scholarly journals Medical research, Big Data and the need for privacy by design

2019 ◽  
Vol 6 (1) ◽  
pp. 205395171882435 ◽  
Author(s):  
Bart Jacobs ◽  
Jean Popma
Keyword(s):  
Big Data ◽  
Medical Research ◽  
Scientific Community ◽  
Medical Center ◽  
Life Sciences ◽  
Personal Data ◽  
Research Data ◽  
Privacy By Design ◽  
Research Setting ◽  
Large Cohort Study

Medical research data is sensitive personal data that needs to be protected from unauthorized access and unintentional disclosure. In a research setting, sharing of (big) data within the scientific community is necessary in order to make progress and maximize scientific benefits derived from valuable and costly data. At the same time, convincingly protecting the privacy of people (patients) participating in medical research is a prerequisite for maintaining trust and willingness to share. In this commentary, we will address this issue and the pitfalls involved in the context of the PEP project 1 that provides the infrastructure for the Personalized Parkinson’s Project, 2 a large cohort study on Parkinson’s disease from Radboud University Medical Center (Radboudumc), in cooperation with Verily life Sciences, an Alphabet subsidiary.

SMART CITY: OPPORTUNITIES AND CHALLENGES IN PUBLIC SERVICES AND ITS RELATION TO THE PROTECTION OF RIGHTS AND PRIVACY IN BIG-DATA ERA

2018 ◽  
Vol 2 (2) ◽  
pp. 116
Author(s):  
Kukuh Tejomurti ◽  
Padma Widyantari
Keyword(s):  
Big Data ◽  
Public Service ◽  
Smart City ◽  
National Level ◽  
Personal Data ◽  
Internet Technology ◽  
Public Security ◽  
Privacy By Design ◽  
Traffic Jam ◽  
The Government

<p>This article investigates <em>Smart City</em> program with the utilization of internet technology that government assumes as means to solve problems every city encounters, such as traffic jam, retribution, public security, and trash dumping. To provide public service, <em>Smart City</em> collects and manages personal data information of citizens from the intended city and puts it into a Big Data base. This program with <em>Big Data</em> technology has been successful addressing problems in cities. On the other hand, a consequence on how to protect public’s electronic-based personal data should be taken into account as well. Collecting, Processing, and Saving Information of public personal data may carry on particular risk, including violation on individual’s rights and privacy, when it is not well managed and set under a very clear policy, especially when its <em>big data </em>server is outside the territory of Indonesia. In general conclusion, the government needs to enact a regulation in constitutional and national level and/or regional regulation which specifically sets on how to prevent the misuse of electronic-based personal data and what law that regulates any violation against individual rights and privacy, as well as a regulation called <em>privacy by design</em>.</p>

scholarly journals Anticipatory Governance in Biobanking: Security and Risk Management in Digital Health

2021 ◽  
Vol 27 (3) ◽  
Author(s):  
Dagmar Rychnovská
Keyword(s):  
Big Data ◽  
Data Security ◽  
Digital Health ◽  
Life Sciences ◽  
Personal Data ◽  
Field Research ◽  
Societal Implications ◽  
Biomedical Data ◽  
Anticipatory Governance ◽  
Future Challenges

AbstractAlthough big-data research has met with multiple controversies in diverse fields, political and security implications of big data in life sciences have received less attention. This paper explores how threats and risks are anticipated and acted on in biobanking, which builds research repositories for biomedical samples and data. Focusing on the biggest harmonisation cluster of biomedical research in Europe, BBMRI-ERIC, the paper analyses different logics of risk in the anticipatory discourse on biobanking. Based on document analysis, interviews with ELSI experts, and field research, three types of framing of risk are reconstructed: data security, privacy, and data misuse. The paper finds that these logics downplay the broader social and political context and reflects on the limits of the practices of anticipatory governance in biobanking. It argues that this regime of governance can make it difficult for biobanks to address possible future challenges, such as access to biomedical data by authorities, pressures for integrating biobank data with other type of personal data, or their use for profiling beyond medical purposes. To address potential controversies and societal implications related to the use of big data in health research and medicine, the paper suggests to expand the vocabulary and practices of anticipatory governance, in the biobanking community and beyond.

scholarly journals Key Points for an Ethical Evaluation of Healthcare Big Data

Processes ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 493 ◽  
Author(s):  
Pilar Leon-Sanz
Keyword(s):  
Big Data ◽  
Ethical Issues ◽  
Group Identification ◽  
Life Sciences ◽  
Personal Data ◽  
Use Of Data ◽  
New Concepts ◽  
Key Points ◽  
Bioethical Debate ◽  
The Relationship

Background: The article studies specific ethical issues arising from the use of big data in Life Sciences and Healthcare. Methods: Main consensus documents, other studies, and particular cases are analyzed. Results: New concepts that emerged in five key areas for the bioethical debate on big data and health are identified—the accuracy and validity of data and algorithms, questions related to transparency and confidentiality in the use of data; aspects that raise the coding or pseudonymization and the anonymization of data, and also problems derived from the possible individual or group identification; the new ways of obtaining consent for the transfer of personal data; the relationship between big data and the responsibility of professional decision; and the commitment of the Institutions and Public Administrations. Conclusions: Good practices in the management of big data related to Life Sciences and Healthcare depend on respect for the rights of individuals, the improvement that these practices can introduce in assistance to individual patients, the promotion of society’s health in general and the advancement of scientific knowledge.

scholarly journals Record linkage of routine data with cohorts’ data of infants under European and Portuguese law

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
J Doetsch ◽  
I Lopes ◽  
R Redinha ◽  
H Barros
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Data Protection ◽  
Record Linkage ◽  
Data Science ◽  
Personal Data ◽  
Routine Data ◽  
Cohort Data ◽  
Education Data ◽  
Explicit Consent

Abstract The usage and exchange of “big data” is at the forefront of the data science agenda where Record Linkage plays a prominent role in biomedical research. In an era of ubiquitous data exchange and big data, Record Linkage is almost inevitable, but raises ethical and legal problems, namely personal data and privacy protection. Record Linkage refers to the general merging of data information to consolidate facts about an individual or an event that are not available in a separate record. This article provides an overview of ethical challenges and research opportunities in linking routine data on health and education with cohort data from very preterm (VPT) infants in Portugal. Portuguese, European and International law has been reviewed on data processing, protection and privacy. A three-stage analysis was carried out: i) interplay of threefold law-levelling for Record Linkage at different levels; ii) impact of data protection and privacy rights for data processing, iii) data linkage process' challenges and opportunities for research. A framework to discuss the process and its implications for data protection and privacy was created. The GDPR functions as utmost substantial legal basis for the protection of personal data in Record Linkage, and explicit written consent is considered the appropriate basis for the processing sensitive data. In Portugal, retrospective access to routine data is permitted if anonymised; for health data if it meets data processing requirements declared with an explicit consent; for education data if the data processing rules are complied. Routine health and education data can be linked to cohort data if rights of the data subject and requirements and duties of processors and controllers are respected. A strong ethical context through the application of the GDPR in all phases of research need to be established to achieve Record Linkage between cohort and routine collected records for health and education data of VPT infants in Portugal. Key messages GDPR is the most important legal framework for the protection of personal data, however, its uniform approach granting freedom to its Member states hampers Record Linkage processes among EU countries. The question remains whether the gap between data protection and privacy is adequately balanced at three legal levels to guarantee freedom for research and the improvement of health of data subjects.

Big Data, Anonymisation and Governance to Personal Data Protection

2020 ◽  
Author(s):  
Artur Potiguara Carvalho ◽  
Fernanda Potiguara Carvalho ◽  
Edna Dias Canedo ◽  
Pedro Henrique Potiguara Carvalho
Keyword(s):  
Big Data ◽  
Data Protection ◽  
Personal Data ◽  
Personal Data Protection

German labour market data – Data provision and access for the international scientific community

2020 ◽  
Vol 21 (3) ◽  
pp. 313-333
Author(s):  
Dana Müller ◽  
Stefanie Wolter
Keyword(s):  
Labour Market ◽  
Survey Data ◽  
Scientific Community ◽  
Market Research ◽  
Research Data ◽  
International Scientific Community ◽  
High Quality ◽  
Data Centre ◽  
Integrated Employment ◽  
Data Provision

AbstractThe Research Data Centre at the Institute for Employment Research (RDC-IAB) has been offering high-quality administrative and survey data on the German labour market for 15 years and has become one of the most important locations worldwide for researchers interested in data for labour market research. This article provides an overview of the RDC-IAB, including its data and access modes. The article presents two datasets in more detail: the Sample of Integrated Employment Biographies, a classic dataset, and the Linked Personnel Panel, a new dataset. Finally, this article provides insights into future infrastructure and data developments.

scholarly journals The academic viewpoint on Big data and patient data ownership (as seen in the scientific literature)

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
I Mircheva ◽  
M Mirchev
Keyword(s):  
Public Health ◽  
Big Data ◽  
Medical Research ◽  
Information And Communication Technologies ◽  
Patient Information ◽  
Scientific Literature ◽  
Medical Data ◽  
Patient Data ◽  
Academic Community ◽  
Ethical Challenges

Abstract Background Ownership of patient information in the context of Big Data is a relatively new problem, apparently not yet fully understood. There are not enough publications on the subject. Since the topic is interdisciplinary, incorporating legal, ethical, medical and aspects of information and communication technologies, a slightly more sophisticated analysis of the issue is needed. Aim To determine how the medical academic community perceives the issue of ownership of patient information in the context of Big Data. Methods Literature search for full text publications, indexed in PubMed, Springer, ScienceDirect and Scopus identified only 27 appropriate articles authored by academicians and corresponding to three focus areas: problem (ownership); area (healthcare); context (Big Data). Three major aspects were studied: scientific area of publications, aspects and academicians' perception of ownership in the context of Big Data. Results Publications are in the period 2014 - 2019, 37% published in health and medical informatics journals, 30% in medicine and public health, 19% in law and ethics; 78% authored by American and British academicians, highly cited. The majority (63%) are in the area of scientific research - clinical studies, access and use of patient data for medical research, secondary use of medical data, ethical challenges to Big data in healthcare. The majority (70%) of the publications discuss ownership in ethical and legal aspects and 67% see ownership as a challenge mostly to medical research, access control, ethics, politics and business. Conclusions Ownership of medical data is seen first and foremost as a challenge. Addressing this challenge requires the combined efforts of politicians, lawyers, ethicists, computer and medical professionals, as well as academicians, sharing these efforts, experiences and suggestions. However, this issue is neglected in the scientific literature. Publishing may help in open debates and adequate policy solutions. Key messages Ownership of patient information in the context of Big Data is a problem that should not be marginalized but needs a comprehensive attitude, consideration and combined efforts from all stakeholders. Overcoming the challenge of ownership may help in improving healthcare services, medical and public health research and the health of the population as a whole.

scholarly journals Introduction to the Special Issue on New Longitudinal Data for Retirement Analysis and Policy

2021 ◽  
pp. 1-5
Author(s):  
Marco Angrisani ◽  
Anya Samek ◽  
Arie Kapteyn
Keyword(s):  
Big Data ◽  
Academic Research ◽  
Cost Effective ◽  
Research Data ◽  
Data Sources ◽  
Special Issue ◽  
Administrative Records ◽  
The Past ◽  
Survey Questionnaires ◽  
Internet Panels

The number of data sources available for academic research on retirement economics and policy has increased rapidly in the past two decades. Data quality and comparability across studies have also improved considerably, with survey questionnaires progressively converging towards common ways of eliciting the same measurable concepts. Probability-based Internet panels have become a more accepted and recognized tool to obtain research data, allowing for fast, flexible, and cost-effective data collection compared to more traditional modes such as in-person and phone interviews. In an era of big data, academic research has also increasingly been able to access administrative records (e.g., Kostøl and Mogstad, 2014; Cesarini et al., 2016), private-sector financial records (e.g., Gelman et al., 2014), and administrative data married with surveys (Ameriks et al., 2020), to answer questions that could not be successfully tackled otherwise.

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