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Big Data, Little Data, No Data
\"Big Data\" is on the covers ofScience, Nature, theEconomist, andWiredmagazines, on the front pages of theWall Street Journaland theNew York Times.But despite the media hyperbole, as Christine Borgman points out in this examination of data and scholarly research, having the right data is usually better than having more data; little data can be just as valuable as big data. In many cases, there are no data -- because relevant data don't exist, cannot be found, or are not available. Moreover, data sharing is difficult, incentives to do so are minimal, and data practices vary widely across disciplines.Borgman, an often-cited authority on scholarly communication, argues that data have no value or meaning in isolation; they exist within a knowledge infrastructure -- an ecology of people, practices, technologies, institutions, material objects, and relationships. After laying out the premises of her investigation -- six \"provocations\" meant to inspire discussion about the uses of data in scholarship -- Borgman offers case studies of data practices in the sciences, the social sciences, and the humanities, and then considers the implications of her findings for scholarly practice and research policy. To manage and exploit data over the long term, Borgman argues, requires massive investment in knowledge infrastructures; at stake is the future of scholarship.
eBook
The computing universe : a journey through a revolution
\"Computers now impact almost every aspect of our lives, from our social interactions to the safety and performance of our cars. How did this happen in such a short time? And this is just the beginning. In this book, Tony Hey and Gyuri Pâapay lead us on a journey from the early days of computers in the 1930s to the cutting-edge research of the present day that will shape computing in the coming decades. Along the way, they explain the ideas behind hardware, software, algorithms, Moore's Law, the birth of the personal computer, the Internet and the Web, the Turing Test, Jeopardy's Watson, World of Warcraft, spyware, Google, Facebook, and quantum computing. This book also introduces the fascinating cast of dreamers and inventors who brought these great technological developments into every corner of the modern world. This exciting and accessible introduction will open up the universe of computing to anyone who has ever wondered where his or her smartphone came from\"-- Provided by publisher.
Book
Connected Code
Coding, once considered an arcane craft practiced by solitary techies, is now recognized by educators and theorists as a crucial skill, even a new literacy, for all children. Programming is often promoted in K-12 schools as a way to encourage \"computational thinking\" -- which has now become the umbrella term for understanding what computer science has to contribute to reasoning and communicating in an ever-increasingly digital world.InConnected Code,Yasmin Kafai and Quinn Burke argue that although computational thinking represents an excellent starting point, the broader conception of \"computational participation\" better captures the twenty-first-century reality. Computational participation moves beyond the individual to focus on wider social networks and a DIY culture of digital \"making.\" Kafai and Burke describe contemporary examples of computational participation: students who code not for the sake of coding but to create games, stories, and animations to share; the emergence of youth programming communities; the practices and ethical challenges of remixing (rather than starting from scratch); and the move beyond stationary screens to programmable toys, tools, and textiles.
eBook
Careers in computer science
Careers in computer science are among the hottest, most in-demand occupations in the United States today. Comments from people in the industry, current statistics and forecasts, and realistic descriptions provide a useful look at computer science jobs ranging from software developers to information security analysts to database administrators.
Book
Research methods in human-computer interaction
Research Methods in Human-Computer Interaction is a comprehensive guide to performing research and is essential reading for both quantitative and qualitative methods.Since the first edition was published in 2009, the book has been adopted for use at leading universities around the world, including Harvard University, Carnegie-Mellon University.
eBook
The computer : a very short introduction
Computers have changed so much since the room-filling, bulky magnetic tape running monsters of the mid 20th century. They now form a vital part of most people's lives. And they are more ubiquitous than might be thought - you may have more than 30 computers in your home: not just the desktop and laptop but think of the television, the fridge, the microwave. But what is the basic nature of the modern computer? How does it work? How has it been possible to squeeze so much power into increasingly small machines? And what will the next generations of computers look like? In this Very Short Introduction, Darrel Ince looks at the basic concepts behind all computers; the changes in hardware and software that allowed computers to become so small and commonplace; the challenges produced by the computer revolution - especially whole new modes of cybercrime and security issues; the Internet and the advent of 'cloud computing'; and the promise of whole new horizons opening up with quantum computing, and even computing using DNA-- Source other than Library of Congress.
Book
Data Clustering
Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains.The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as feature selection, agglomerative clustering, partitional clustering, density-based clustering, probabilistic clustering, grid-based clustering, spectral clustering, and nonnegative matrix factorization Domains, covering methods used for different domains of data, such as categorical data, text data, multimedia data, graph data, biological data, stream data, uncertain data, time series clustering, high-dimensional clustering, and big data Variations and Insights, discussing important variations of the clustering process, such as semisupervised clustering, interactive clustering, multiview clustering, cluster ensembles, and cluster validation In this book, top researchers from around the world explore the characteristics of clustering problems in a variety of application areas. They also explain how to glean detailed insight from the clustering process-including how to verify the quality of the underlying clusters-through supervision, human intervention, or the automated generation of alternative clusters.
eBook
Computing tomorrow : future research directions in computer science
The book's purpose is to show that long-term research in computer science is crucial and that it must not be driven solely by commercial considerations. The authors don't shirk difficult aspects of their topics, but try to expose them in the simplest terms possible, in order that the reader can understand the issues involved.
Book
SciPy 1.0: fundamental algorithms for scientific computing in Python
SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.
This Perspective describes the development and capabilities of SciPy 1.0, an open source scientific computing library for the Python programming language.
Journal Article