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Towards Consistent Data Representation in the IoT Healthcare Landscape

Authors:

Filippo Piccinini,

Antonella CarbonaroAuthors Info & Claims

DH '18: Proceedings of the 2018 International Conference on Digital Health

Pages 5 - 10

https://doi.org/10.1145/3194658.3194668

Published: 23 April 2018 Publication History

Abstract

Nowadays, the enormous volume of health and fitness data gathered from IoT wearable devices offers favourable opportunities to the research community. For instance, it can be exploited using sophisticated data analysis techniques, such as automatic reasoning, to find patterns and, extract information and new knowledge in order to enhance decision-making and deliver better healthcare. However, due to the high heterogeneity of data representation formats, the IoT healthcare landscape is characterised by an ubiquitous presence of data silos which prevents users and clinicians from obtaining a consistent representation of the 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: (1) consistently represent health and fitness data from heterogeneous IoT sources; (2) integrate and exchange them; and (3) enable automatic reasoning by inference engines.

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Cited By

Pérez-Gaspar MGomez JBárcenas EGarcia F(2024)A fuzzy description logic based IoT framework: Formal verification and end user programmingPLOS ONE10.1371/journal.pone.029665519:3(e0296655)Online publication date: 22-Mar-2024
https://doi.org/10.1371/journal.pone.0296655
Lanotte FO’Brien MJayaraman A(2023)AI in Rehabilitation Medicine: Opportunities and ChallengesAnnals of Rehabilitation Medicine10.5535/arm.2313147:6(444-458)Online publication date: 31-Dec-2023
https://doi.org/10.5535/arm.23131
N. A(2023)Early prediction in AI-enabled IoT environmentAIoT and Big Data Analytics for Smart Healthcare Applications10.2174/9789815196054123050008(85-99)Online publication date: 26-Dec-2023
https://doi.org/10.2174/9789815196054123050008
Show More Cited By

Index Terms

Towards Consistent Data Representation in the IoT Healthcare Landscape
1. Applied computing
  1. Life and medical sciences
    1. Health informatics
2. Information systems
  1. World Wide Web
    1. Web data description languages
      1. Semantic web description languages
        Resource Description Framework (RDF)
        Web Ontology Language (OWL)

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Published In

cover image ACM Conferences

DH '18: Proceedings of the 2018 International Conference on Digital Health

April 2018

172 pages

ISBN:9781450364935

DOI:10.1145/3194658

General Chair:
Patty Kostkova
University College London, UK
,
Program Chairs:
Floriana Grasso
University of Liverpool, UK
,
Carlos Castillo
Eurecat, Spain
,
Yelena Mejova
QCRI, Qatar
,
Arnold Bosman
Transmissible, Netherlands
,
Michael Edelstein
Chatham House, UK

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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IW3C2: International World Wide Web Conference Committee
University College London: University College London

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SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 April 2018

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Antonella Carbonaro

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DH'18

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IW3C2
University College London

DH'18: International Digital Health Conference

April 23 - 26, 2018

Lyon, France

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Cited By

Pérez-Gaspar MGomez JBárcenas EGarcia F(2024)A fuzzy description logic based IoT framework: Formal verification and end user programmingPLOS ONE10.1371/journal.pone.029665519:3(e0296655)Online publication date: 22-Mar-2024
https://doi.org/10.1371/journal.pone.0296655
Lanotte FO’Brien MJayaraman A(2023)AI in Rehabilitation Medicine: Opportunities and ChallengesAnnals of Rehabilitation Medicine10.5535/arm.2313147:6(444-458)Online publication date: 31-Dec-2023
https://doi.org/10.5535/arm.23131
N. A(2023)Early prediction in AI-enabled IoT environmentAIoT and Big Data Analytics for Smart Healthcare Applications10.2174/9789815196054123050008(85-99)Online publication date: 26-Dec-2023
https://doi.org/10.2174/9789815196054123050008
Pfeiffer Salomão Dias LDamasceno Vianna HHeckler WLuis Victória Barbosa J(2023)Ontology-Based Reasoning to Classify Behaviors Associated with Chronic Disease Risk FactorsProceedings of the XIX Brazilian Symposium on Information Systems10.1145/3592813.3592917(292-299)Online publication date: 29-May-2023
https://dl.acm.org/doi/10.1145/3592813.3592917
Bitilis PZafeiropoulos NKoletis AKotis K(2023)Uncovering the Semantics of PD Patients' Movement Data Collected via off-the-shelf Wearables2023 14th International Conference on Information, Intelligence, Systems & Applications (IISA)10.1109/IISA59645.2023.10345958(1-8)Online publication date: 10-Jul-2023
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Steenwinckel BDe Brouwer MStojchevska MVan Der Donckt JNelis JRuyssinck Jvan der Herten JCasier KVan Ooteghem JCrombez PDe Turck FVan Hoecke SOngenae F(2023)Data Analytics for Health and Connected Care: Ontology, Knowledge Graph and ApplicationsPervasive Computing Technologies for Healthcare10.1007/978-3-031-34586-9_23(344-360)Online publication date: 11-Jun-2023
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Giallorenzo SMontesi FSafina LZingaro S(2022)Ephemeral data handling in microservices with TqueryPeerJ Computer Science10.7717/peerj-cs.10378(e1037)Online publication date: 22-Jul-2022
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Hlongwane SGrobbelaar S(2022)A Practical Framework for Value Creation in Health Information Systems From an Ecosystem Perspective: Evaluated in the South African ContextFrontiers in Psychology10.3389/fpsyg.2022.63788313Online publication date: 2-Jun-2022
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Alhajri MSalehi Shahraki ARudolph C(2022)Privacy of Fitness Applications and Consent Management in BlockchainProceedings of the 2022 Australasian Computer Science Week10.1145/3511616.3513100(65-73)Online publication date: 14-Feb-2022
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Kumar SJeong SAhn IJarwar M(2022)Things Data Interoperability Through Annotating oneM2M resources for NGSI-LD Entities2022 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics)10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics55523.2022.00056(119-124)Online publication date: Aug-2022
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