Abstract:Today, the Internet of Things (IoT) is comprised of vertically oriented platforms for things. Developers who want to use them need to negotiate access individually and need to adapt to the platform-specific API and information models. Having to do these efforts for each platform often outweighs the possible gains for application developers to adapt their applications to multiple platforms. This fragmentation of the IoT and the missing interoperability result in high entry barriers for developers and currently … Show more
“…To show the feasibility of our framework, together with the suitability of current UML/OCL reasoners to solve the matching problem, we have conducted some experiments with real data-services developed in the BIG IoT Project [1], where we participate and that has motivated the ideas proposed in this paper.…”
Section: Methodsmentioning
confidence: 99%
“…Regarding the context of IoT, the current proposals that we know for semantically describing IoT sensors to enable their discovery are not fully automatic [17,1,18]. The approach presented in [17] is meant for helping human users to find their desired semantically-described sensors through a GUI and, thus, it implements manual discovery.…”
Section: Related Workmentioning
confidence: 99%
“…The approach presented in [17] is meant for helping human users to find their desired semantically-described sensors through a GUI and, thus, it implements manual discovery. In the case of [1], and despite pursuing automatic discovery, for the moment its unique way to describe the input/output relation is by means of a single tag annotation, so, its discovery process is reduced to checking the coincidence of such tag, which is a syntactic check rather than a semantic one. On the other side, the proposal in [18], although it can be fully automated, is in essence based on selecting sensors according to non-functional criteria (e.g.…”
Section: Related Workmentioning
confidence: 99%
“…Additionally, smart objects can also be interested in consuming data coming from other external data-services, so that they can use it to take their smart decisions. This idea is being currently exploted in several european projects like, for instance, the BIG IoT European project [1].…”
Abstract. Note: This is a preprint version that deviates slightly from the published version of this paper. Data-services are applications in charge of retrieving certain data when they are called. They are found in different communities such as the Internet Of Things, Cloud Computing, Big Data, etc. So, there is a real need to discover how can an application that requires some data automatically find a data-service which is providing it. To our knowledge, the problem of automatically discovering these data-services is still open. To make a step forward in this direction, we propose an ontology-based framework to address this problem. In our framework, input and output values of the request are mapped into concepts of the domain ontology. Then, data-services specify how to obtain the output from the input by stating the relationship between the mapped concepts of the ontology.
“…To show the feasibility of our framework, together with the suitability of current UML/OCL reasoners to solve the matching problem, we have conducted some experiments with real data-services developed in the BIG IoT Project [1], where we participate and that has motivated the ideas proposed in this paper.…”
Section: Methodsmentioning
confidence: 99%
“…Regarding the context of IoT, the current proposals that we know for semantically describing IoT sensors to enable their discovery are not fully automatic [17,1,18]. The approach presented in [17] is meant for helping human users to find their desired semantically-described sensors through a GUI and, thus, it implements manual discovery.…”
Section: Related Workmentioning
confidence: 99%
“…The approach presented in [17] is meant for helping human users to find their desired semantically-described sensors through a GUI and, thus, it implements manual discovery. In the case of [1], and despite pursuing automatic discovery, for the moment its unique way to describe the input/output relation is by means of a single tag annotation, so, its discovery process is reduced to checking the coincidence of such tag, which is a syntactic check rather than a semantic one. On the other side, the proposal in [18], although it can be fully automated, is in essence based on selecting sensors according to non-functional criteria (e.g.…”
Section: Related Workmentioning
confidence: 99%
“…Additionally, smart objects can also be interested in consuming data coming from other external data-services, so that they can use it to take their smart decisions. This idea is being currently exploted in several european projects like, for instance, the BIG IoT European project [1].…”
Abstract. Note: This is a preprint version that deviates slightly from the published version of this paper. Data-services are applications in charge of retrieving certain data when they are called. They are found in different communities such as the Internet Of Things, Cloud Computing, Big Data, etc. So, there is a real need to discover how can an application that requires some data automatically find a data-service which is providing it. To our knowledge, the problem of automatically discovering these data-services is still open. To make a step forward in this direction, we propose an ontology-based framework to address this problem. In our framework, input and output values of the request are mapped into concepts of the domain ontology. Then, data-services specify how to obtain the output from the input by stating the relationship between the mapped concepts of the ontology.
“…The layer below the semantic models is responsible for the definition of messaging interfaces and supporting the abstraction of smart things. Past and ongoing initiatives for this layer are, for example, IoT-A 6 , the OGC SensorThings API 7 , and the BIGIoT API [13]. The open messaging standards called Open-Messaging Interface (O-MI) 8 and Open-Data Format (O-DF) 9 are used in the open ecosystem to achieve interoperability on the application layer.…”
Section: B Semantic Interoperability In the Iotmentioning
Abstract-A present challenge in today's Internet of Things (IoT) ecosystem is to enable interoperability across heterogeneous systems and service providers. Restricted access to data sources and services limits the capabilities of a smart city to improve social, environmental and economic aspects. Interoperability in the IoT is concerned with both, messaging interfaces and semantic understanding of heterogeneous data. In this paper, the first building blocks of an emerging open IoT ecosystem developed at the EU level are presented. Semantic web technologies are applied to the existing messaging components to support and improve semantic interoperability. The approach is demonstrated with a proof-of-concept for connected vehicle services in a smart city setting.
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