Products related to Data:
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Data Management in Large-Scale Education Research
Research data management is becoming more complicated.Researchers are collecting more data, using more complex technologies, all the while increasing the visibility of our work with the push for data sharing and open science practices.Ad hoc data management practices may have worked for us in the past, but now others need to understand our processes as well, requiring researchers to be more thoughtful in planning their data management routines. This book is for anyone involved in a research study involving original data collection.While the book focuses on quantitative data, typically collected from human participants, many of the practices covered can apply to other types of data as well.The book contains foundational context, instructions, and practical examples to help researchers in the field of education begin to understand how to create data management workflows for large-scale, typically federally funded, research studies.The book starts by describing the research life cycle and how data management fits within this larger picture.The remaining chapters are then organized by each phase of the life cycle, with examples of best practices provided for each phase.Finally, considerations on whether the reader should implement, and how to integrate those practices into a workflow, are discussed. Key Features:Provides a holistic approach to the research life cycle, showing how project management and data management processes work in parallel and collaborativelyCan be read in its entirety, or referenced as needed throughout the life cycleIncludes relatable examples specific to education researchIncludes a discussion on how to organize and document data in preparation for data sharing requirementsContains links to example documents as well as templates to help readers implement practices
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Data Excess in Digital Media Research
Data excess — particularly in digital media research — is inevitable.It emerges as the ‘debris’ and ‘leftovers’ from planning, fieldwork and writing; the words cut from drafts and copied to untouched and forgotten files; digital metadata automatically recorded to databases; the data archived but never analysed or published.What do or can we do with this excess from our research?Thinking beyond academic constraints and the constant push towards the next new fundable thing, Data Excess in Digital Media Research explicitly engages with data that has been left behind, ignored, obscured or even ‘written out’ of research publications.Positioning ‘excess’ as a conceptual, methodological, ethical and pragmatic challenge and opportunity, the authors in this edited collection examine what can happen when media researchers return to their surplus archives and develop new knowledge from what would otherwise be under-explored excess. Provoking an ethical reconsideration of what we do, or do not do, with excess data, this is a call to action for researchers and scholars to rethink how they conduct their research as the consequences of datafication grow ever more central to both our academic endeavours and our lives.
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Research Data Management and Data Literacies
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.
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Discovering Computers: Digital Technology, Data, and Devices
DISCOVERING COMPUTERS: DIGITAL TECHNOLOGY, DATA, AND DEVICES, 17th edition, teaches you not only the basics of technology, but also how you will use it -- and the responsibilities that go along with being a digital citizen.Focusing on current technology, the content addresses convergence of devices and platforms.Each module integrates practical how-to tips, ethics issues and security topics, while Consider This boxes woven throughout help you sharpen your critical-thinking skills.A variety of end-of-module activities -- checkpoint questions, small group activities and problem-solving exercises -- enable you to put what you learn into practice.MindTap digital learning solution is also available.Using an inviting approach that ensures understanding, DISCOVERING COMPUTERS equips you with the information you need for success at home, school and work.
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How to calculate the amount of data in digital video data?
To calculate the amount of data in digital video data, you need to consider the resolution, frame rate, and bit depth of the video. First, calculate the total number of pixels in each frame by multiplying the width by the height of the video resolution. Then, multiply this by the number of frames per second to get the total number of pixels per second. Finally, multiply this by the bit depth (usually 8 bits per color channel) to get the total amount of data per second in bits.
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What does a timing diagram for preamble and payload data look like in digital technology?
In digital technology, a timing diagram for preamble and payload data typically shows the timing relationship between the preamble and the payload data. The preamble is a sequence of known bits that helps the receiver synchronize with the transmitter and establish a communication link. In the timing diagram, the preamble will be shown as a series of pulses or bits occurring at specific time intervals, followed by the payload data which contains the actual information being transmitted. The timing diagram will illustrate how the preamble and payload data are synchronized and transmitted within the digital communication system.
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How do you calculate the amount of data in digital video data?
The amount of data in digital video data can be calculated by multiplying the video resolution (width x height in pixels), the bit depth (number of bits used to represent each color channel), the frame rate (number of frames per second), and the duration of the video in seconds. This will give you the total amount of data in bits. To convert this to a more commonly used unit, such as megabytes or gigabytes, you can divide the total amount of data in bits by 8 to get the amount in bytes, and then divide by 1024 multiple times to convert to larger units.
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Is digital data protection important to you?
Yes, digital data protection is very important to me. As a consumer, I want to ensure that my personal information is secure and not vulnerable to cyber attacks or data breaches. As a professional, I understand the importance of protecting sensitive business data and maintaining the trust of clients and customers. In today's digital age, data protection is essential for both personal and professional security.
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Big Data for the Public Good : Regulating Access to Public Sector Big Data for Research and Innovation
Can researchers and innovators use UK public sector data to produce knowledge that improves policy making, scrutinises government work and promotes the public interest?This book looks at interactions between UK public sector officials and researchers/innovators to shed light on barriers to data access and use.It asks: what are the frameworks that govern access to public sector big datasets for researchers and innovators?How are these frameworks applied in practice? What are the governance solutions for policy makers interested in harnessing the untapped potential of public sector big data to improve their policies and create public benefit?Public sector data is a valuable resource that can help researchers and innovators create knowledge and solutions that benefit society.As public bodies collect increasingly more data about us, UK policy makers try to maximise the use of public sector big data for the benefit of the public.But accessing this data is not easy. There are many legal, technical, and ethical barriers that prevent the use of public sector data for research and innovation.This book is for researchers and innovators who want to understand and overcome the barriers to accessing UK public sector data.It is also for policy makers who are interested in how public sector data can be used to improve decision-making, scrutinise government work, and promote the public interest.
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Advancing Data Science Education in K-12 : Foundations, Research, and Innovations
Advancing Data Science Education in K-12 offers a highly accessible, research-based treatment of the foundations of data science education and its increasingly vital role in K-12 instructional content. As federal education initiatives and developers of technology-enriched curricula attempt to incorporate the study of data science—the generation, capture, and computational analysis of data at large scale—into schooling, a new slate of skills, literacies, and approaches is needed to ensure an informed, effective, and unproblematic deployment for young learners.Friendly to novices and experts alike, this book provides an authoritative synthesis of the most important research and theory behind data science education, its implementation into K-12 curricula, and clarity into the distinctions between data literacy and data science.Learning with and about data hold equal and interdependent importance across these chapters, conveying the variety of issues, situations, and decision-making integral to a well-rounded, critically minded perspective on data science education. Students and faculty in teaching, leadership, curriculum development, and educational technology programs will come away with essential insights into the breadth of our current and future engagements with data; the real-world opportunities and challenges data holds when taught in conjunction with other subject matter in formal schooling; and the nature of data as a human and societal construct that demands new competencies of today’s learners.
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Harnessing Digital Technology and Data for Nursing Practice
As new technologies and data become essential for the delivery of optimal care, nurses will play an increasingly vital role in developing and implementing digital health strategies.This timely book is designed to help you develop proficiency and confidence to lead this digital transformation. Harnessing Digital Technology and Data for Nursing Practice provides comprehensive coverage of the historical, theoretical and practical dimensions of the digital transformation in nursing.It considers a wide range of topics, from person-centred practice and user-centred design to nursing workforce development, evolving nursing practices, and the role of data in improving patient care and research.Expert insights are supported by learning activities and real-life case studies, with application of theory to practice throughout. Aimed at nurses in all settings and working at all professional levels, this book will leave the reader with an appreciation of how an array of digital technologies and data can positively impact nurses' wellbeing, support and improve your daily practice, and ultimately ensure patient-centred, safe and effective care. Written specifically for nurses and midwives - explains how you can play a central role in shaping the digital future of health careProvides historical, theoretical and practical perspectives - offers a sound base from which to understand the role of data technology in your workCovers a wide spectrum of topics, including: digital transformation of health carenursing informaticsuser-centred designdata-driven practiceperson-centred carehealth inequalitiestelehealth and remote monitoringethical and legal considerationspopulation healthresearchProvides practical insights and case studies to help you apply digital technologies in practiceAcknowledges the challenges in adopting digital health, and stresses the importance of digital literacy and nurse involvement in the design and implementation of digital solutionsGlobally relevant and future oriented - creates a vision for nurses as co-navigators of care who make decisions informed by real-time patient analyticsAncillary videos to support learning
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The Elements of Big Data Value : Foundations of the Research and Innovation Ecosystem
This open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society.It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data.The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems.The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation.
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How does data transmission from analog to digital work?
Data transmission from analog to digital works by first converting the analog signal into a digital format. This is done through a process called sampling, where the analog signal is measured at regular intervals and each measurement is assigned a digital value. The digital data is then encoded and modulated for transmission over a digital communication channel, such as a network or the internet. At the receiving end, the digital signal is demodulated and decoded back into its original analog form for use. This process allows for more efficient and reliable transmission of data over long distances.
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Does market research hinder innovation in business administration?
Market research does not necessarily hinder innovation in business administration. In fact, it can provide valuable insights into consumer needs and preferences, helping businesses to develop innovative products and services that meet market demands. By understanding market trends and customer behavior, businesses can identify opportunities for innovation and stay ahead of competitors. However, relying too heavily on market research without allowing room for creativity and risk-taking can limit the potential for groundbreaking innovations. It is important for businesses to strike a balance between leveraging market research and fostering a culture of innovation to drive success in business administration.
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By which methods do opinion research institutes collect their data?
Opinion research institutes collect their data through various methods, including surveys, interviews, focus groups, and observational studies. Surveys are commonly conducted through phone, online, or in-person questionnaires to gather information from a large sample of individuals. Interviews involve one-on-one discussions with participants to delve deeper into their opinions and perspectives. Focus groups bring together a small group of individuals to discuss and provide feedback on specific topics. Observational studies involve researchers directly observing and recording behaviors or opinions in real-life settings.
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What is Digital Technology 2?
Digital Technology 2 is a course that builds upon the foundational concepts introduced in Digital Technology 1. It delves deeper into topics such as programming, web development, data analysis, and cybersecurity. Students will further develop their skills in using digital tools and technologies to solve real-world problems and gain a more advanced understanding of how technology impacts society. The course aims to prepare students for a career in the rapidly evolving field of digital technology.
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