From Conceptual Structures to Semantic Interoperability of Content

Dobrev, Pavlin; Kalaydjiev, Ognian; Angelova, Galia

doi:10.1007/978-3-540-73681-3_15

Cited by 12 publications

(6 citation statements)

References 3 publications

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“…One can examine various interoperability levels [25][26][27][28][29], but since syntactic and semantic levels are particularly essential for data integration, we focus on these two levels. Syntactic interoperability is concerned with software infrastructure needed, whereas semantic level addresses the meaning of data while sharing or exchanging data between systems [30].…”

Section: Related Workmentioning

confidence: 99%

Semantic and Syntactic Interoperability for Agricultural Open-Data Platforms in the Context of IoT Using Crop-Specific Trait Ontologies

Aydın

2020

Applied Sciences

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In recent years, Internet-of-Things (IoT)-based applications have been used in various domains such as health, industry and agriculture. Considerable amounts of data in diverse formats are collected from wireless sensor networks (WSNs) integrated into IoT devices. Semantic interoperability of data gathered from IoT devices is generally being carried out using existing sensor ontologies. However, crop-specific trait ontologies—which include site-specific parameters concerning hazelnut as a particular agricultural product—can be used to make links between domain-specific variables and sensor measurement values as well. This research seeks to address how to use crop-specific trait ontologies for linking site-specific parameters to sensor measurement values. A data-integration approach for semantic and syntactic interoperability is proposed to achieve this objective. An open-data platform is developed and its usability is evaluated to justify the viability of the proposed approach. Furthermore, this research shows how to use web services and APIs to carry out the syntactic interoperability of sensor data in agriculture domain.

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Section: Related Workmentioning

confidence: 99%

Semantic and Syntactic Interoperability for Agricultural Open-Data Platforms in the Context of IoT Using Crop-Specific Trait Ontologies

Aydın

2020

Applied Sciences

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“…Also, they need to represent these resources using the same data representation format to be understandable for both applications. For example, using RDF, and OWL [13]. The size and scope of the learning resources (learning contents) that we can combine to a bigger content package is a key point to consider.…”

Section: Figure 1: Learning Contents Granularitiesmentioning

confidence: 99%

Learning Materials Representation for Interoperability in Heterogeneous Environment

2020

IJATCSE

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Learning resources are used for different learners and in different contexts along with heterogeneous environments. So, we need a way to enable automatic selection and compilation of these learning resources and adapt them to the target learner within these heterogeneous environments. This paper proposes using semantic web technologies and specially ontology in adaptive modeling of the learning resources to select the suitable material to the right learner in heterogeneous environment. We have implemented the ontology using Protégé 5.5.0. This proposed ontology model can help instructors and resource designers.

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“…It was firstly developed to be applied in military simulation systems within the U.S. Department of Defense but has been successfully applied in different domains as U.S. Department of Energy solutions for the power-grid [GridWise 2007]. Also, it was featured as a reference model in several contributions, such as [Tolk et al 2007], [Dobrev et al 2007], [Zeigler et al 2007] and [Morris et al 2004].…”

Section: Levels Of Conceptual Interoperability Model (Lcim)mentioning

confidence: 99%

Interoperability Requirement to Enhance Collaboration in Software Product Lines: A Systematic Mapping

Neiva¹,

Campos²,

David³

et al. 2016

Anais Do XIII Simpósio Brasileiro De Sistemas Colaborativos (SBSC 2016)

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[Background]: Software Product Lines (SPLs) have been widely discussed in literature as part of solution to build systems solutions in a collaborative way. Providing interoperability support is an essential requirement to achieve effective results in collaborative systems field. Despite the importance of interoperability in SPLs, research related to this field is scarce and scattered in literature. Fulfilling this requirement is not a trivial task and a mapping study about which interoperability solutions have been tackled in SPLs has not been done yet. [Goal]: This paper aims at identifying and classifying research related to interoperability in SPLs. [Method]: Conduct a systematic mapping to identify and classify SPL interoperability solutions. [Results]: The classifications showed that syntactic was the main addressed interoperability level and that architecture and variability issues were the focus of the SPL researches. [Conclusions]: The results have suggested that an expressive number of solutions related to the syntactic interoperability level were proposed. However, some challenges remain opened, such as providing higher interoperability level support, for example, regarding pragmatic, dynamic and conceptual interoperability solutions.

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From Conceptual Structures to Semantic Interoperability of Content

Cited by 12 publications

References 3 publications

Semantic and Syntactic Interoperability for Agricultural Open-Data Platforms in the Context of IoT Using Crop-Specific Trait Ontologies

Semantic and Syntactic Interoperability for Agricultural Open-Data Platforms in the Context of IoT Using Crop-Specific Trait Ontologies

Learning Materials Representation for Interoperability in Heterogeneous Environment

Interoperability Requirement to Enhance Collaboration in Software Product Lines: A Systematic Mapping

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