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This paper provides a systematic and critical review of the economics literature on data as an economic good and draws lessons for data governance. We conclude that focusing on data as an economic good in governance efforts is hardwired to…

Computers and Society · Computer Science 2023-04-19 Nadezhda Purtova , Gijs van Maanen

As platform ecosystems are growing by platform users' data, the importance of data governance has been highlighted. In particular, how to share control and decision rights with platform users are regarded as significant design issues since…

Software Engineering · Computer Science 2017-06-26 Sung Une Lee , Liming Zhu , Ross Jeffery

Government policies aim to address public issues and problems and therefore play a pivotal role in peoples lives. The creation of public policies, however, is complex given the perspective of large and diverse stakeholders involvement,…

Databases · Computer Science 2018-03-20 Barkha Javed , Zaheer Khan , Richard McClatchey

The exponential growth of data in current times and the demand to gain information and knowledge from the data present new challenges for database researchers. Known database systems and algorithms are no longer capable of effectively…

Databases · Computer Science 2017-12-06 Yaron Gonen

Informatics and technological advancements have triggered generation of huge volume of data with varied complexity in its management and analysis. Big Data analytics is the practice of revealing hidden aspects of such data and making…

Databases · Computer Science 2018-03-30 Bikram Karmakar , Indranil Mukhopadhyay

During the last decade or so, we have had a deluge of data from not only science fields but also industry and commerce fields. Although the amount of data available to us is constantly increasing, our ability to process it becomes more and…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-04-13 Nhien-An Le-Khac , Lamine Aouad , M-Tahar Kechadi

Actual organizations, in particular the ones which operate in evolving and distributed environments, need advanced frameworks for the management of the knowledge life cycle. These systems have to be based on the social relations which…

General Physics · Physics 2010-04-26 Luigi Lella , Ignazio Licata

In the dynamic landscape of contemporary business, the wave in data and technological advancements has directed companies toward embracing data-driven decision-making processes. Despite the vast potential that data holds for strategic…

Databases · Computer Science 2024-07-10 Xuejiao Li , Yang Cheng , Xiaoning Xia , Charles Møller

Despite the current interest in Open Data publishing, a formal and comprehensive methodology supporting an organization in deciding which data to publish and carrying out precise procedures for publishing high-quality data, is still…

Databases · Computer Science 2017-07-14 Gianluca Cima

Advancement in information and communication technology (ICT) has given rise to explosion of data in every field of operations. Working with the enormous volume of data (or Big Data, as it is popularly known as) for extraction of useful…

Other Computer Science · Computer Science 2017-05-16 Sanjib Biswas , Jaydip Sen

This paper will discuss the role of an artificially-intelligent computer system as critique-based, implicit-organizational, and an inherently necessary device, deployed in synchrony with parallel governmental policy, as a genuine means of…

Artificial Intelligence · Computer Science 2020-02-27 Christopher A. Tucker

The advent of data-driven science in the 21st century brought about the need for well-organized structured data and associated infrastructure able to facilitate the applications of Artificial Intelligence and Machine Learning. We present an…

Databases · Computer Science 2022-03-03 Alexander Zech , Timur Bazhirov

Software systems are expansive, exhibiting behaviors characteristic of complex systems, such as self-organization and emergence. These systems, highlighted by advancements in Large Language Models (LLMs) and other AI applications developed…

Software Engineering · Computer Science 2025-04-01 Jan Žižka

In the context of Industry 4.0, the manufacturing sector is increasingly facing the challenge of data usability, which is becoming a widespread phenomenon and a new contemporary concern. In response, Data Governance (DG) emerges as a viable…

Databases · Computer Science 2024-09-24 Xuejiao Li , Yang Cheng , Charles Møller

The rapid advancement of artificial intelligence has positioned data governance as a critical concern for responsible AI development. While frameworks exist for conventional AI systems, the potential emergence of Artificial General…

Computers and Society · Computer Science 2025-08-19 Masayuki Hatta

The amount of data in the world is expanding rapidly. Every day, huge amounts of data are created by scientific experiments, companies, and end users' activities. These large data sets have been labeled as "Big Data", and their storage,…

Databases · Computer Science 2020-04-29 Mahdi Bohlouli , Frank Schulz , Lefteris Angelis , David Pahor , Ivona Brandic , David Atlan , Rosemary Tate

Synthetic data, or data generated by machine learning models, is increasingly emerging as a solution to the data access problem. However, its use introduces significant governance and accountability challenges, and potentially debases…

Computers and Society · Computer Science 2025-06-03 Madhavendra Thakur , Jason Hausenloy

The abundance of data has transformed the world in every aspect. It has become the core element in decision making, problem solving, and innovation in almost all areas of life, including business, science, healthcare, education, and many…

Cryptography and Security · Computer Science 2024-03-28 Amen Faridoon , M. Tahar Kechadi

In this paper we present a novel model for governing societies based on modern information technology, which neither relies on manual bureaucratic labor, nor depends on process-based e-government services for governance. We expose the flaws…

Computers and Society · Computer Science 2012-01-05 Alois Paulin

What is a systematic way to efficiently apply a wide spectrum of advanced ML programs to industrial scale problems, using Big Models (up to 100s of billions of parameters) on Big Data (up to terabytes or petabytes)? Modern parallelization…