Democratizing data: Environmental data access and its future PDF Download

Author: Michael C. Kruk
Publisher: Frontiers Media SA
ISBN: 2832515231
Category : Science
Languages : en
Pages : 100

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Author: Anne Bowser
Publisher: Frontiers Media SA
ISBN: 2832507263
Category : Science
Languages : en
Pages : 316

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Author: Viktor Mayer-Schönberger
Publisher: Univ of California Press
ISBN: 0520387732
Category : Business & Economics
Languages : en
Pages : 219

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The power of information -- Data alchemy -- Schumpeter's nightmare -- Data capitalism -- Might and machines -- Access rules -- Open data reloaded -- The end of data colonialism.

Author: United States. Congress. Senate. Committee on the Judiciary. Subcommittee on Technology and the Law
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 302

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Author: National Research Council
Publisher: National Academies Press
ISBN: 0309267919
Category : Science
Languages : en
Pages : 201

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Book Description
Digital technologies and networks are now part of everyday work in the sciences, and have enhanced access to and use of scientific data, information, and literature significantly. They offer the promise of accelerating the discovery and communication of knowledge, both within the scientific community and in the broader society, as scientific data and information are made openly available online. The focus of this project was on computer-mediated or computational scientific knowledge discovery, taken broadly as any research processes enabled by digital computing technologies. Such technologies may include data mining, information retrieval and extraction, artificial intelligence, distributed grid computing, and others. These technological capabilities support computer-mediated knowledge discovery, which some believe is a new paradigm in the conduct of research. The emphasis was primarily on digitally networked data, rather than on the scientific, technical, and medical literature. The meeting also focused mostly on the advantages of knowledge discovery in open networked environments, although some of the disadvantages were raised as well. The workshop brought together a set of stakeholders in this area for intensive and structured discussions. The purpose was not to make a final declaration about the directions that should be taken, but to further the examination of trends in computational knowledge discovery in the open networked environments, based on the following questions and tasks: 1. Opportunities and Benefits: What are the opportunities over the next 5 to 10 years associated with the use of computer-mediated scientific knowledge discovery across disciplines in the open online environment? What are the potential benefits to science and society of such techniques? 2. Techniques and Methods for Development and Study of Computer-mediated Scientific Knowledge Discovery: What are the techniques and methods used in government, academia, and industry to study and understand these processes, the validity and reliability of their results, and their impact inside and outside science? 3. Barriers: What are the major scientific, technological, institutional, sociological, and policy barriers to computer-mediated scientific knowledge discovery in the open online environment within the scientific community? What needs to be known and studied about each of these barriers to help achieve the opportunities for interdisciplinary science and complex problem solving? 4. Range of Options: Based on the results obtained in response to items 1-3, define a range of options that can be used by the sponsors of the project, as well as other similar organizations, to obtain and promote a better understanding of the computer-mediated scientific knowledge discovery processes and mechanisms for openly available data and information online across the scientific domains. The objective of defining these options is to improve the activities of the sponsors (and other similar organizations) and the activities of researchers that they fund externally in this emerging research area. The Future of Scientific Knowledge Discovery in Open Networked Environments: Summary of a Workshop summarizes the responses to these questions and tasks at hand.

Author: M. Z. Naser
Publisher: John Wiley & Sons
ISBN: 1119897602
Category : Technology & Engineering
Languages : en
Pages : 610

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Accessible and practical framework for machine learning applications and solutions for civil and environmental engineers This textbook introduces engineers and engineering students to the applications of artificial intelligence (AI), machine learning (ML), and machine intelligence (MI) in relation to civil and environmental engineering projects and problems, presenting state-of-the-art methodologies and techniques to develop and implement algorithms in the engineering domain. Through real-world projects like analysis and design of structural members, optimizing concrete mixtures for site applications, examining concrete cracking via computer vision, evaluating the response of bridges to hazards, and predicating water quality, and energy expenditure in buildings, this textbook offers readers in-depth case studies with solved problems that are commonly faced by civil and environmental engineers. The approaches presented range from simplified to advanced methods, incorporating coding-based and coding-free techniques. Professional engineers and engineering students will find value in the step-by-step examples that are accompanied by sample databases and codes for readers to practice with. Written by a highly qualified professional with significant experience in the field, Machine Learning includes valuable information on: The current state of machine learning and causality in civil and environmental engineering as viewed through a scientometrics analysis, plus a historical perspective Supervised vs. unsupervised learning for regression, classification, and clustering problems Details explainable and causal methods for practical engineering problems Database development, outlining how an engineer can effectively collect and verify appropriate data to be used in machine intelligence analysis A framework for machine learning adoption and application, covering key questions commonly faced by practitioners This textbook is a must-have reference for undergraduate/graduate students to learn concepts on the use of machine learning, for scientists/researchers to learn how to integrate machine learning into civil and environmental engineering, and for design/engineering professionals as a reference guide for undertaking MI design, simulation, and optimization for infrastructure.

Author: United States. Congress. House. Committee on Government Operations. Government Information, Justice, and Agriculture Subcommittee
Publisher:
ISBN:
Category : Depository libraries
Languages : en
Pages : 914

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Author: United States. Congress. Senate. Committee on Governmental Affairs. Subcommittee on Government Information and Regulation
Publisher:
ISBN:
Category : Administrative law
Languages : en
Pages : 708

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Author: Derbali, Abdelkader Mohamed Sghaier
Publisher: IGI Global
ISBN:
Category : Business & Economics
Languages : en
Pages : 389

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Book Description
The crucial challenge of integrating sustainability into business and investment decisions is compounded by the complexity of analyzing vast and intricate datasets to make informed choices. Traditional approaches often fail to provide timely and accurate insights into environmental, social, and governance (ESG) factors, hindering progress toward a greener future. Additionally, the rapid evolution of AI and machine learning in finance has left many professionals needing help to grasp their full potential in advancing sustainability goals. With a comprehensive understanding and practical guidance, organizations can stay caught up in adopting sustainable practices and leveraging AI for financial and environmental benefits. Social and Ethical Implications of AI in Finance for Sustainability offers a timely and comprehensive solution to these challenges by thoroughly examining how AI can safely enhance sustainability in finance. The book bridges the gap between theory and practice, offering practical insights and real-world applications to empower academics, practitioners, policymakers, and students. Through a series of expertly curated chapters, readers will gain a deep understanding of the role AI plays in reshaping finance for a sustainable future. The book's instructional elements, including case studies and expert analysis, provide a roadmap for incorporating AI into sustainability strategies, enabling organizations to make informed decisions and drive positive change.

Author: Ian D. Jones
Publisher: Elsevier
ISBN: 0128227109
Category : Science
Languages : en
Pages : 1105

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Wetzel’s Limnology: Lake and River Ecosystems, Fourth Edition, presents a fully updated revision of the classic textbook Limnology: Lake and River Ecosystems - last published in 2001. The coverage has been thoroughly updated with recent research and theoretical developments. Each chapter of this edited volume has been written by an expert, or team of experts, providing a comprehensive and global perspective, with the editors working closely with the authors to maintain continuity within and between the chapters. This is not only an essential textbook for undergraduate and graduate students in limnology but also a standard reference book for seasoned limnologists and other scientists. Chapters from the third edition have been updated by an international team of experts, incorporating developments from the past two decades Several new chapters have been added, reflecting exciting developments in the field of limnology New color illustrations and images throughout Detailed summaries at the end of each chapter