scholarly journals Data Protection and Data Privacy Act for BIG DATA Governance

2021 ◽  
pp. 189-211
Author(s):  
Kesava Pillai Rajadorai ◽  
Vazeerudeen Abdul Hameed ◽  
Selvakumar Samuel
Keyword(s):  
Big Data ◽  
Data Protection ◽  
Data Privacy ◽  
Data Governance ◽  
Privacy Act

Big Data Governance in Agile and Data-Driven Software Development

2019 ◽  
pp. 179-199
Author(s):  
Lili Aunimo ◽  
Ari V. Alamäki ◽  
Harri Ketamo
Keyword(s):  
Big Data ◽  
Software Development ◽  
Predictive Models ◽  
Data Privacy ◽  
Business Case ◽  
Business Environment ◽  
Data Driven ◽  
Data Governance ◽  
Governance Framework ◽  
A Company

Constructing a big data governance framework is important when a company performs data-driven software development. The most important aspects of big data governance are data privacy, security, availability, usability, and integrity. In this chapter, the authors present a business case where a framework for big data governance has been built. The business case is about the development and continuous improvement of a new mobile application that is targeted for consumers. In this context, big data is used in product development, in building predictive modes related to the users and for personalization of the product. The main finding of the study is a novel big data governance framework and that a proper framework for big data governance is useful when building and maintaining trustworthy and value adding big data-driven predictive models in an authentic business environment.

Big Data Governance in Agile and Data-Driven Software Development

2021 ◽  
pp. 344-364
Author(s):  
Lili Aunimo ◽  
Ari V. Alamäki ◽  
Harri Ketamo
Keyword(s):  
Big Data ◽  
Software Development ◽  
Predictive Models ◽  
Data Privacy ◽  
Business Case ◽  
Business Environment ◽  
Data Driven ◽  
Data Governance ◽  
Governance Framework ◽  
A Company

Constructing a big data governance framework is important when a company performs data-driven software development. The most important aspects of big data governance are data privacy, security, availability, usability, and integrity. In this chapter, the authors present a business case where a framework for big data governance has been built. The business case is about the development and continuous improvement of a new mobile application that is targeted for consumers. In this context, big data is used in product development, in building predictive modes related to the users and for personalization of the product. The main finding of the study is a novel big data governance framework and that a proper framework for big data governance is useful when building and maintaining trustworthy and value adding big data-driven predictive models in an authentic business environment.

Data Protection and BI

2014 ◽  
pp. 389-413
Author(s):  
Daragh O Brien
Keyword(s):  
Big Data ◽  
Data Protection ◽  
Information Quality ◽  
Quality Characteristics ◽  
Data Governance ◽  
Information Governance ◽  
Security Control ◽  
Important Quality ◽  
The Right ◽  
The Relationship

Data Protection (DP) and Privacy are increasingly important quality characteristics of Information, particularly in the context of Business Intelligence and Big Data. This relationship between Data Protection and Information Quality (IQ) is often poorly understood, and DP itself is often misunderstood as being an issue of security control rather than information governance. This chapter examines the relationship between DP, IQ, and Data Governance (DG). It provides an overview of how techniques and practices from IQ and DG can ensure that BI projects are grounded on appropriate privacy controls that ensure that the right information is being used in the right way by the right people to answer the right questions.

scholarly journals Big Tech platforms in health research: Re-purposing big data governance in light of the General Data Protection Regulation’s research exemption

2021 ◽  
Vol 8 (1) ◽  
pp. 205395172110187
Author(s):  
Luca Marelli ◽  
Giuseppe Testa ◽  
Ine van Hoyweghen
Keyword(s):  
Big Data ◽  
Data Protection ◽  
Health Research ◽  
Digital Health ◽  
Scientific Research ◽  
Current Data ◽  
Data Governance ◽  
General Data Protection Regulation ◽  
Research Activities ◽  
General Data

The emergence of a global industry of digital health platforms operated by Big Tech corporations, and its growing entanglements with academic and pharmaceutical research networks, raise pressing questions on the capacity of current data governance models, regulatory and legal frameworks to safeguard the sustainability of the health research ecosystem. In this article, we direct our attention toward the challenges faced by the European General Data Protection Regulation in regulating the potentially disruptive engagement of Big Tech platforms in health research. The General Data Protection Regulation upholds a rather flexible regime for scientific research through a number of derogations to otherwise stricter data protection requirements, while providing a very broad interpretation of the notion of “scientific research”. Precisely the breadth of these exemptions combined with the ample scope of this notion could provide unintended leeway to the health data processing activities of Big Tech platforms, which have not been immune from carrying out privacy-infringing and socially disruptive practices in the health domain. We thus discuss further finer-grained demarcations to be traced within the broadly construed notion of scientific research, geared to implementing use-based data governance frameworks that distinguish health research activities that should benefit from a facilitated data protection regime from those that should not. We conclude that a “re-purposing” of big data governance approaches in health research is needed if European nations are to promote research activities within a framework of high safeguards for both individual citizens and society.

scholarly journals Negotiating the reuse of health-data: Research, Big Data, and the European General Data Protection Regulation

2019 ◽  
Vol 6 (2) ◽  
pp. 205395171986259 ◽  
Author(s):  
Johannes Starkbaum ◽  
Ulrike Felt
Keyword(s):  
Big Data ◽  
Data Protection ◽  
Data Science ◽  
Data Reuse ◽  
Data Governance ◽  
General Data Protection Regulation ◽  
Related Data ◽  
Sustainable Implementation ◽  
Health Related ◽  
General Data

Before the EU General Data Protection Regulation entered into force in May 2018, we witnessed an intense struggle of actors associated with data-dependent fields of science, in particular health-related academia and biobanks striving for legal derogations for data reuse in research. These actors engaged in a similar line of argument and formed issue alliances to pool their collective power. Using descriptive coding followed by an interpretive analysis, this article investigates the argumentative repertoire of these actors and embeds the analysis in ethical debates on data sharing and biobank-related data governance. We observe efforts to perform a paradigmatic shift of the discourse around the General Data Protection Regulation-implementation away from ‘protecting data’ as key concern to ‘protecting health’ of individuals and societies at large. Instead of data protection, the key risks stressed by health researchers became potential obstacles to research. In line, exchange of information with data subjects is not a key concern in the arguments of biobank-related actors and it is assumed that patients want ‘their’ data to be used. We interpret these narratives as a ‘reaction’ to potential restrictions for data reuse and in line with a broader trend towards Big Data science, as the very idea of biobanking is conceptualized around long-term use of readily prepared data. We conclude that a sustainable implementation of biobanks needs not only to comply with the General Data Protection Regulation, but must proactively re-imagine its relation to citizens and data subjects in order to account for the various ways that science gets entangled with society.

scholarly journals UIDAI Aadhar Enrollment with P2P Blockchain Technologies

2019 ◽  
Vol 9 (2S) ◽  
pp. 720-723
Keyword(s):  
Big Data ◽  
Data Protection ◽  
Personal Information ◽  
Personal Data ◽  
Sensitive Data ◽  
Encrypted Data ◽  
The Right To Privacy ◽  
Privacy Act ◽  
Distributed Ledger ◽  
The Right

Blockchain technologies are becoming more popular in securing the sensitive data such as government holding citizens’ s wealth, health and personal information. A blockchain is a shared encrypted data of records, consisting of a ledger of transactions. As the data stored in blockchain is tamper proof, it is proposed to implement new Aadhar enrolments with P2P Blockchains and migrate the existing centralized Aadhar personnel’s personal data from the conventional RDBMS / Big data system repositories to distributed ledger technologies by creating private blockchains. In this paper, we will discuss how to provide security for Aadhar card enrolment data using blockchain architectures. A blockchain-based Aadhaar would help UIDAI in truly complying with the data protection and privacy stipulations outlined in the Right to Privacy Act judgment

Data Protection and BI

2019 ◽  
pp. 1603-1628
Author(s):  
Daragh O Brien
Keyword(s):  
Big Data ◽  
Data Protection ◽  
Information Quality ◽  
Quality Characteristics ◽  
Data Governance ◽  
Information Governance ◽  
Security Control ◽  
Important Quality ◽  
The Right ◽  
The Relationship

Data Protection (DP) and Privacy are increasingly important quality characteristics of Information, particularly in the context of Business Intelligence and Big Data. This relationship between Data Protection and Information Quality (IQ) is often poorly understood, and DP itself is often misunderstood as being an issue of security control rather than information governance. This chapter examines the relationship between DP, IQ, and Data Governance (DG). It provides an overview of how techniques and practices from IQ and DG can ensure that BI projects are grounded on appropriate privacy controls that ensure that the right information is being used in the right way by the right people to answer the right questions.

scholarly journals Permissioned Blockchains: Towards Privacy Management and Data Regulation Compliance

2020 ◽  
Author(s):  
Paulo Henrique Alves ◽  
Isabella Z. Frajhof ◽  
Fernando A. Correia ◽  
Clarisse De Souza ◽  
Helio Lopes
Keyword(s):  
Data Protection ◽  
Data Privacy ◽  
Distributed Database ◽  
Analytical Framework ◽  
Data Governance ◽  
Sensitive Data ◽  
Significant Control ◽  
Blockchain Technology ◽  
Governance Model ◽  
Permissioned Blockchains

Data privacy and protection has been a trending topic in recent years. The COVID 19 pandemic has brought about additional challenges and tensions. For example, sharing health data across several organizations is crucial for significant control and reduction of massive infection and death risks. This implies the need for broadly collecting and using personal and sensitive data, which raises the complexity of data protection and privacy challenges. Permissioned blockchain technology is one way to empower users in controlling how their data flows through the net, in a transparent and secure way, through an immutable, unified, and distributed database ruled by smart contracts. Given this background, we developed a second layer data governance model for permissioned blockchains based on the Governance Analytical Framework principles to be applied in pandemic situations. The model has been designed to organize the relationship between data subjects, data controller, and data processor. Regarding privacy concerns, our proposal complies with the Brazilian General Data Protection Law.

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