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Data Matters

Data Matters PDF Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 030948247X
Category : Science
Languages : en
Pages : 103

Book Description
In an increasingly interconnected world, perhaps it should come as no surprise that international collaboration in science and technology research is growing at a remarkable rate. As science and technology capabilities grow around the world, U.S.-based organizations are finding that international collaborations and partnerships provide unique opportunities to enhance research and training. International research agreements can serve many purposes, but data are always involved in these collaborations. The kinds of data in play within international research agreements varies widely and may range from financial and consumer data, to Earth and space data, to population behavior and health data, to specific project-generated dataâ€"this is just a narrow set of examples of research data but illustrates the breadth of possibilities. The uses of these data are various and require accounting for the effects of data access, use, and sharing on many different parties. Cultural, legal, policy, and technical concerns are also important determinants of what can be done in the realms of maintaining privacy, confidentiality, and security, and ethics is a lens through which the issues of data, data sharing, and research agreements can be viewed as well. A workshop held on March 14-16, 2018, in Washington, DC explored the changing opportunities and risks of data management and use across disciplinary domains. The third workshop in a series, participants gathered to examine advisory principles for consideration when developing international research agreements, in the pursuit of highlighting promising practices for sustaining and enabling international research collaborations at the highest ethical level possible. The intent of the workshop was to explore, through an ethical lens, the changing opportunities and risks associated with data management and use across disciplinary domainsâ€"all within the context of international research agreements. This publication summarizes the presentations and discussions from the workshop.

Dark Data

Dark Data PDF Author: David J. Hand
Publisher: Princeton University Press
ISBN: 0691234469
Category : Computers
Languages : en
Pages : 344

Book Description
"Data describe and represent the world. However, no matter how big they may be, data sets don't - indeed cannot - capture everything. Data are measurements - and, as such, they represent only what has been measured. They don't necessarily capture all the information that is relevant to the questions we may want to ask. If we do not take into account what may be missing/unknown in the data we have, we may find ourselves unwittingly asking questions that our data cannot actually address, come to mistaken conclusions, and make disastrous decisions. In this book, David Hand looks at the ubiquitous phenomenon of "missing data." He calls this "dark data" (making a comparison to "dark matter" - i.e., matter in the universe that we know is there, but which is invisible to direct measurement). He reveals how we can detect when data is missing, the types of settings in which missing data are likely to be found, and what to do about it. It can arise for many reasons, which themselves may not be obvious - for example, asymmetric information in wars; time delays in financial trading; dropouts in clinical trials; deliberate selection to enhance apparent performance in hospitals, policing, and schools; etc. What becomes clear is that measuring and collecting more and more data (big data) will not necessarily lead us to better understanding or to better decisions. We need to be vigilant to what is missing or unknown in our data, so that we can try to control for it. How do we do that? We can be alert to the causes of dark data, design better data-collection strategies that sidestep some of these causes - and, we can ask better questions of our data, which will lead us to deeper insights and better decisions"--

Data Matters

Data Matters PDF Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 030948247X
Category : Science
Languages : en
Pages : 103

Book Description
In an increasingly interconnected world, perhaps it should come as no surprise that international collaboration in science and technology research is growing at a remarkable rate. As science and technology capabilities grow around the world, U.S.-based organizations are finding that international collaborations and partnerships provide unique opportunities to enhance research and training. International research agreements can serve many purposes, but data are always involved in these collaborations. The kinds of data in play within international research agreements varies widely and may range from financial and consumer data, to Earth and space data, to population behavior and health data, to specific project-generated dataâ€"this is just a narrow set of examples of research data but illustrates the breadth of possibilities. The uses of these data are various and require accounting for the effects of data access, use, and sharing on many different parties. Cultural, legal, policy, and technical concerns are also important determinants of what can be done in the realms of maintaining privacy, confidentiality, and security, and ethics is a lens through which the issues of data, data sharing, and research agreements can be viewed as well. A workshop held on March 14-16, 2018, in Washington, DC explored the changing opportunities and risks of data management and use across disciplinary domains. The third workshop in a series, participants gathered to examine advisory principles for consideration when developing international research agreements, in the pursuit of highlighting promising practices for sustaining and enabling international research collaborations at the highest ethical level possible. The intent of the workshop was to explore, through an ethical lens, the changing opportunities and risks associated with data management and use across disciplinary domainsâ€"all within the context of international research agreements. This publication summarizes the presentations and discussions from the workshop.

Matters of Life and Data

Matters of Life and Data PDF Author: Charles D. Morgan
Publisher: Morgan James Publishing
ISBN: 1630474665
Category : Business & Economics
Languages : en
Pages : 346

Book Description
Thanks to Edward Snowden and the N.S.A., “Big Data” is a hot---and controversial---topic these days. In Charles D. Morgan’s lively memoir, "Matters of Life and Data", he shows that data gathering itself is neither good nor bad---it’s how it’s used that matters. But Big Data isn’t the whole story here---Morgan is also a champion race car driver, a jet pilot, and an all-around gadget-geek-turned-business-visionary. Life is about solving the problems we’re faced with, and Charles Morgan’s life has been one of trial, error, and great achievement. His story will inspire all who read it.

Measuring Race

Measuring Race PDF Author: Robert T. Teranishi
Publisher: Multicultural Education
ISBN: 9780807763612
Category : Education
Languages : en
Pages : 0

Book Description
"Understanding the complexity of racial categories is essential for achieving equity and reducing inequality in the United States. The authors show how that by disaggregating data on race, researchers and policymakers can more fully understand how race is factored in educational settings"--

Data Feminism

Data Feminism PDF Author: Catherine D'Ignazio
Publisher: MIT Press
ISBN: 0262358530
Category : Social Science
Languages : en
Pages : 328

Book Description
A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought. Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.” Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.

Training Data for Machine Learning

Training Data for Machine Learning PDF Author: Anthony Sarkis
Publisher: "O'Reilly Media, Inc."
ISBN: 1492094498
Category : Computers
Languages : en
Pages : 332

Book Description
Your training data has as much to do with the success of your data project as the algorithms themselves because most failures in AI systems relate to training data. But while training data is the foundation for successful AI and machine learning, there are few comprehensive resources to help you ace the process. In this hands-on guide, author Anthony Sarkis--lead engineer for the Diffgram AI training data software--shows technical professionals, managers, and subject matter experts how to work with and scale training data, while illuminating the human side of supervising machines. Engineering leaders, data engineers, and data science professionals alike will gain a solid understanding of the concepts, tools, and processes they need to succeed with training data. With this book, you'll learn how to: Work effectively with training data including schemas, raw data, and annotations Transform your work, team, or organization to be more AI/ML data-centric Clearly explain training data concepts to other staff, team members, and stakeholders Design, deploy, and ship training data for production-grade AI applications Recognize and correct new training-data-based failure modes such as data bias Confidently use automation to more effectively create training data Successfully maintain, operate, and improve training data systems of record

Customs Matters

Customs Matters PDF Author: Mr. Augusto A Perez Azcarraga
Publisher: International Monetary Fund
ISBN:
Category : Business & Economics
Languages : en
Pages : 320

Book Description
Customs administrations around the world face new challenges: an increasing volume of international trade, a revolution in new technologies, and fundamental changes in business models. The benefits of a well-performing customs administration are clear, as is the need to develop efficient, effective, fair, and modern customs administrations. Customs Matters analyzes the many changes and challenges customs administrations face and pro-poses ways to address them. By offering a cross-sectional view of the main aspects of customs ad-ministration, the book guides policymakers and customs officials as they evaluate the current state of their customs system with a view to developing, reinforcing, or relaunching their own roadmaps for customs modernization.

Open Scientific Data

Open Scientific Data PDF Author: Vera J. Lipton
Publisher:
ISBN: 9781838809867
Category : Big data
Languages : en
Pages :

Book Description
Public science is critical to the economy and to society. However, much of the beneficial impact of scientific research only occurs when scientific knowledge is disseminated broadly and is used by others. This book examines the emerging policy, law and practice of facilitating open access to scientific research data. One particular focus is to examine the open data policies recently introduced by research funders and publishers, and the potential in these for driving the practice of open scientific data into the future. This study identifies five major stumbling blocks to sustainable open scientific data. Firstly, it is the prevailing mindset that facilitating open access to data is analogous to facilitating open access to publications and, therefore, research data can easily be shared, with research funders and librarians effectively leading the process. Secondly, it is the unclear meaning of the term data which causes confusion among stakeholders. Thirdly, it is the misunderstood incentives for data sharing and the additional inputs required from researchers. Fourthly, data privacy—an issue that only applies to selected research datasets, and yet appears to dominate the discussion about open research data. Finally, there is a copyright law, which poses challenges at different stages of data release and reuse. In this book, it is argued that the above problems can be addressed using a staged model for open scientific data. I draw specifically on the practice with open scientific data at CERN (the European Organization for Nuclear Research) and the practice of sharing clinical trial data to argue that open data can be shared at various stages of processing and diversification. This model is supplemented by recommendations proposing changes to existing open data mandates and the introduction of a text and data mining exemption into Australian copyright law.

From the Internet of Things to the Internet of Ideas: The Role of Artificial Intelligence

From the Internet of Things to the Internet of Ideas: The Role of Artificial Intelligence PDF Author: Abdalmuttaleb M. A. Musleh Al-Sartawi
Publisher: Springer Nature
ISBN: 3031177460
Category : Technology & Engineering
Languages : en
Pages : 727

Book Description
This book shows latest research on the role Artificial inelegance in enabling IoT to evoke IoI, and how IoI flourish inside technologies like social media platforms, social networks: communities of practice/interest, to assure a globally sustainable unit where humans integrate with machines to collaboratively share ideas and solve complex problems. Such a book holds several benefits. It will reveal theoretical practical, and managerial implications through discussions that will embrace a wide array of technologies focused on the role of AI enabled IoT to evoke IoI. EAMMIS 2022 was organized by the Bridges Foundation in cooperation with Coventry University, UK on the 10th and 11th of June 2022. EAMMIS 2022 theme was From the Internet of Things to the Internet of Ideas: The role of Artificial Intelligence. The papers presented at the conference provide a holistic view of AI and its applications, IOT and the IOI which will help societies to better use and benefit from AI, IOT and IOI to develop future strategies and actions.

Measure What Matters

Measure What Matters PDF Author: John Doerr
Publisher: Penguin
ISBN: 052553623X
Category : Business & Economics
Languages : en
Pages : 322

Book Description
#1 New York Times Bestseller Legendary venture capitalist John Doerr reveals how the goal-setting system of Objectives and Key Results (OKRs) has helped tech giants from Intel to Google achieve explosive growth—and how it can help any organization thrive. In the fall of 1999, John Doerr met with the founders of a start-up whom he'd just given $12.5 million, the biggest investment of his career. Larry Page and Sergey Brin had amazing technology, entrepreneurial energy, and sky-high ambitions, but no real business plan. For Google to change the world (or even to survive), Page and Brin had to learn how to make tough choices on priorities while keeping their team on track. They'd have to know when to pull the plug on losing propositions, to fail fast. And they needed timely, relevant data to track their progress—to measure what mattered. Doerr taught them about a proven approach to operating excellence: Objectives and Key Results. He had first discovered OKRs in the 1970s as an engineer at Intel, where the legendary Andy Grove ("the greatest manager of his or any era") drove the best-run company Doerr had ever seen. Later, as a venture capitalist, Doerr shared Grove's brainchild with more than fifty companies. Wherever the process was faithfully practiced, it worked. In this goal-setting system, objectives define what we seek to achieve; key results are how those top-priority goals will be attained with specific, measurable actions within a set time frame. Everyone's goals, from entry level to CEO, are transparent to the entire organization. The benefits are profound. OKRs surface an organization's most important work. They focus effort and foster coordination. They keep employees on track. They link objectives across silos to unify and strengthen the entire company. Along the way, OKRs enhance workplace satisfaction and boost retention. In Measure What Matters, Doerr shares a broad range of first-person, behind-the-scenes case studies, with narrators including Bono and Bill Gates, to demonstrate the focus, agility, and explosive growth that OKRs have spurred at so many great organizations. This book will help a new generation of leaders capture the same magic.