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Semantic Modelling of Smart Healthcare Data

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Intelligent Systems and Applications (IntelliSys 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 869))

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Abstract

Nowadays, healthcare is becoming increasingly connected and increasingly complex. These changes provide opportunities and challenges to the research community. For instance, the enormous volume of data gathered from IoT wearable fitness devices and wellness appliances, if effectively analysed and understood, can be exploited to improve people’s well-being and identify predictive markers of future diseases. However, due to the lack of devices interoperability and heterogeneity of data representation formats, the IoT healthcare landscape is characterised by a pervasive presence of “data silos" which prevents users and health practitioners from obtaining an overall view of whole knowledge. Semantic web technologies, such as ontologies and inference rules have been shown as a promising way for the integration and exploitation of data from heterogeneous sources. In this paper, we present a semantic data model useful to: (a) analyse information from unstructured data sources along with generic or domain specific datasets; (b) unify them in an interlinked data processing area. The proposed semantic eHealth system enables automatic inferences and logical reasoning, and can significantly facilitate reuse, exploitation and possible extension of IoT health data sources.

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Author information

Authors and Affiliations

  1. Master’s Degree in Computer Science and Engineering, University of Bologna, Bologna, Italy

    Roberto Reda

  2. Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) S.r.l. IRCCS, Oncology Research Hospital, Meldola (FC), Italy

    Filippo Piccinini

  3. Department of Computer Science and Engineering, University of Bologna, Bologna, Italy

    Antonella Carbonaro

Authors
  1. Roberto Reda
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  2. Filippo Piccinini
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  3. Antonella Carbonaro
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Corresponding author

Correspondence to Antonella Carbonaro .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, UK

    Rahul Bhatia

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Reda, R., Piccinini, F., Carbonaro, A. (2019). Semantic Modelling of Smart Healthcare Data. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems and Applications. IntelliSys 2018. Advances in Intelligent Systems and Computing, vol 869. Springer, Cham. https://doi.org/10.1007/978-3-030-01057-7_32

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