scholarly journals Bigger is always not better, less is more, sometimes: the concept of data minimization in the context of Big Data

2021 ◽  
Author(s):  
Md. Abdul Malek
Keyword(s):  
Big Data ◽  
Personal Data ◽  
Digital Transformation ◽  
Location Tracking ◽  
Less Is More ◽  
Internet Users ◽  
Data Value ◽  
Data Explosion ◽  
The Universe ◽  
Minimization Approach

<p><i>Over 4.1 billion internet users of the universe generate about 2.5 quintillion bytes of data each day; and a digital universe of 44 zettabytes will hit 2021. As the data landscape expands every second every day, the data value also increases by leaps and bound. Personal data then get revitalized for the disruptive use of location tracking, predictive policing, fraud detection, healthcare, advertising media, and entertainment. Likewise, massive amassing of data also at the same pace gives rise to some new issues regarding the Big Data effects, including privacy invasion, data breaches, and cyber threats, etc. Taking efforts for mitigating the risks of data explosion thus becomes imperative for the society we live in. Accordingly, this paper attempts to focus on the ways how the data minimization approach mitigates such risks, and how this approach as a concept is being incorporated in the legal instruments. After suggesting practical methods on how to reap benefits from the principle, the paper concludes by exploring the way out of the existing dilemmas so created in the digital transformation. </i></p>

scholarly journals Bigger is always not better, less is more, sometimes: the concept of data minimization in the context of Big Data

2021 ◽  
Author(s):  
Md. Abdul Malek
Keyword(s):  
Big Data ◽  
Personal Data ◽  
Digital Transformation ◽  
Location Tracking ◽  
Less Is More ◽  
Internet Users ◽  
Data Value ◽  
Data Explosion ◽  
The Universe ◽  
Minimization Approach

<p><i>Over 4.1 billion internet users of the universe generate about 2.5 quintillion bytes of data each day; and a digital universe of 44 zettabytes will hit 2021. As the data landscape expands every second every day, the data value also increases by leaps and bound. Personal data then get revitalized for the disruptive use of location tracking, predictive policing, fraud detection, healthcare, advertising media, and entertainment. Likewise, massive amassing of data also at the same pace gives rise to some new issues regarding the Big Data effects, including privacy invasion, data breaches, and cyber threats, etc. Taking efforts for mitigating the risks of data explosion thus becomes imperative for the society we live in. Accordingly, this paper attempts to focus on the ways how the data minimization approach mitigates such risks, and how this approach as a concept is being incorporated in the legal instruments. After suggesting practical methods on how to reap benefits from the principle, the paper concludes by exploring the way out of the existing dilemmas so created in the digital transformation. </i></p>

scholarly journals Bigger is always not better, less is more, sometimes: the concept of data minimization in the context of Big Data

2021 ◽  
Author(s):  
Md. Abdul Malek
Keyword(s):  
Big Data ◽  
Personal Data ◽  
Location Tracking ◽  
Less Is More ◽  
Use Of Data ◽  
Data Value ◽  
The Face ◽  
Data Explosion ◽  
The Universe ◽  
Minimization Approach

<p></p><p><i>With the data landscape of the universe expands every second every day by leaps and bound, the data value also increases unprecedentedly. Particularly, the disruptive use of data in location tracking, predictive policing, fraud detection, healthcare, advertising media, and entertainment has already revitalized personal data in many ways. But massive amassing of data also gives rise to new issues regarding the Big Data effects, including privacy invasion, data breaches, and cyber threats, etc. Taking effective efforts for mitigating the risks of data explosion thus becomes indispensable for companies, organizations, and societies alike. In such background, this paper attempts to focus on the ways how the data minimization approach mitigates such risks, and how this approach as a concept is being incorporated in legal instruments globally. After exploring practical methods of applying data minimization, the paper concludes by delineating the way out of the existing dilemmas so created in the face of Big Data. </i></p><br><p></p>

The Privacy Paradox in the Big Data Era? No Thanks, We Are the E-People

2019 ◽  
Vol 9 (3) ◽  
pp. 32-47 ◽  
Author(s):  
Marco Vassallo
Keyword(s):  
Big Data ◽  
Personal Data ◽  
Factor Analyses ◽  
Convenience Sample ◽  
Confirmatory Factor Analyses ◽  
Internet Users ◽  
Confirmatory Factor ◽  
Privacy Paradox ◽  
New Perspective ◽  
Definition Of

The objective of this work is to propose a new perspective in understanding the phenomenon of online behaviors, termed the privacy paradox, i.e., worry on preserving personal data and contents, but a little attention to disclose them, and thus introducing the new definition of e-people. The provocative hypothesis of this study regards the internet users who, in the Big Data era, are affected by a common covariation of being e-popular/e-visible, e-narcissist, e-(socially)-accepted, e-remembered. These e-behaviors will be conceptually gathered under the term of Achilles' paradigm. A structured web-questionnaire was submitted to a convenience sample of 198 internet users. First and second-order confirmatory factor analyses together with latent means models concretely supported the existence of the Achilles' paradigm and its impact on the privacy paradox concerns. As a result, the privacy paradox is not an effective paradox anymore: self-disclosing privacy online seems to be a well-accepted behavior.

scholarly journals Critical big data literacy tools—Engaging citizens and promoting empowered internet usage

Data & Policy ◽  
2020 ◽  
Vol 2 ◽  
Author(s):  
Ina Sander
Keyword(s):  
Big Data ◽  
Data Science ◽  
Personal Data ◽  
Internet Usage ◽  
Data Systems ◽  
Data Literacy ◽  
Internet Users ◽  
New Findings ◽  
And Behavior ◽  
Attitudes And Behavior

Abstract Datafied societies need informed public debate about the implications of data science technologies. At present, internet users are often unaware of the potential consequences of disclosing personal data online and few citizens have the knowledge to participate in such debates. This paper argues that critical big data literacy efforts are one way to address this lack of knowledge. It draws on findings from a small qualitative investigation and discusses the effectiveness of online critical big data literacy tools. Through pre and post use testing, the short- and longer-term influence of these tools on people’s privacy attitudes and behavior was investigated. The study’s findings suggested that the tools tested had a predominantly positive initial effect, leading to improved critical big data literacy among most participants, which resulted in more privacy-sensitive attitudes and internet usage. When analyzing the tools’ longer-term influence, results were more mixed, with evidence suggesting for some that literacy effects of the tools were short-lived, while for others they led to more persistent and growing literacy. The findings confirm previous research noting the complexity of privacy attitudes and also find that resignation toward privacy is multi-faceted. Overall, this study reaffirms the importance of critical big data literacy and produces new findings about the value of interactive data literacy tools. These tools have been under-researched to date. This research shows that these tools could provide a relevant means to work toward empowering internet users, promoting a critical internet usage and, ideally, enabling more citizens to engage in public debates about changing data systems.

HIMSS Impact18: Leading Digital Transformation und Big Data in Medicine

2018 ◽  
Vol 23 (09) ◽  
pp. 25-25
Author(s):  
Sabine Schützmann
Keyword(s):  
Big Data ◽  
Digital Transformation

Am 17. und 18. Oktober findet im Hasso-Plattner-Institut (HPI) in Potsdam zum zweiten Mal die HIMSS Impact statt: Ein englischsprachiges Symposium, welches aktuelle Trends im Gesundheitswesen, digitale Strategien und jüngste Forschungserkenntnisse beleuchtet.

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

Payment Instruments, Financial Privacy and Online Purchases

2016 ◽  
Vol 15 (3) ◽  
Author(s):  
Yann Balgobin ◽  
David Bounie ◽  
Martin Quinn ◽  
Patrick Waelbroeck
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Monte Carlo Model ◽  
Personal Data ◽  
Purchasing Decisions ◽  
Online Purchases ◽  
Econometric Methods ◽  
Internet Users ◽  
Payment Instruments ◽  
Financial Privacy

AbstractThe protection of financial personal data has become a major concern for Internet users in the digital economy. This paper investigates whether the consumers’ use of non-bank payment instruments that preserve financial privacy from banks and relatives may increase their online purchases. We analyze the purchasing decisions and the use of bank and non-bank payment instruments of a representative sample of French Internet consumers in 2015. Using two econometric methods, namely a two-step regression and a Bayesian Markov Chain Monte Carlo model to account for a potential endogeneity problem, we find evidence that the use of a non-bank payment instrument positively influences consumers’ online purchases.

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