Download or read book Data Management for Social Scientists written by Nils B. Weidmann and published by Cambridge University Press. This book was released on 2023-03-09 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: Equips social scientists with the tools and techniques to conduct quantitative research in the age of big data.

Download or read book Data Management for Researchers written by Kristin Briney and published by Pelagic Publishing Ltd. This book was released on 2015-09-01 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to everything scientists need to know about data management, this book is essential for researchers who need to learn how to organize, document and take care of their own data. Researchers in all disciplines are faced with the challenge of managing the growing amounts of digital data that are the foundation of their research. Kristin Briney offers practical advice and clearly explains policies and principles, in an accessible and in-depth text that will allow researchers to understand and achieve the goal of better research data management. Data Management for Researchers includes sections on: * The data problem – an introduction to the growing importance and challenges of using digital data in research. Covers both the inherent problems with managing digital information, as well as how the research landscape is changing to give more value to research datasets and code. * The data lifecycle – a framework for data’s place within the research process and how data’s role is changing. Greater emphasis on data sharing and data reuse will not only change the way we conduct research but also how we manage research data. * Planning for data management – covers the many aspects of data management and how to put them together in a data management plan. This section also includes sample data management plans. * Documenting your data – an often overlooked part of the data management process, but one that is critical to good management; data without documentation are frequently unusable. * Organizing your data – explains how to keep your data in order using organizational systems and file naming conventions. This section also covers using a database to organize and analyze content. * Improving data analysis – covers managing information through the analysis process. This section starts by comparing the management of raw and analyzed data and then describes ways to make analysis easier, such as spreadsheet best practices. It also examines practices for research code, including version control systems. * Managing secure and private data – many researchers are dealing with data that require extra security. This section outlines what data falls into this category and some of the policies that apply, before addressing the best practices for keeping data secure. * Short-term storage – deals with the practical matters of storage and backup and covers the many options available. This section also goes through the best practices to insure that data are not lost. * Preserving and archiving your data – digital data can have a long life if properly cared for. This section covers managing data in the long term including choosing good file formats and media, as well as determining who will manage the data after the end of the project. * Sharing/publishing your data – addresses how to make data sharing across research groups easier, as well as how and why to publicly share data. This section covers intellectual property and licenses for datasets, before ending with the altmetrics that measure the impact of publicly shared data. * Reusing data – as more data are shared, it becomes possible to use outside data in your research. This chapter discusses strategies for finding datasets and lays out how to cite data once you have found it. This book is designed for active scientific researchers but it is useful for anyone who wants to get more from their data: academics, educators, professionals or anyone who teaches data management, sharing and preservation. "An excellent practical treatise on the art and practice of data management, this book is essential to any researcher, regardless of subject or discipline." —Robert Buntrock, Chemical Information Bulletin

Download or read book Data Management in R written by Martin Elff and published by Sage Publications Limited. This book was released on 2021-01-09 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: An invaluable step-by-step, pedagogically engaging guide to data management in R for social science researchers, this book shows students how to recode and document data, as well as how to combine data from different sources or import from statistical packages other than R.

Download or read book Data Management for Social Scientists written by Nils B. Weidmann and published by Cambridge University Press. This book was released on 2023-03-09 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 'data revolution' offers many new opportunities for research in the social sciences. Increasingly, social and political interactions can be recorded digitally, leading to vast amounts of new data available for research. This poses new challenges for organizing and processing research data. This comprehensive introduction covers the entire range of data management techniques, from flat files to database management systems. It demonstrates how established techniques and technologies from computer science can be applied in social science projects, drawing on a wide range of different applied examples. This book covers simple tools such as spreadsheets and file-based data storage and processing, as well as more powerful data management software like relational databases. It goes on to address advanced topics such as spatial data, text as data, and network data. This book is one of the first to discuss questions of practical data management specifically for social science projects. This title is also available as Open Access on Cambridge Core.

Download or read book Introduction to Data Science for Social and Policy Research written by Jose Manuel Magallanes Reyes and published by Cambridge University Press. This book was released on 2017-09-21 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive guide provides a step-by-step approach to data collection, cleaning, formatting, and storage, using Python and R.

Download or read book Knowledge Discovery in the Social Sciences written by Xiaoling Shu and published by University of California Press. This book was released on 2020-02-04 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge Discovery in the Social Sciences helps readers find valid, meaningful, and useful information. It is written for researchers and data analysts as well as students who have no prior experience in statistics or computer science. Suitable for a variety of classes—including upper-division courses for undergraduates, introductory courses for graduate students, and courses in data management and advanced statistical methods—the book guides readers in the application of data mining techniques and illustrates the significance of newly discovered knowledge. Readers will learn to: • appreciate the role of data mining in scientific research • develop an understanding of fundamental concepts of data mining and knowledge discovery • use software to carry out data mining tasks • select and assess appropriate models to ensure findings are valid and meaningful • develop basic skills in data preparation, data mining, model selection, and validation • apply concepts with end-of-chapter exercises and review summaries

Download or read book Managing and Sharing Research Data written by Louise Corti and published by SAGE. This book was released on 2014-02-04 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research funders in the UK, USA and across Europe are implementing data management and sharing policies to maximize openness of data, transparency and accountability of the research they support. Written by experts from the UK Data Archive with over 20 years experience, this book gives post-graduate students, researchers and research support staff the data management skills required in today’s changing research environment. The book features guidance on: how to plan your research using a data management checklist how to format and organize data how to store and transfer data research ethics and privacy in data sharing and intellectual property rights data strategies for collaborative research how to publish and cite data how to make use of other people’s research data, illustrated with six real-life case studies of data use.

Download or read book Data Collection and Management written by Magda Stouthamer-Loeber and published by SAGE Publications, Incorporated. This book was released on 1995-08-08 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tired of a trial-and-error approach to collecting and managing data? Data Collection and Management offers helpful information on managing research projects. By stressing how to use good standards for data collecting and processing, the authors cover such important how-tos as planning research activities; making budgetary decisions and keeping the budget under control; hiring, training, and supervising field interviewing staff; establishing whether interviewers are ready to start interviewing; and ensuring high participant acquisition and retention rates. The book also covers using computerized information systems for tracking data collected and the data management process. Proposal writers, principal investigators, graduate research students, and project coordinators of research requiring large-scale field data collection will find the book to be an indispensable tool.

Download or read book Research Data Management written by Joyce M. Ray and published by Purdue University Press. This book was released on 2014 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: It has become increasingly accepted that important digital data must be retained and shared in order to preserve and promote knowledge, advance research in and across all disciplines of scholarly endeavor, and maximize the return on investment of public funds. To meet this challenge, colleges and universities are adding data services to existing infrastructures by drawing on the expertise of information professionals who are already involved in the acquisition, management and preservation of data in their daily jobs. Data services include planning and implementing good data management practices, thereby increasing researchers' ability to compete for grant funding and ensuring that data collections with continuing value are preserved for reuse. This volume provides a framework to guide information professionals in academic libraries, presses, and data centers through the process of managing research data from the planning stages through the life of a grant project and beyond. It illustrates principles of good practice with use-case examples and illuminates promising data service models through case studies of innovative, successful projects and collaborations.

Download or read book Social Science Research written by Anol Bhattacherjee and published by CreateSpace. This book was released on 2012-04-01 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.

Download or read book Decoding the Social World written by Sandra Gonzalez-Bailon and published by MIT Press. This book was released on 2017-12-22 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: How data science and the analysis of networks help us solve the puzzle of unintended consequences. Social life is full of paradoxes. Our intentional actions often trigger outcomes that we did not intend or even envision. How do we explain those unintended effects and what can we do to regulate them? In Decoding the Social World, Sandra González-Bailón explains how data science and digital traces help us solve the puzzle of unintended consequences—offering the solution to a social paradox that has intrigued thinkers for centuries. Communication has always been the force that makes a collection of people more than the sum of individuals, but only now can we explain why: digital technologies have made it possible to parse the information we generate by being social in new, imaginative ways. And yet we must look at that data, González-Bailón argues, through the lens of theories that capture the nature of social life. The technologies we use, in the end, are also a manifestation of the social world we inhabit. González-Bailón discusses how the unpredictability of social life relates to communication networks, social influence, and the unintended effects that derive from individual decisions. She describes how communication generates social dynamics in aggregate (leading to episodes of “collective effervescence”) and discusses the mechanisms that underlie large-scale diffusion, when information and behavior spread “like wildfire.” She applies the theory of networks to illuminate why collective outcomes can differ drastically even when they arise from the same individual actions. By opening the black box of unintended effects, González-Bailón identifies strategies for social intervention and discusses the policy implications—and how data science and evidence-based research embolden critical thinking in a world that is constantly changing.

Download or read book Engaging Researchers with Data Management written by Connie Clare and published by . This book was released on 2019 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: Engaging Researchers with Data Management is an invaluable collection of 24 case studies, drawn from institutions across the globe, that demonstrate clearly and practically how to engage the research community with RDM. These case studies together illustrate the variety of innovative strategies research institutions have developed to engage with their researchers about managing research data. Each study is presented concisely and clearly, highlighting the essential ingredients that led to its success and challenges encountered along the way. By interviewing key staff about their experiences.

Download or read book Data Management in R written by Martin Elff and published by SAGE. This book was released on 2020-12-02 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: An invaluable, step-by-step guide to data management in R for social science researchers. This book will show you how to recode data, combine data from different sources, document data, and import data from statistical packages other than R. It explores both qualitative and quantitative data and is packed with a range of supportive learning features such as code examples, overview boxes, images, tables, and diagrams.

Download or read book Laboratory Experiments in the Social Sciences written by Murray Webster and published by Elsevier. This book was released on 2007-07-03 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: Laboratory Experiments in the Social Sciences is the only book providing core information for researchers about the ways and means to conduct experiments. Its comprehensive regard for laboratory experiments encompasses "how-to explanations, investigations of philosophies and ethics, explorations of experiments in specific social science disciplines, and summaries of both the history and future of social science laboratories. No other book offers such a direct avenue to enlarging our knowledge in the social sciences.This collection of original chapters combines instructions and advice about the design of laboratory experiments in the social sciences with the array of other issues. While there are books on experimental design and chapters in more general methods books on design, theory, and ethical issues, no other book attempts to discuss the fundamental ideas of the philosophy of science or lays out the methods comprehensively or in such detail. Experimentation has recently prospered because of increasing interest in cross-disciplinary syntheses, and this book of advice, guidelines, and observations underline its potential and increasing importance.· Provides a comprehensive summary of issues in social science experimentation, from ethics to design, management, and financing· Offers "how-to" explanations of the problems and challenges faced by everyone involved in social science experiments· Pays attention to both practical problems and to theoretical and philosophical arguments· Defines commonalities and distinctions within and among experimental situations across the social sciences

Download or read book Qualitative Analysis for Social Scientists written by Anselm L. Strauss and published by Cambridge University Press. This book was released on 1987-06-26 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: The teaching of qualitative analysis in the social sciences is rarely undertaken in a structured way. This handbook is designed to remedy that and to present students and researchers with a systematic method for interpreting qualitative data', whether derived from interviews, field notes, or documentary materials. The special emphasis of the book is on how to develop theory through qualitative analysis. The reader is provided with the tools for doing qualitative analysis, such as codes, memos, memo sequences, theoretical sampling and comparative analysis, and diagrams, all of which are abundantly illustrated by actual examples drawn from the author's own varied qualitative research and research consultations, as well as from his research seminars. Many of the procedural discussions are concluded with rules of thumb that can usefully guide the researchers' analytic operations. The difficulties that beginners encounter when doing qualitative analysis and the kinds of persistent questions they raise are also discussed, as is the problem of how to integrate analyses. In addition, there is a chapter on the teaching of qualitative analysis and the giving of useful advice during research consultations, and there is a discussion of the preparation of material for publication. The book has been written not only for sociologists but for all researchers in the social sciences and in such fields as education, public health, nursing, and administration who employ qualitative methods in their work.

Download or read book Data Journeys in the Sciences written by Sabina Leonelli and published by Springer Nature. This book was released on 2020-06-29 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: This groundbreaking, open access volume analyses and compares data practices across several fields through the analysis of specific cases of data journeys. It brings together leading scholars in the philosophy, history and social studies of science to achieve two goals: tracking the travel of data across different spaces, times and domains of research practice; and documenting how such journeys affect the use of data as evidence and the knowledge being produced. The volume captures the opportunities, challenges and concerns involved in making data move from the sites in which they are originally produced to sites where they can be integrated with other data, analysed and re-used for a variety of purposes. The in-depth study of data journeys provides the necessary ground to examine disciplinary, geographical and historical differences and similarities in data management, processing and interpretation, thus identifying the key conditions of possibility for the widespread data sharing associated with Big and Open Data. The chapters are ordered in sections that broadly correspond to different stages of the journeys of data, from their generation to the legitimisation of their use for specific purposes. Additionally, the preface to the volume provides a variety of alternative “roadmaps” aimed to serve the different interests and entry points of readers; and the introduction provides a substantive overview of what data journeys can teach about the methods and epistemology of research.

Download or read book Research Data Management and Data Literacies written by Koltay Tibor and published by Chandos Publishing. This book was released on 2021-10-31 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research Data Management and Data Literacies help researchers familiarize themselves with RDM, and with the services increasingly offered by libraries. This new volume looks at data-intensive science, or 'Science 2.0' as it is sometimes termed in commentary, from a number of perspectives, including the tasks academic libraries need to fulfil, new services that will come online in the near future, data literacy and its relation to other literacies, research support and the need to connect researchers across the academy, and other key issues, such as 'data deluge,' the importance of citations, metadata and data repositories. This book presents a solid resource that contextualizes RDM, including good theory and practice for researchers and professionals who find themselves tasked with managing research data. - Gives guidance on organizing, storing, preserving and sharing research data using Research Data Management (RDM) - Contextualizes RDM within the global shift to data-intensive research - Helps researchers and information professionals understand and optimize data-intensive ways of working - Considers RDM in relation to varying needs of researchers across the sciences and humanities - Presents key issues surrounding RDM, including data literacy, citations, metadata and data repositories