scholarly journals Fundamental privacy rights in a pandemic state

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252169
Author(s):  
Tânia Carvalho ◽  
Pedro Faria ◽  
Luís Antunes ◽  
Nuno Moniz
Keyword(s):  
Risk Analysis ◽  
Data Protection ◽  
State Of The Art ◽  
Health Data ◽  
Privacy Rights ◽  
Data Set ◽  
Health Authorities ◽  
Identity Disclosure ◽  
Decision Making Processes ◽  
Regional Health Authorities

Faced with the emergence of the Covid-19 pandemic, and to better understand and contain the disease’s spread, health organisations increased the collaboration with other organisations sharing health data with data scientists and researchers. Data analysis assists such organisations in providing information that could help in decision-making processes. For this purpose, both national and regional health authorities provided health data for further processing and analysis. Shared data must comply with existing data protection and privacy regulations. Therefore, a robust de-identification procedure must be used, and a re-identification risk analysis should also be performed. De-identified data embodies state-of-the-art approaches in Data Protection by Design and Default because it requires the protection of direct and indirect identifiers (not just direct). This article highlights the importance of assessing re-identification risk before data disclosure by analysing a data set of individuals infected by Covid-19 that was made available for research purposes. We stress that it is highly important to make this data available for research purposes and that this process should be based on the state of the art methods in Data Protection by Design and by Default. Our main goal is to consider different re-identification risk analysis scenarios since the information on the intruder side is unknown. Our conclusions show that there is a risk of identity disclosure for all of the studied scenarios. For one, in particular, we proceed to an example of a re-identification attack. The outcome of such an attack reveals that it is possible to identify individuals with no much effort.

scholarly journals The “A” of FAIR – As Open as Possible, as Closed as Necessary

2020 ◽  
Vol 2 (1-2) ◽  
pp. 47-55 ◽  
Author(s):  
Annalisa Landi ◽  
Mark Thompson ◽  
Viviana Giannuzzi ◽  
Fedele Bonifazi ◽  
Ignasi Labastida ◽  
...  
Keyword(s):  
Data Sharing ◽  
Data Protection ◽  
Personal Data ◽  
Health Data ◽  
Privacy Rights ◽  
Regulatory Requirements ◽  
Data Set ◽  
General Data Protection Regulation ◽  
Digital Era ◽  
General Data

In order to provide responsible access to health data by reconciling benefits of data sharing with privacy rights and ethical and regulatory requirements, Findable, Accessible, Interoperable and Reusable (FAIR) metadata should be developed. According to the H2020 Program Guidelines on FAIR Data, data should be “as open as possible and as closed as necessary”, “open” in order to foster the reusability and to accelerate research, but at the same time they should be “closed” to safeguard the privacy of the subjects. Additional provisions on the protection of natural persons with regard to the processing of personal data have been endorsed by the European General Data Protection Regulation (GDPR), Reg (EU) 2016/679, that came into force in May 2018. This work aims to solve accessibility problems related to the protection of personal data in the digital era and to achieve a responsible access to and responsible use of health data. We strongly suggest associating each data set with FAIR metadata describing both the type of data collected and the accessibility conditions by considering data protection obligations and ethical and regulatory requirements. Finally, an existing FAIR infrastructure component has been used as an example to explain how FAIR metadata could facilitate data sharing while ensuring protection of individuals.

scholarly journals Public administration’s challenges in order to guarantee the fundamental right of personal data protection in the post-COVID-19 era

2020 ◽  
Vol 7 (1) ◽  
pp. 167-192
Author(s):  
José Luis Dominguez Alvarez
Keyword(s):  
Data Protection ◽  
Personal Data ◽  
Health Data ◽  
Essential Elements ◽  
Economic Changes ◽  
Digital Rights ◽  
Personal Data Protection ◽  
Health Authorities ◽  
Technological Tools ◽  
Harmful Effects

The irruption of COVID-19 has led to a multitude of deep-seated transformations, which go beyond the purely sanitary sphere, leading to major socio-economic changes, among which the evolution of traditional forms of administrative intervention or the empowerment and/or acceleration of the advances derived from the digital (re)volution stand out for their extraordinary importance. Thereby, in recent months we have witnessed the implementation of numerous initiatives aimed to alleviate the harmful effects of the pandemic by developing technological tools based on processing categories of specially protected personal data, such as health data, which raises important questions from the perspective of privacy and digital rights. The aim of this study is to carry out a detailed analysis of some essential elements, necessary to achieve the difficult balance between the promotion of technological instruments that contribute to control the effects of COVID-19 increasing the resources available to health authorities, and safeguarding the fundamental right of personal data protection.

scholarly journals A Benchmark and Evaluation of Non-Rigid Structure from Motion

2020 ◽  
Author(s):  
Sebastian Hoppe Nesgaard Jensen ◽  
Mads Emil Brix Doest ◽  
Henrik Aanæs ◽  
Alessio Del Bue
Keyword(s):  
Computer Vision ◽  
Structure From Motion ◽  
State Of The Art ◽  
The State ◽  
Quality Data ◽  
Data Set ◽  
Rigid Structure ◽  
Public Data ◽  
3D Information ◽  
Further Development

AbstractNon-rigid structure from motion (nrsfm), is a long standing and central problem in computer vision and its solution is necessary for obtaining 3D information from multiple images when the scene is dynamic. A main issue regarding the further development of this important computer vision topic, is the lack of high quality data sets. We here address this issue by presenting a data set created for this purpose, which is made publicly available, and considerably larger than the previous state of the art. To validate the applicability of this data set, and provide an investigation into the state of the art of nrsfm, including potential directions forward, we here present a benchmark and a scrupulous evaluation using this data set. This benchmark evaluates 18 different methods with available code that reasonably spans the state of the art in sparse nrsfm. This new public data set and evaluation protocol will provide benchmark tools for further development in this challenging field.

scholarly journals Recruitment into psychiatry

1996 ◽  
Vol 20 (3) ◽  
pp. 177-177 ◽  
Author(s):  
David Storer
Keyword(s):  
Advisory Committee ◽  
Manpower Planning ◽  
Regional Health ◽  
Senior Registrar ◽  
Adequate Supply ◽  
Health Authorities ◽  
Joint Planning ◽  
Regional Health Authorities

The major problem of manpower planning in psychiatry has until fairly recently been one of securing enough posts in the training grades to place doctors wishing to train in psychiatry and to ensure an adequate supply of applicants for consultant posts. Numerous consultant vacancies and a ‘bottleneck’ between registrar and senior registrar grades was the frustrating combination largely consequent upon the failure of some regional health authorities to fund the posts which Joint Planning Advisory Committee (JPAC) had approved.

scholarly journals State-of-the-Art Prescriptive Criteria Weight Elicitation

2012 ◽  
Vol 2012 ◽  
pp. 1-24 ◽  
Author(s):  
Mona Riabacke ◽  
Mats Danielson ◽  
Love Ekenberg
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Theory ◽  
Decision Analysis ◽  
Analytical Methods ◽  
State Of The Art ◽  
Criteria Weights ◽  
Decision Making Processes ◽  
Method Of Assessment ◽  
Descriptive Theories

Comparatively few of the vast amounts of decision analytical methods suggested have been widely spread in actual practice. Some approaches have nevertheless been more successful in this respect than others. Quantitative decision making has moved from the study of decision theory founded on a single criterion towards decision support for more realistic decision-making situations with multiple, often conflicting, criteria. Furthermore, the identified gap between normative and descriptive theories seems to suggest a shift to more prescriptive approaches. However, when decision analysis applications are used to aid prescriptive decision-making processes, additional demands are put on these applications to adapt to the users and the context. In particular, the issue of weight elicitation is crucial. There are several techniques for deriving criteria weights from preference statements. This is a cognitively demanding task, subject to different biases, and the elicited values can be heavily dependent on the method of assessment. There have been a number of methods suggested for assessing criteria weights, but these methods have properties which impact their applicability in practice. This paper provides a survey of state-of-the-art weight elicitation methods in a prescriptive setting.

scholarly journals Public Interest, Health Research and Data Protection Law: Establishing a Legitimate Trade-Off between Individual Control and Research Access to Health Data

Laws ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 6 ◽  
Author(s):  
Mark J. Taylor ◽  
Tess Whitton
Keyword(s):  
Public Interest ◽  
Data Protection ◽  
Health Research ◽  
Health Data ◽  
Personal Health ◽  
Positive Contribution ◽  
Data Governance ◽  
The Public ◽  
Individual Control ◽  
Data Protection Law

The United Kingdom’s Data Protection Act 2018 introduces a new public interest test applicable to the research processing of personal health data. The need for interpretation and application of this new safeguard creates a further opportunity to craft a health data governance landscape deserving of public trust and confidence. At the minimum, to constitute a positive contribution, the new test must be capable of distinguishing between instances of health research that are in the public interest, from those that are not, in a meaningful, predictable and reproducible manner. In this article, we derive from the literature on theories of public interest a concept of public interest capable of supporting such a test. Its application can defend the position under data protection law that allows a legal route through to processing personal health data for research purposes that does not require individual consent. However, its adoption would also entail that the public interest test in the 2018 Act could only be met if all practicable steps are taken to maximise preservation of individual control over the use of personal health data for research purposes. This would require that consent is sought where practicable and objection respected in almost all circumstances. Importantly, we suggest that an advantage of relying upon this concept of the public interest, to ground the test introduced by the 2018 Act, is that it may work to promote the social legitimacy of data protection legislation and the research processing that it authorises without individual consent (and occasionally in the face of explicit objection).

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