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Regional Digital Agendas for Healthcare

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Spatio-Temporal Composition of Sensor Cloud Services Semantic Web Service matchmakers: State of the art and A framework for discovering and classifying ubiquitous services in digital health ecosystemsJournal of.

With the constant growth of Internet of Things IoT ecosystems, allowing them to interact transparently has become a major issue for both the research and the software development communities. In this paper we propose a novel approach that builds semantically interoperable ecosystems of IoT devices. The approach was evaluated in order to prove that it provides complete and correct answers without affecting the response time and that it scales linearly in large ecosystems.

Discovery should enable context- and content-based searching i. A thorough analysis of the current proposals that address semantic interoperability for IoT ecosystems was presented by Zout et al. There are mainly two approaches for Web-available IoT devices based on the W3C standards that perform both context- and content-based searches: federation and centralised approaches. The centralised approaches deal with the heterogeneity of the devices by requiring them to periodically send data, which compromises the freshness of the information and requires practitioners to implement synchronization mechanisms.

“Semantic service matchmaking for Digital Health Ecosystems.”

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Dong, H., Hussain, F.K.: Semantic service matchmaking for digital health ecosystems. Knowl.-Based Syst. 24, – () 4. Dong, H., Hussain, F.K., Chang.

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The vision of Digital Ecosystems was initiated by the European Commission, with the purpose of constructing an information and.

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Towards certified open data in digital service ecosystems

Ecosystems that support digital businesses maximize the economic value of network connections. This forces a shift toward platforms and ecosystems that are collaborative by nature by applying business models with multiple actors playing multiple roles. The purpose of this study is to show how the main concepts emerging from research on digital platform ecosystems DPEs could be organized in a taxonomy-based framework with different levels or dimensions of analysis.

This study discusses some of the contingencies at these different levels and argues that future research needs to study DPEs across multiple levels of analysis. While this integrative framework allows the comparison, contrast and integration of various perspectives at different levels of analysis, further theorizing will be needed to advance the DPE research. The multidimensional framework proposed here involves the use of a multimethodological approach that incorporates a synergy of businesses, technological innovations and management methods to provide support for research in interrelationships across platform ecosystems PEs on a regular basis.

ecosystem for the Namibian context could improve healthcare services as a result of the (). Semantic service matchmaking for digital health ecosystems.

Abstract: This paper approaches a solution of Winograd Schemas with a marker passing algorithm which operates on an automatically generated semantic graph. The semantic graph contains common sense facts from data sources form the semantic web like domain ontologies e. Out of those facts, a semantic decomposition algorithm selects relevant facts for the concepts used in the Winograd Schema and adds them to the semantic graph. Markers are propagated through the graph and used to identify an answer to the Winograd Schema.

Depending on the encoded knowledge in the graph connectionist view of world knowledge and the information encoded on the marker for symbolic reasoning our approach selects the answers. Abstract: The development of self-adaptive systems can greatly benefit from reference frameworks to structure the development process. Current reference frameworks abstract from the adaptation decision — the selection of a specific adaptation based on the goals and options available.

This decision is usually based on the three adaptation policies: rule-based, goal-based or utility based. However, concepts from these policies often are combined with each other in different ways to achieve hybrid policies. To structure this combination this paper identifies four types of such combinations. We express these types as patterns within a model that captures the functions, models and relations participating in the adaptation decision.

A Human-Centered Semantic Service Platform for the Digital Ecosystems Environment

Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. DOI: However, because of the diversity and heterogeneity of the services in the DEST environment, existing commercial products or research outputs cannot be directly applied to this field so as to fulfill the requirements of SMEs. View on Springer. Save to Library.

Analysts predict that new Internet of Things (IoT) products and services privacy and security and semantic interoperability have to be tackled. The worlds. The overall scope is to create and foster ecosystems of platforms for climate, food, energy, mobility, digital society and health applications” [19], Self-matchmaking​.

Abstract The dramatic increase in the use of knowledge discovery applications requires end users to write complex database search requests to retrieve information. Such users are not only expected to grasp the structural complexity of complex databases but also the semantic relationships between data stored in databases. In order to overcome such difficulties, researchers have been focusing on knowledge representation and interactive query generation through ontologies, with particular emphasis on improving the interface between data and search requests in order to bring the result sets closer to users research requirements.

This paper discusses ontology-based information retrieval approaches and techniques by taking into consideration the aspects of ontology modelling, processing and the translation of ontological knowledge into database search requests. It also extensively compares the existing ontology-to-database transformation and mapping approaches in terms of loss of data and semantics, structural mapping and domain knowledge applicability.

The research outcomes, recommendations and future challenges presented in this paper can bridge the gap between ontology and relational models to generate precise search requests using ontologies. Moreover, the comparison presented between various ontology-based information retrieval, database-to-ontology transformations and ontology-to-database mappings approaches provides a reference for enhancing the searching capabilities of massively loaded information management systems.

Building Healthcare Ecosystems


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