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Envisioning the Data Science Discipline
The need to manage, analyze, and extract knowledge from data is pervasive across industry, government, and academia. Scientists, engineers, and executives routinely encounter enormous volumes of data, and new techniques and tools are emerging to create knowledge out of these data, some of them capable of working with real-time streams of data. The nation�e(tm)s ability to make use of these data depends on the availability of an educated workforce with necessary expertise. With these new capabilities have come novel ethical challenges regarding the effectiveness and appropriateness of broad applications of data analyses. The field of data science has emerged to address the proliferation of ...
Envisioning the Data Science Discipline
The need to manage, analyze, and extract knowledge from data is pervasive across industry, government, and academia. Scientists, engineers, and executives routinely encounter enormous volumes of data, and new techniques and tools are emerging to create knowledge out of these data, some of them capable of working with real-time streams of data. The nation's ability to make use of these data depends on the availability of an educated workforce with necessary expertise. With these new capabilities have come novel ethical challenges regarding the effectiveness and appropriateness of broad applications of data analyses. The field of data science has emerged to address the proliferation of data an...
Data Science for Undergraduates
Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent. Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field.
Data Science Careers, Training, and Hiring
This book is an information packed overview of how to structure a data science career, a data science degree program, and how to hire a data science team, including resources and insights from the authors experience with national and international large-scale data projects as well as industry, academic and government partnerships, education, and workforce. Outlined here are tips and insights into navigating the data ecosystem as it currently stands, including career skills, current training programs, as well as practical hiring help and resources. Also, threaded through the book is the outline of a data ecosystem, as it could ultimately emerge, and how career seekers, training programs, and ...
Information and Communication Technologies for Development. Strengthening Southern-Driven Cooperation as a Catalyst for ICT4D
The two volumes IFIP AICT 551 and 552 constitute the refereed proceedings of the 15th IFIP WG 9.4 International Conference on Social Implications of Computers in Developing Countries, ICT4D 2019, held in Dar es Salaam, Tanzania, in May 2019. The 97 revised full papers and 2 short papers presented were carefully reviewed and selected from 185 submissions. The papers present a wide range of perspectives and disciplines including (but not limited to) public administration, entrepreneurship, business administration, information technology for development, information management systems, organization studies, philosophy, and management. They are organized in the following topical sections: communities, ICT-enabled networks, and development; digital platforms for development; ICT for displaced population and refugees. How it helps? How it hurts?; ICT4D for the indigenous, by the indigenous and of the indigenous; local technical papers; pushing the boundaries - new research methods, theory and philosophy in ICT4D; southern-driven human-computer interaction; sustainable ICT, informatics, education and learning in a turbulent world - "doing the safari way”.
Informatics Education in Healthcare
This heavily revised second edition defines the current state of the art for informatics education in medicine and healthcare. This field has continued to undergo considerable changes as the field of informatics continues to evolve. The book features extensively revised chapters addressing the latest developments in areas including relevant informatics concepts for those who work in health information technology and those teaching informatics courses in clinical settings, techniques for teaching informatics with limited resources, and the use of online modalities in bioinformatics research education. New topics covered include how to get appropriate accreditation for an informatics program, data science and bioinformatics education, and undergraduate health informatics education. Informatics Education in Healthcare: Lessons Learned addresses the broad range of informatics education programs and available techniques for teaching informatics. It therefore provides a valuable reference for all involved in informatics education.
Guide to Teaching Data Science
Data science is a new field that touches on almost every domain of our lives, and thus it is taught in a variety of environments. Accordingly, the book is suitable for teachers and lecturers in all educational frameworks: K-12, academia and industry. This book aims at closing a significant gap in the literature on the pedagogy of data science. While there are many articles and white papers dealing with the curriculum of data science (i.e., what to teach?), the pedagogical aspect of the field (i.e., how to teach?) is almost neglected. At the same time, the importance of the pedagogical aspects of data science increases as more and more programs are currently open to a variety of people. This ...
Ethics in Statistics
Data plays a vital role in different parts of our lives. In the world of big data, and policy determined by a variety of statistical artifacts, discussions around the ethics of data gathering, manipulation and presentation are increasingly important. Ethics in Statistics aims to make a significant contribution to that debate. The processes of gathering data through sampling, summarising of the findings, and extending results to a population, need to be checked via an ethical prospective, as well as a statistical one. Statistical learning without ethics can be harmful for mankind. This edited collection brings together contributors in the field of data science, data analytics and statistics, to share their thoughts about the role of ethics in different aspects of statistical learning.
Democratizing Our Data
Why America's data system is broken, and how to fix it. Why, with data increasingly important, available, valuable and cheap, are the data produced by the American government getting worse and costing more? State and local governments rely on population data from the US Census Bureau; prospective college students and their parents can check data from the National Center for Education Statistics; small businesses can draw on data about employment and wages from the Bureau of Labor Statistics. But often the information they get is out of date or irrelevant, based on surveys--a form of information gathering notorious for low response rates. In A Data Manifesto, Julia Lane argues that bad data is bad for democracy. Her book is a wake-up call to America to fix its broken public data system.
