Bibliography of Materials Relevant to the Interaction of Competition Policy, Big Data and Personal Data

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.

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Big Data, Anonymisation and Governance to Personal Data Protection

The 21st Annual International Conference on Digital Government Research ◽

10.1145/3396956.3398253 ◽

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

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Solutions to Big Data Privacy and Security Challenges Associated With COVID-19 Surveillance Systems

Frontiers in Big Data ◽

10.3389/fdata.2021.645204 ◽

2021 ◽

Vol 4 ◽

Author(s):

Vibhushinie Bentotahewa ◽

Chaminda Hewage ◽

Jason Williams

Keyword(s):

Big Data ◽

Data Privacy ◽

Personal Data ◽

Surveillance Systems ◽

Privacy Rights ◽

Personal Privacy ◽

Privacy And Security ◽

Digital Surveillance ◽

Feasible Solutions ◽

The Impact

The growing dependency on digital technologies is becoming a way of life, and at the same time, the collection of data using them for surveillance operations has raised concerns. Notably, some countries use digital surveillance technologies for tracking and monitoring individuals and populations to prevent the transmission of the new coronavirus. The technology has the capacity to contribute towards tackling the pandemic effectively, but the success also comes at the expense of privacy rights. The crucial point to make is regardless of who uses and which mechanism, in one way another will infringe personal privacy. Therefore, when considering the use of technologies to combat the pandemic, the focus should also be on the impact of facial recognition cameras, police surveillance drones, and other digital surveillance devices on the privacy rights of those under surveillance. The GDPR was established to ensure that information could be shared without causing any infringement on personal data and businesses; therefore, in generating Big Data, it is important to ensure that the information is securely collected, processed, transmitted, stored, and accessed in accordance with established rules. This paper focuses on Big Data challenges associated with surveillance methods used within the COVID-19 parameters. The aim of this research is to propose practical solutions to Big Data challenges associated with COVID-19 pandemic surveillance approaches. To that end, the researcher will identify the surveillance measures being used by countries in different regions, the sensitivity of generated data, and the issues associated with the collection of large volumes of data and finally propose feasible solutions to protect the privacy rights of the people, during the post-COVID-19 era.

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Digital Economy, Big Data and Competition Law

Market and Competition Law Review ◽

10.7559/mclawreview.2019.315 ◽

2019 ◽

Vol 3 (1) ◽

pp. 53-89

Author(s):

Roberto Augusto Castellanos Pfeiffer

Keyword(s):

Big Data ◽

Data Protection ◽

Personal Data ◽

Competition Law ◽

Digital Economy ◽

Data Driven ◽

Dominant Position ◽

Privacy Concerns ◽

Sense Data ◽

Abuse Of Dominant Position

Big data has a very important role in the digital economy, because firms have accurate tools to collect, store, analyse, treat, monetise and disseminate voluminous amounts of data. Companies have been improving their revenues with information about the behaviour, preferences, needs, expectations, desires and evaluations of their consumers. In this sense, data could be considered as a productive input. The article focuses on the current discussion regarding the possible use of competition law and policy to address privacy concerns related to big data companies. The most traditional and powerful tool to deal with privacy concerns is personal data protection law. Notwithstanding, the article examines whether competition law should play an important role in data-driven markets where privacy is a key factor. The article suggests a new approach to the following antitrust concepts in cases related to big data platforms: assessment of market power, merger notification thresholds, measurement of merger effects on consumer privacy, and investigation of abuse of dominant position. In this context, the article analyses decisions of competition agencies which reviewed mergers in big data-driven markets, such as Google/DoubleClick, Facebook/ WhatsApp and Microsoft/LinkedIn. It also reviews investigations of alleged abuse of dominant position associated with big data, in particular the proceeding opened by the Bundeskartellamt against Facebook, in which the German antitrust authority prohibited the data processing policy imposed by Facebook on its users. The article concludes that it is important to harmonise the enforcement of competition, consumer and data protection polices in order to choose the proper way to protect the users of dominant platforms, maximising the benefits of the data-driven economy.

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Is Big Data Security Essential for Students to Understand?

HOLISTICA – Journal of Business and Public Administration ◽

10.2478/hjbpa-2020-0026 ◽

2020 ◽

Vol 11 (2) ◽

pp. 161-170

Author(s):

Rochman Hadi Mustofa

Keyword(s):

Big Data ◽

Undergraduate Students ◽

Data Security ◽

Personal Data ◽

Digital Data ◽

Security And Privacy ◽

Group Discussions ◽

Technology Applications ◽

Digital Payments ◽

Financial Technology

AbstractBig Data has become a significant concern of the world, along with the era of digital transformation. However, there are still many young people, especially in developing countries, who are not yet aware of the security of their big data, especially personal data. Misuse of information from big data often results in violations of privacy, security, and cybercrime. This study aims to determine how aware of the younger generation of security and privacy of their big data. Data were collected qualitatively by interviews and focus group discussions (FGD) from. Respondents were undergraduate students who used social media and financial technology applications such as online shopping, digital payments, digital wallet and hotel/transportation booking applications. The results showed that students were not aware enough and understood the security or privacy of their digital data, and some respondents even gave personal data to potentially scam sites. Most students are not careful in providing big data information because they are not aware of the risks behind it, socialization is needed in the future as a step to prevent potential data theft.

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DATA SOURCES FOR BUSINESS INTELLIGENCE

10.31219/osf.io/jrs54 ◽

2021 ◽

Author(s):

Naveen Kunnathuvalappil Hariharan

Keyword(s):

Big Data ◽

Business Intelligence ◽

Personal Data ◽

Data Sources ◽

Enterprise Information System ◽

Enterprise Information ◽

External Data ◽

Operational Systems ◽

Internal Sources ◽

Key Questions

As organizations' desire for data grows, so does their search for data sources that are both usable and reliable.Businesses can obtain and collect big data in a variety of locations, both inside and outside their own walls.This study aims to investigate the various data sources for business intelligence. For business intelligence,there are three types of data: internal data, external data, and personal data. Internal data is mostly kept indatabases, which serve as the backbone of an enterprise information system and are known as transactionalsystems or operational systems. This information, however, is not always sufficient. If the company wants toanswer market and industry questions or better understand future customers, the analytics team may need to look beyond the company's own data sources. Organizations must have access to a variety of data sources in order to answer the key questions that guide their initiatives. Internal sources, external public sources, andcollaboration with a big data expert could all be beneficial. Companies who are able to extract relevant datafrom their mountain of data acquire new perspectives on their business, allowing them to become morecompetitive

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Methods of big data definition: Russian and foreign experience

Юридические исследования ◽

10.25136/2409-7136.2021.9.36591 ◽

2021 ◽

pp. 143-157

Author(s):

Kseniia Antipova

Keyword(s):

Big Data ◽

Russian Federation ◽

Personal Data ◽

Legal Regulation ◽

The European Union ◽

Legal Doctrine ◽

Original Definition ◽

Data Definition ◽

The Russian Federation

This article explores the main approaches of Russian and foreign authors towards big data definition; reflects the classification of data, components of big data; and provides comparative characteristics to legal regulation of big data. The subject of this research is the legislation of the Russian Federation and legislation of the European Union that regulate the activity on collection, processing and use of big data, personal data and information; judicial and arbitration practice of the Russian Federation in the sphere of personal data; normative legal acts of the Russian Federation; governmental regulation of the Russian Federation and foreign countries in the area of processing, use and transmission of data; as well as legal doctrine in the field of research dedicated to the nature of big data. The relevance of this research is substantiated by the fact that there is yet no conceptual uniformity with regards to big data in the world; the essence and methods of regulating big data are not fully explored. The goal of this research is determine the legal qualification of the data that comprise big data. The task lies in giving definition to the term “big data”; demonstrate the approaches towards determination of legal nature of big data; conduct  classification of big data; outline the criteria for distinguishing data that comprise the concept of big data; formulate the model for optimal regulation of relations in the process of activity on collection, processing, and use of the data. The original definition of big data in the narrow and broad sense is provided. As a result, the author distinguishes the types of data, reflects the legal qualification of data depending on the category of data contained therein: industrial data, user data, and personal data. Attention is also turned to the contractual form of big data circulation.

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