GDPR and the reuse of personal data in scientific research

Katulić, Tihomir; Katulić, Anita

doi:10.23919/mipro.2018.8400237

Cited by 3 publications

(1 citation statement)

References 1 publication

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“…Another interesting case is presented in [23], where the case of charity sectors is investigated. Indeed, the same problem is also touched in the context of using of personal data in scientific research (e.g., [26]). [29] proposes an interesting work that describes how to effectively model legal knowledge (e.g., knowledge produced and derived in the legal context) in order to make it ready for GDPR compliance checking.…”

Section: Related Workmentioning

confidence: 99%

An Innovative Online Process Mining Framework for Supporting Incremental GDPR Compliance of Business Processes

Zaman

Cuzzocrea

Hassani

2019

2019 IEEE International Conference on Big Data (Big Data)

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Section: Related Workmentioning

confidence: 99%

An Innovative Online Process Mining Framework for Supporting Incremental GDPR Compliance of Business Processes

Zaman

Cuzzocrea

Hassani

2019

2019 IEEE International Conference on Big Data (Big Data)

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New Era for Technology in Healthcare Powered by GDPR and Blockchain

Stan

Miclea

2019

6th International Conference on Advancements of Medicine and Health Care Through Technology; 17–20 October 2018, Cluj-Napoca, R

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A Privacy-Preserving and Standard-Based Architecture for Secondary Use of Clinical Data

2022

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The heterogeneity of the formats and standards of clinical data, which includes both structured, semi-structured, and unstructured data, in addition to the sensitive information contained in them, require the definition of specific approaches that are able to implement methodologies that can permit the extraction of valuable information buried under such data. Although many challenges and issues that have not been fully addressed still exist when this information must be processed and used for further purposes, the most recent techniques based on machine learning and big data analytics can support the information extraction process for the secondary use of clinical data. In particular, these techniques can facilitate the transformation of heterogeneous data into a common standard format. Moreover, they can also be exploited to define anonymization or pseudonymization approaches, respecting the privacy requirements stated in the General Data Protection Regulation, Health Insurance Portability and Accountability Act and other national and regional laws. In fact, compliance with these laws requires that only de-identified clinical and personal data can be processed for secondary analyses, in particular when data is shared or exchanged across different institutions. This work proposes a modular architecture capable of collecting clinical data from heterogeneous sources and transforming them into useful data for secondary uses, such as research, governance, and medical education purposes. The proposed architecture is able to exploit appropriate modules and algorithms, carry out transformations (pseudonymization and standardization) required to use data for the second purposes, as well as provide efficient tools to facilitate the retrieval and analysis processes. Preliminary experimental tests show good accuracy in terms of quantitative evaluations.

show abstract

GDPR and the reuse of personal data in scientific research

Cited by 3 publications

References 1 publication

An Innovative Online Process Mining Framework for Supporting Incremental GDPR Compliance of Business Processes

An Innovative Online Process Mining Framework for Supporting Incremental GDPR Compliance of Business Processes

New Era for Technology in Healthcare Powered by GDPR and Blockchain

A Privacy-Preserving and Standard-Based Architecture for Secondary Use of Clinical Data

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