Author: TennentPublisher: Pearson Education India
ISBN: 9788177581515
Category :
Languages : en
Pages : 108
Book Description
Clark'S Tables: Science Data Book
Author: TennentPublisher: Pearson Education India
ISBN: 9788177581515
Category :
Languages : en
Pages : 108
Book Description
Science and Technology Pocket Data Book
Author: Science and Technology Data Book
Author: Preserving Scientific Data on Our Physical Universe
Author: Steering Committee for the Study on the Long-Term Retention of Selected Scientific and Technical Records of the Federal GovernmentPublisher: National Academies Press
ISBN: 0309521068
Category : Computers
Languages : en
Pages : 59
Book Description
This book advises the National Archives and Records Administration and federal R&D agencies on the long-term retention of scientific and technical data, particularly in electronic formats. It proposes the creation of a National Scientific Information Resource Federation, which would apply a strategic data life-cycle management plan to better link the government's existing scientific data holdings and improve public access to those holdings. The book is expected to draw attention to data management concerns in the context of the current government emphasis on promoting a National Information Infrastructure and to make a significant contribution to improving the inadequate situation regarding our nation's valuable scientific data and information resources.
Science and Technology Pocket Data Book
Author: Scientific Data Management
Author: Arie ShoshaniPublisher: CRC Press
ISBN: 9781420069815
Category : Computers
Languages : en
Pages : 590
Book Description
Dealing with the volume, complexity, and diversity of data currently being generated by scientific experiments and simulations often causes scientists to waste productive time. Scientific Data Management: Challenges, Technology, and Deployment describes cutting-edge technologies and solutions for managing and analyzing vast amounts of data, helping scientists focus on their scientific goals. The book begins with coverage of efficient storage systems, discussing how to write and read large volumes of data without slowing the simulation, analysis, or visualization processes. It then focuses on the efficient data movement and management of storage spaces and explores emerging database systems for scientific data. The book also addresses how to best organize data for analysis purposes, how to effectively conduct searches over large datasets, how to successfully automate multistep scientific process workflows, and how to automatically collect metadata and lineage information. This book provides a comprehensive understanding of the latest techniques for managing data during scientific exploration processes, from data generation to data analysis. Enhanced by numerous detailed color images, it includes real-world examples of applications drawn from biology, ecology, geology, climatology, and more. Check out Dr. Shoshani discuss the book during an interview with International Science Grid This Week (iSGTW): http://www.isgtw.org/?pid=1002259
Data Science
Author: John D. KelleherPublisher: MIT Press
ISBN: 0262347032
Category : Computers
Languages : en
Pages : 280
Book Description
A concise introduction to the emerging field of data science, explaining its evolution, relation to machine learning, current uses, data infrastructure issues, and ethical challenges. The goal of data science is to improve decision making through the analysis of data. Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance. This volume in the MIT Press Essential Knowledge series offers a concise introduction to the emerging field of data science, explaining its evolution, current uses, data infrastructure issues, and ethical challenges. It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets. It is closely related to the fields of data mining and machine learning, but broader in scope. This book offers a brief history of the field, introduces fundamental data concepts, and describes the stages in a data science project. It considers data infrastructure and the challenges posed by integrating data from multiple sources, introduces the basics of machine learning, and discusses how to link machine learning expertise with real-world problems. The book also reviews ethical and legal issues, developments in data regulation, and computational approaches to preserving privacy. Finally, it considers the future impact of data science and offers principles for success in data science projects.
Foundations of Statistics for Data Scientists
Author: Alan AgrestiPublisher: CRC Press
ISBN: 1000462919
Category : Business & Economics
Languages : en
Pages : 486
Book Description
Foundations of Statistics for Data Scientists: With R and Python is designed as a textbook for a one- or two-term introduction to mathematical statistics for students training to become data scientists. It is an in-depth presentation of the topics in statistical science with which any data scientist should be familiar, including probability distributions, descriptive and inferential statistical methods, and linear modeling. The book assumes knowledge of basic calculus, so the presentation can focus on "why it works" as well as "how to do it." Compared to traditional "mathematical statistics" textbooks, however, the book has less emphasis on probability theory and more emphasis on using software to implement statistical methods and to conduct simulations to illustrate key concepts. All statistical analyses in the book use R software, with an appendix showing the same analyses with Python. The book also introduces modern topics that do not normally appear in mathematical statistics texts but are highly relevant for data scientists, such as Bayesian inference, generalized linear models for non-normal responses (e.g., logistic regression and Poisson loglinear models), and regularized model fitting. The nearly 500 exercises are grouped into "Data Analysis and Applications" and "Methods and Concepts." Appendices introduce R and Python and contain solutions for odd-numbered exercises. The book's website has expanded R, Python, and Matlab appendices and all data sets from the examples and exercises.
Science Data
Author: Derek McMonaglePublisher: HarperCollins
ISBN: 9780004708768
Category :
Languages : en
Pages : 256
Book Description
Bits of Power
Author: National Research CouncilPublisher: National Academies Press
ISBN: 030917497X
Category : Computers
Languages : en
Pages : 249
Book Description
Since Galileo corresponded with Kepler, the community of scientists has become increasingly international. A DNA sequence is as significant to a researcher in Novosibirsk as it is to one in Pasadena. And with the advent of electronic communications technology, these experts can share information within minutes. What are the consequences when more bits of scientific data cross more national borders and do it more swiftly than ever before? Bits of Power assesses the state of international exchange of data in the natural sciences, identifying strengths, weaknesses, and challenges. The committee makes recommendations about access to scientific data derived from public funding. The volume examines: Trends in the electronic transfer and management of scientific data. Pressure toward commercialization of scientific data, including the economic aspects of government dissemination of the data. The implications of proposed changes to intellectual property laws and the role of scientists in shaping legislative and legal solutions. Improving access to scientific data by and from the developing world. Bits of Power explores how these issues have been addressed in the European Community and includes examples of successful data transfer activities in the natural sciences. The book will be of interest to scientists and scientific data managers, as well as intellectual property rights attorneys, legislators, government agencies, and international organizations concerned about the electronic flow of scientific data.