant genomic and phenomic data

Planteome: ontology-based services for querying and mining plant genomic and phenomic data

Mission-oriented service development using capability-based semantic recommendation for the internet of things

This paper presents a mission-oriented service development environment with web-based modeling tool that enable users create workflow-based service composition. This approach utilizes the ontology-based mission service model composed of mission, task, service and resource, and task/service recommendation. During developing the mission-oriented service, capability-based semantic matching and hierarchical relationship-based filtering are used for three types of recommendation. Also, we develop a modeling environment to monitor and execute the mission service application. In experiments, we have conducted on test beds in two domains such as military environment and smart building.

Ontology-based web services classification for registration and discovery of web services

Web services become increasingly important in the world of internet. Thus, users need to access and effectively share web services. The centralised UDDI is a less robust structure and does not support a large number of web services. If the distributed environment is introduced into the UDDI, there will be a rapid increase in services with minimisation of resource consumption. Accordingly, mechanisms are needed for efficient selection of the appropriate instance of the web service in terms of factors like quality and performance. Distribution mechanisms, clustering and classification are necessary for efficient selection of the appropriate web service to the customer needs. In this paper, we propose a shared repository (ontology) which is produced by clustering of web services. This ontology can be exploited by the UDDI for publishing and discovering web services. A matching algorithm is also proposed to show how to perform this operation. A prototype tool has been developed to support experiments that have been carried out to evaluate and show the efficiency of our matching algorithm. We also introduce a comparative analysis to show the effectiveness of our approach compared to existing works.

AgroPortal : A Proposition for Ontology-Based Services in the Agronomic Domain

Our project is to develop and support a reference ontology repository for the agronomic domain. By reusing the NCBO BioPortal technology, we have already designed and implemented a prototype ontology repository for plants and a few crops. We plan to turn that prototype into a real service to the community. The AgroPortal project aims at reusing the scientific outcomes and experience of the biomedical domain in the context of plant, agronomic and environment sciences. We will offer an ontology portal which features ontology hosting, search, versioning, visualization, comment, but we will also offer services for semantically annotating data with the ontologies, as well as storing and exploiting ontology alignments and data annotations. All of these within a fully semantic web compliant infrastructure. The main objective of this project is to enable straightforward use of agronomic related ontologies, avoiding data managers and researchers the burden to deal with complex knowledge engineering issues to annotate the research data. The AgroPortal project will specifically pay attention to respect the requirements of the agronomic community and the specificities of the crop domain. We will first focus on the outputs of a few existing driving agronomic use cases related to rice and wheat, with the goal of generalizing to other Crop Ontology related use cases. AgroPortal will offer a robust and stable platform that we anticipate will be highly valued by the community.

Capability-based semantic matching for dynamic resource allocation in tactical edge environment

There are technological, operational, and environmental constraints at tactical edge, which are disconnected operation, intermittent connectivity, and limited bandwidth, size, weight and power limitations, ad-hoc and mobile network, and so on. Moreover, an operational environment is highly dynamic: requirements change in response to the emerging situation, and the availability of resources needs to be updated constantly due to the factors, such as technical failures. Therefore, an efficient matching mechanism is required that considers all possible criteria to achieve a mission. In this paper, we proposed an ontology-based mission service model that consists of a mission, tasks, services, and resources, and developed a capability-based matching mechanism in tactical edge environment. In addition, we have developed a prototype that supports dynamic resource allocation during executing a mission in tactical edge.

Services and a Distributed Ecosystem for Supporting Mobile Medical Application Development

The main objective of this paper is to provide novel methods facilitating an efficient access and reuse of healthcarerelated data sources within a large scalable and reliable infrastructure, so called ecosystem of ontology-based services which reflect big data and specific patient care. This task focuses on developing ontology-based services for gathering outputs from the various data sources (portable wearable devices, the EHR data, clinical notes, claims, medical imaging data, etc.), that are used in various applied fields of mHealth, and on creating management technology for provision of interconnected healthcare-related data sources and processing procedures. The developed services are the main ‘building blocks’ for more complex applications that use some medical data processing scenarios. To hide the low-level details of the service orchestration mechanism, an automated ontology-based workflow management engine is introduced, that will allow expressing various data processing workflows in the abstract terms of the ‘glue’ high-level ontology rather than in low-level details of interaction different services.

Expert selection service system by fuzzy ontology modelling

Classical ontology is insufficient for handling vague and imprecise information. To deal with this problem, a four-layered structure of fuzzy domain ontology based on fuzzy logic theory is designed to extend classical domain ontology in this paper. Fuzzy concepts, fuzzy properties and fuzzy memberships are defined in the fuzzy domain ontology to describe knowledge with uncertainty based on semantics. Applying this four-layered extended structure of fuzzy domain ontology, expert fuzzy ontology in the domain of science and technology evaluation is developed, and expert selection algorithm based on fuzzy ontology is designed to realise expert selection service according to selection requirements with vague and imprecise semantics. The practical application results show that semantic expert selection service can not only work more efficiently and accurately for expert selection than keyword-based expert selection service and classical ontology-based expert selection service, but also provide decision support for it.

A semantically-aided architecture for a web-based monitoring system for carotid atherosclerosis.

Carotid atherosclerosis is a multifactorial disease and its clinical diagnosis depends on the evaluation of heterogeneous clinical data, such as imaging exams, biochemical tests and the patient's clinical history. The lack of interoperability between Health Information Systems (HIS) does not allow the physicians to acquire all the necessary data for the diagnostic process. In this paper, a semantically-aided architecture is proposed for a web-based monitoring system for carotid atherosclerosis that is able to gather and unify heterogeneous data with the use of an ontology and to create a common interface for data access enhancing the interoperability of HIS. The architecture is based on an application ontology of carotid atherosclerosis that is used to (a) integrate heterogeneous data sources on the basis of semantic representation and ontological reasoning and (b) access the critical information using SPARQL query rewriting and ontology-based data access services. The architecture was tested over a carotid atherosclerosis dataset consisting of the imaging exams and the clinical profile of 233 patients, using a set of complex queries, constructed by the physicians. The proposed architecture was evaluated with respect to the complexity of the queries that the physicians could make and the retrieval speed. The proposed architecture gave promising results in terms of interoperability, data integration of heterogeneous sources with an ontological way and expanded capabilities of query and retrieval in HIS.

An ontology-based semantic configuration approach to constructing Data as a Service for enterprises

To align business strategies with IT systems, enterprises should rapidly implement new applications based on existing information with complex associations to adapt to the continually changing external business environment. Thus, Data as a Service (DaaS) has become an enabling technology for enterprise through information integration and the configuration of existing distributed enterprise systems and heterogonous data sources. However, business modelling, system configuration and model alignment face challenges at the design and execution stages. To provide a comprehensive solution to facilitate data-centric application design in a highly complex and large-scale situation, a configurable ontology-based service integrated platform (COSIP) is proposed to support business modelling, system configuration and execution management. First, a meta-resource model is constructed and used to describe and encapsulate information resources by way of multi-view business modelling. Then, based on ontologies, three semantic configuration patterns, namely composite resource configuration, business scene configuration and runtime environment configuration, are designed to systematically connect business goals with executable applications. Finally, a software architecture based on model-view-controller (MVC) is provided and used to assemble components for software implementation. The result of the case study demonstrates that the proposed approach provides a flexible method of implementing data-centric applications.

Towards a framework for ontology-based information retrieval services

In this paper, we present a complete ontology-based framework for the extraction and retrieval of semantic information in specific domains. We focus on the recognition of semantic information extracted from data sources and the mapping of this knowledge into ontology. In order to achieve more scalability, we propose an approach for semantic indexing based on entity retrieval model. The proposed approach was validated using an example of ontology in public transportation domain. Finally, we evaluated our system using ontology mapping and real world data sources. Experiment results show that our proposed framework can provide meaningful search results.

The Extended Algorithm of the Bipartite Graph Matching Semantic Web Service Discovery

In previous work, the ontology-based algorithm of bipartite graph matching semantic web service discovery was presented. But in these algorithms, the problem of finding augment path was not resolved very well. It will affect the recall rate and precision rate of web service discovery. In order to resolve these problems, this paper proposes an ontology-based bipartite graph matching semantic web service discovery algorithm, which extends the optimal bipartite graph matching algorithm. It uses the slack function to find the augment path in the equivalent sub graph. The algorithm also contributes to the improvement of the recall rate and precision rate of the service discovery.

Reliability Prediction of Ontology-Based Service Compositions Using Petri Net and Time Series Models

OWL-S, one of the most important Semantic Web service ontologies proposed to date, provides a core ontological framework and guidelines for describing the properties and capabilities of their web services in an unambiguous, computer interpretable form. Predicting the reliability of composite service processes specified in OWL-S allows service users to decide whether the process meets the quantitative quality requirement. In this study, we consider the runtime quality of services to be fluctuating and introduce a dynamic framework to predict the runtime reliability of services specified in OWL-S, employing the Non-Markovian stochastic Petri net (NMSPN) and the time series model. The framework includes the following steps: obtaining the historical response times series of individual service components; fitting these series with a autoregressive-moving-average-model (ARMA for short) and predicting the future firing rates of service components; mapping the OWL-S process into a NMSPN model; employing the predicted firing rates as the model input of NMSPN and calculating the normal completion probability as the reliability estimate. In the case study, a comparison between the static model and our approach based on experimental data is presented and it is shown that our approach achieves higher prediction accuracy.

A Petri-Net-Based Approach to Reliability Determination of Ontology-Based Service Compositions

Ontology Web Language for Services (OWL-S), one of the most significant semantic Web service ontologies proposed to date, provides a core ontological framework and guidelines for describing the properties and capabilities of services in an unambiguous computer-interpretable form. Analysis of the quality of service of composite service processes specified in OWL-S enables service users to decide whether the process meets nonfunctional requirements. In this paper, we propose a probabilistic approach for reliability analysis of OWL-S processes, employing the non-Markovian stochastic Petri net (NMSPN) as the fundamental model. Based on the NMSPN representations of the OWL-S elements, we introduce an analytical method for the calculation of the process-normal-completion probability as the reliability estimate. This method takes the probabilistic parameters of service invocations and messages as model inputs. To validate the feasibility and accuracy of our approach, we obtain runtime experimental data and conduct a confidence interval analysis in a case study. A sensitivity analysis is also performed to determine the impact of model parameters on reliability and to help identify the reliability bottlenecks.