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Authors: Juha Puustjärvi 1 and Leena Puustjärvi 2

Affiliations: 1 University of Helsinki, Finland ; 2 The Pharmacy of Kaivopuisto, Finland

Keyword(s): Personal Health Record, Personal Data, Data Integration, Smart Home, Semantic Web, RDF, SPARQL.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Cloud Computing ; Collaboration and e-Services ; Complex Systems Modeling and Simulation ; Data Engineering ; e-Business ; e-Health ; Electronic Health Records and Standards ; Enterprise Information Systems ; Health Information Systems ; Integration/Interoperability ; Interoperability ; Knowledge Management and Information Sharing ; Knowledge-Based Systems ; Ontologies and the Semantic Web ; Platforms and Applications ; Semantic Interoperability ; Sensor Networks ; Simulation and Modeling ; Software Agents and Internet Computing ; Software and Architectures ; Symbolic Systems

Abstract: A personal health record (PHR) is a record of a consumer that includes data gathered from different sources such as from health care providers, pharmacies, insures, the consumer, and third parties. Gathering data is technically complicated and error-prone due to the heterogeneities of the data sources. Further, due to failed or missed transmissions patients’ PHRs are often incomplete. However, a consumer should have easy access to their own health information as well as to any relevant information they need in order to make decisions about their own heath care. Nevertheless, no holistic approach for managing personal data beyond PHRs has been developed. Satisfying this challenge requires a means to capture and interconnect information from a variety of personal data sources and from public data sources. In order to achieve this goal, we have designed a Personal Record (PR). It is virtually a single record in the sense that it gives an illusion of a traditional standalone tool, suc h as a traditional PHR, although its content may locate in a variety of sources, e.g., in systems storing data of health, gyms, smart homes, or personal notes. By means of PR we can also achieve synergy, e.g., in using health data together with welfare and smart home data we can produce outcomes that could not be achieved by functioning independently with single data sources. Moreover, using personal data together with public data sources we can also achieve more informal outcomes. The only requirement is that the data sources are in RDF-format, i.e., in the form of subject–predicate–object expressions. Then the SPARQL processor has the ability to process the data as well as to find the connections between triples from separate sources. (More)

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Paper citation in several formats:
Puustjärvi, J. and Puustjärvi, L. (2016). Managing Fragmented Personal Data: Going beyond the Limits of Personal Health Records. In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - HEALTHINF, (BIOSTEC 2016) ISBN 978-989-758-170-0; ISSN 2184-4305, pages 145-150. DOI: 10.5220/0005626101450150

@conference{healthinf16,
author={Juha Puustjärvi. and Leena Puustjärvi.},
title={Managing Fragmented Personal Data: Going beyond the Limits of Personal Health Records},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - HEALTHINF, (BIOSTEC 2016)},
year={2016},
pages={145-150},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005626101450150},
isbn={978-989-758-170-0},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - HEALTHINF, (BIOSTEC 2016)
TI - Managing Fragmented Personal Data: Going beyond the Limits of Personal Health Records
SN - 978-989-758-170-0
IS - 2184-4305
AU - Puustjärvi, J.
AU - Puustjärvi, L.
PY - 2016
SP - 145
EP - 150
DO - 10.5220/0005626101450150

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