The Discipline Of Data
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Dama Dmbok
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Author : Dama International
language : en
Publisher:
Release Date : 2017
Dama Dmbok written by Dama International and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Database management categories.
Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment.
Process Mining
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Author : Wil M. P. van der Aalst
language : en
Publisher: Springer
Release Date : 2016-04-15
Process Mining written by Wil M. P. van der Aalst and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-15 with Computers categories.
This is the second edition of Wil van der Aalst’s seminal book on process mining, which now discusses the field also in the broader context of data science and big data approaches. It includes several additions and updates, e.g. on inductive mining techniques, the notion of alignments, a considerably expanded section on software tools and a completely new chapter of process mining in the large. It is self-contained, while at the same time covering the entire process-mining spectrum from process discovery to predictive analytics. After a general introduction to data science and process mining in Part I, Part II provides the basics of business process modeling and data mining necessary to understand the remainder of the book. Next, Part III focuses on process discovery as the most important process mining task, while Part IV moves beyond discovering the control flow of processes, highlighting conformance checking, and organizational and time perspectives. Part V offers a guide to successfully applying process mining in practice, including an introduction to the widely used open-source tool ProM and several commercial products. Lastly, Part VI takes a step back, reflecting on the material presented and the key open challenges. Overall, this book provides a comprehensive overview of the state of the art in process mining. It is intended for business process analysts, business consultants, process managers, graduate students, and BPM researchers.
Guide To Teaching Data Science
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Author : Orit Hazzan
language : en
Publisher: Springer Nature
Release Date : 2023-03-20
Guide To Teaching Data Science written by Orit Hazzan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-20 with Computers categories.
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 book provides a variety of pedagogical discussions and specific teaching methods and frameworks, as well as includes exercises, and guidelines related to many data science concepts (e.g., data thinking and the data science workflow), main machine learning algorithms and concepts (e.g., KNN, SVM, Neural Networks, performance metrics, confusion matrix, and biases) and data science professional topics (e.g., ethics, skills and research approach). Professor Orit Hazzan is a faculty member at the Technion’s Department of Education in Science and Technology since October 2000. Her research focuses on computer science, software engineering and data science education. Within this framework, she studies the cognitive and social processes on the individual, the team and the organization levels, in all kinds of organizations. Dr. Koby Mike is a Ph.D. graduate from the Technion's Department of Education in Science and Technology under the supervision of Professor Orit Hazzan. He continued his post-doc research on data science education at the Bar-Ilan University, and obtained a B.Sc. and an M.Sc. in Electrical Engineering from Tel Aviv University.
Foundations Of Data Science
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Author : Avrim Blum
language : en
Publisher: Cambridge University Press
Release Date : 2020-01-23
Foundations Of Data Science written by Avrim Blum and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-23 with Computers categories.
Covers mathematical and algorithmic foundations of data science: machine learning, high-dimensional geometry, and analysis of large networks.
Data Management For Researchers
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Author : Kristin Briney
language : en
Publisher: Pelagic Publishing Ltd
Release Date : 2015-09-01
Data Management For Researchers written by Kristin Briney and has been published by Pelagic Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-01 with Computers categories.
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
Nasa S Planetary Data System
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Author :
language : en
Publisher:
Release Date : 1992
Nasa S Planetary Data System written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Planets categories.
Doing Data Science
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Author : Cathy O'Neil
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2013-10-09
Doing Data Science written by Cathy O'Neil and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-09 with Computers categories.
A guide to the usefulness of data science covers such topics as algorithms, logistic regression, financial modeling, data visualization, and data engineering.
How To Quantcrit
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Author : Wendy Castillo
language : en
Publisher: Taylor & Francis
Release Date : 2024-10-21
How To Quantcrit written by Wendy Castillo and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-21 with Education categories.
How to QuantCrit equips researchers and users of quantitative data with practices to alter how they collect and analyze quantitative data. Using Quantitative Critical Race Theory (QuantCrit) as a framework, this book develops the foundation for an iterative praxis to explore a range of questions that prompt practitioners and stakeholders to be engaged critics in working towards a more just and equitable society. The book begins with an overview of QuantCrit and its five tenets: (1) the centrality of racism; (2) numbers are not neutral; (3) categories are neither ‘natural’ nor given; (4) the importance voice and insight (data cannot speak for themselves); and (5) a social justice/equity orientation. Each subsequent chapter begins with a more detailed explanation and exploration of the tenet. Then, the chapters move into actionable steps that researchers and data users can take to implement QuantCrit into applied practice. Finally, the book closes with thoughts on working to use quantitative data for racial justice. This book is intended for researchers, data users, and graduate students in education and education-related disciplines. It offers insights and suggested actions that range from working with existing data sets in more racially just ways to more radically reimagining the entire educational research process. As such, the book offers ideas and information that can be useful for anyone working with quantitative educational data. The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license. The Open Access version of this book was funder by the Spencer Foundation and WT Grant Foundation.
Nasa Data And Information Systems
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Author :
language : en
Publisher:
Release Date : 1988
Nasa Data And Information Systems written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Earth sciences categories.
Academic Libraries And Collaborative Research Services
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Author : Carrie Forbes
language : en
Publisher: Bloomsbury Publishing PLC
Release Date : 2022-08-16
Academic Libraries And Collaborative Research Services written by Carrie Forbes and has been published by Bloomsbury Publishing PLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-16 with Language Arts & Disciplines categories.
Higher education institutions in the United States and across the globe, are realizing the importance of enabling internal and external collaborative work, e.g., interdisciplinary research and community partnerships. In recent years, researchers have documented the benefits of organizational collaboration for research including greater efficiency, effectiveness, and enhanced research reputation. In addition, accreditors, foundations, business, and government agencies have been espousing the value of collaboration for knowledge creation and research and improved organizational functioning. As a result of both the external pressures and the known benefits, many forms of internal and external research collaborations have begun to emerge in higher education. At the heart of this change, academic libraries, who have long been models for collaborative work, are increasingly participating in the research process by providing a widening range of research services beyond traditional reference services. Innovative library services, in areas such as bibliometric analysis, research data management, and data repositories, are evolving in response to changes in education funding and policies. These funding and policy changes have also coincided with technological developments to create opportunities for academic librarians to find new roles within their institutions and the research community. There is a growing body of literature examining these changing academic library roles, but few volumes have concentrated on how the nature of collaborative work in libraries is helping to reshape institutional research practices. Academic Libraries and Collaborative Research Services fills that void by providing academic librarians and administrators with case studies and guidance on how academic libraries are establishing their place in this new collaborative research arena in the areas of emerging liaison roles, research data services, open access and scholarly publishing, and professional development programming. The book will also be useful to higher education administrators and institutional research officers looking for information on how to partner with libraries to increase the effectiveness of collaborative research.