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Data Provenance in Healthcare: Approaches, Challenges, and Future Directions
Data provenance means recording data origins and the history of data generation and processing. In healthcare, data provenance is one of the essential processes that make it possible to track the sources and reasons behind any problem with a user’s data. With the emergence of the General Data Protec...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10384601/ https://www.ncbi.nlm.nih.gov/pubmed/37514788 http://dx.doi.org/10.3390/s23146495 |
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author | Ahmed, Mansoor Dar, Amil Rohani Helfert, Markus Khan, Abid Kim, Jungsuk |
author_facet | Ahmed, Mansoor Dar, Amil Rohani Helfert, Markus Khan, Abid Kim, Jungsuk |
author_sort | Ahmed, Mansoor |
collection | PubMed |
description | Data provenance means recording data origins and the history of data generation and processing. In healthcare, data provenance is one of the essential processes that make it possible to track the sources and reasons behind any problem with a user’s data. With the emergence of the General Data Protection Regulation (GDPR), data provenance in healthcare systems should be implemented to give users more control over data. This SLR studies the impacts of data provenance in healthcare and GDPR-compliance-based data provenance through a systematic review of peer-reviewed articles. The SLR discusses the technologies used to achieve data provenance and various methodologies to achieve data provenance. We then explore different technologies that are applied in the healthcare domain and how they achieve data provenance. In the end, we have identified key research gaps followed by future research directions. |
format | Online Article Text |
id | pubmed-10384601 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-103846012023-07-30 Data Provenance in Healthcare: Approaches, Challenges, and Future Directions Ahmed, Mansoor Dar, Amil Rohani Helfert, Markus Khan, Abid Kim, Jungsuk Sensors (Basel) Systematic Review Data provenance means recording data origins and the history of data generation and processing. In healthcare, data provenance is one of the essential processes that make it possible to track the sources and reasons behind any problem with a user’s data. With the emergence of the General Data Protection Regulation (GDPR), data provenance in healthcare systems should be implemented to give users more control over data. This SLR studies the impacts of data provenance in healthcare and GDPR-compliance-based data provenance through a systematic review of peer-reviewed articles. The SLR discusses the technologies used to achieve data provenance and various methodologies to achieve data provenance. We then explore different technologies that are applied in the healthcare domain and how they achieve data provenance. In the end, we have identified key research gaps followed by future research directions. MDPI 2023-07-18 /pmc/articles/PMC10384601/ /pubmed/37514788 http://dx.doi.org/10.3390/s23146495 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Systematic Review Ahmed, Mansoor Dar, Amil Rohani Helfert, Markus Khan, Abid Kim, Jungsuk Data Provenance in Healthcare: Approaches, Challenges, and Future Directions |
title | Data Provenance in Healthcare: Approaches, Challenges, and Future Directions |
title_full | Data Provenance in Healthcare: Approaches, Challenges, and Future Directions |
title_fullStr | Data Provenance in Healthcare: Approaches, Challenges, and Future Directions |
title_full_unstemmed | Data Provenance in Healthcare: Approaches, Challenges, and Future Directions |
title_short | Data Provenance in Healthcare: Approaches, Challenges, and Future Directions |
title_sort | data provenance in healthcare: approaches, challenges, and future directions |
topic | Systematic Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10384601/ https://www.ncbi.nlm.nih.gov/pubmed/37514788 http://dx.doi.org/10.3390/s23146495 |
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