The need for machine-processable agreements in health data management
The need for machine-processable agreements in health data management
Data processing agreements in health data management are laid out by organisations in monolithic “Terms and Conditions” documents written in natural legal language. These top-down policies usually protect the interest of the service providers, rather than the data owners. They are coarse-grained and do not allow for more than a few opt-in or opt-out options for individuals to express their consent on personal data processing, and these options often do not transfer to software as they were intended to. In this paper, we study the problem of health data sharing and we advocate the need for individuals to describe their personal contract of data usage in a formal, machine-processable language. We develop an application for sharing patient genomic information and test results, and use interactions with patients and clinicians in order to identify the particular peculiarities a privacy/policy/consent language should offer in this complicated domain. We present how Semantic Web technologies can have a central role in this approach by providing the formal tools and features required in such a language. We present our ongoing approach to construct an ontology-based framework and a policy language that allows patients and clinicians to express fine-grained consent, preferences or suggestions on sharing medical information. Our language offers unique features such as multi-party ownership of data or data sharing dependencies. We evaluate the landscape of policy languages from different areas, and show how they are lacking major requirements needed in health data management. In addition to enabling patients, our approach helps organisations increase technological capabilities, abide by legal requirements, and save resources.
Consent, Data sharing, Genomic data, Genomic medicine, Health data management, Privacy languages, Privacy policies
1-21
Konstantinidis, Georgios
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Chapman, Adriane
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Weal, Mark
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Alzubaidi, Ahmed
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Ballard, Lisa
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Lucassen, Anneke
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April 2020
Konstantinidis, Georgios
f174fb99-8434-4485-a7e4-bee0fef39b42
Chapman, Adriane
721b7321-8904-4be2-9b01-876c430743f1
Weal, Mark
e8fd30a6-c060-41c5-b388-ca52c81032a4
Alzubaidi, Ahmed
3958a76a-3aba-4408-b49a-87505a1859bf
Ballard, Lisa
48a7b1af-4d2b-4ec7-8927-84361a3c62a9
Lucassen, Anneke
2eb85efc-c6e8-4c3f-b963-0290f6c038a5
Konstantinidis, Georgios, Chapman, Adriane, Weal, Mark, Alzubaidi, Ahmed, Ballard, Lisa and Lucassen, Anneke
(2020)
The need for machine-processable agreements in health data management.
Algorithms, 13 (4), , [87].
(doi:10.3390/a13040087).
Abstract
Data processing agreements in health data management are laid out by organisations in monolithic “Terms and Conditions” documents written in natural legal language. These top-down policies usually protect the interest of the service providers, rather than the data owners. They are coarse-grained and do not allow for more than a few opt-in or opt-out options for individuals to express their consent on personal data processing, and these options often do not transfer to software as they were intended to. In this paper, we study the problem of health data sharing and we advocate the need for individuals to describe their personal contract of data usage in a formal, machine-processable language. We develop an application for sharing patient genomic information and test results, and use interactions with patients and clinicians in order to identify the particular peculiarities a privacy/policy/consent language should offer in this complicated domain. We present how Semantic Web technologies can have a central role in this approach by providing the formal tools and features required in such a language. We present our ongoing approach to construct an ontology-based framework and a policy language that allows patients and clinicians to express fine-grained consent, preferences or suggestions on sharing medical information. Our language offers unique features such as multi-party ownership of data or data sharing dependencies. We evaluate the landscape of policy languages from different areas, and show how they are lacking major requirements needed in health data management. In addition to enabling patients, our approach helps organisations increase technological capabilities, abide by legal requirements, and save resources.
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algorithms-13-00087-v2 (1)
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More information
Accepted/In Press date: 4 April 2020
e-pub ahead of print date: 7 April 2020
Published date: April 2020
Additional Information:
Special Issue: Selected papers from: Second International Workshop on Semantic Web Technologies for Health Data Management
Keywords:
Consent, Data sharing, Genomic data, Genomic medicine, Health data management, Privacy languages, Privacy policies
Identifiers
Local EPrints ID: 441061
URI: http://eprints.soton.ac.uk/id/eprint/441061
ISSN: 1999-4893
PURE UUID: 84153203-63ea-407d-be2a-d7e94d5decab
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Date deposited: 28 May 2020 16:58
Last modified: 17 Mar 2024 03:46
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Contributors
Author:
Georgios Konstantinidis
Author:
Mark Weal
Author:
Ahmed Alzubaidi
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