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15 November 2021
Data Policy and Governance
Contemporary societies live in a context of hyperconnection to the Internet, changing the way how information and knowledge affect different environments, creating new governance dilemmas related to the digital world. The datafication of various aspects of governments, society and the economy correspond to a new set of possibilities for the application of new policy instruments based on big data and emerging digital technologies such as artificial intelligence, internet of things, blockchain and platforms. These new instruments provide an increasing automation and customization of public services, changes in the cost and benefit ratio for governments and businesses, development of analytical capacities with the potential to improve policies and businesses, improve communication with society.
The emergence of these new information and communication technologies reshapes several institutional aspects of governments, industries, and markets, implying a race for the development and application of these technologies. The emerging digital world takes data as a central resource for the application of digital technologies as instruments to change society. The development of these information and communication technologies depends on large volumes of data so that they can be applied and enable these new analytical capabilities.
Artificial intelligence, for example, depends on data collected and shared so that they can implement techniques of machine learning, deep learning, facial recognition, speech recognition, among others, to generate prediction, simulation, and decision. IoT technologies collect and store data massively, sharing that data so they can generate decision. Platforms collect data in real time and share information to automatically generate customization and process improvements.
In all these situations, the collection, storage, processing and sharing of data is a necessary condition for the development and application of digital technologies and to produce public value. Digital technologies can improve processes, reduce costs, and expand society's well-being. However, big data structures create a series of new governance dilemmas and new risks for society. Among these risks for public and private organizations, we highlight:
• The risks to privacy with the increasing surveillance of citizens by governments and companies;
• Cybersecurity and data leakage problems;
• The generation of algorithmic biases due to the poor quality of the data, producing various forms of injustice and inequality;
• Governance failures resulting from data management;
• Geopolitical problems arising from the delay and problems in the development of technologies due to precarious data sharing structures.
This set of problems has constituted for governments a new agenda aimed at the design of data governance policies and structures. The objective of the design of this data policy and new governance structures is to create templates that guide the actors in the process of collecting, storing, processing, and sharing data, to reduce the risks of new technologies and increase society's trust in the digital transformation.
Data policy and governance is an emerging field of study, with an important institutional innovation process to be addressed. Different institutional approaches and designs of data policy have been proposed, such as data commons, data trust or data foundations. Each of these designs proposes different instruments for dealing with data policy, taking on a dual objective: (1) how to protect citizens' privacy and reduce risks to governments and companies regarding data management? (2) how, at the same time, to provide adequate mechanisms to guarantee data sharing and accelerate technological development? The design of data policy has mobilized different instruments to answer these two fundamental questions. Among these instruments, we highlight:
• The creation of institutional frameworks for the regulation of the data collection, storage, processing and sharing;
• Creation of agencies, mobilizing organizational resources that deliver results in data regulation;
• Definition of institutional processes and routines to deal with cybersecurity and data leakage problems;
• Communication strategies with society.
Data policy is an important contemporary institutional innovation. The policy design perspective makes it possible to analyze the problems and the practice of data policy by understanding the process of choosing policy instruments, the calibration of these instruments in data management practice, the connection between the policy instruments and the intended goals in terms of privacy protection, data collection, storage, processing and sharing, the design of big data instruments for public services, the design of data sharing for policy evaluation, the design of digital policies that connect the development of digital tools with the target population and improvements in public services, data policy aimed at industrial and market development creating mechanisms for data sharing.
This special issue on data policy and governance will welcome articles dealing with topics related to the design of policies for data governance, identification of gaps and institutional problems, evaluation of the results of different institutional data governance designs, evaluation of the design of regulatory instruments, calibration of instruments for design of data policy, data sharing instruments for the development of digital technologies. We are seeking empirical papers that do not just describe data policy and governance but are evaluative and build on this evidence and that focuses on policy design practices for data policy. We welcome case studies or large-scale surveys studies that explore the policy instruments to data governance, dealing with how data sharing improve technological development, work of public managers and public management practices to design data policy.
Topics may include, but are not limited to:
• Implementation and choice of regulatory instruments for data governance;
• Evaluation and case studies on data governance designs;
• Case studies for the design of data protection and privacy policies;
• Policy design to face cybersecurity problems;
• Design of digital transformation policy with big data analytics and evidences to improve public services;
• Policy design for data sharing aiming at technological development.
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15th November 2021: Submission of article manuscripts to special issue editors
1st February 2022: First review of papers complete. Authors informed about acceptance, necessary revisions, or rejection.
1st April 2022: Resubmission of articles (2nd ms version)
1st May 2022: Second review of (revised) papers complete
1st July 2022: Resubmission of articles (3rd ms version)
1st September 2022 (estimated): Electronic publication of articles
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