Librarian's Guide to Online Searching
Librarian's Guide to Online Searching

Author: Christopher C. Brown

Publisher: Bloomsbury Publishing USA

Published: 2021-06-18

Total Pages: 337

ISBN-13:

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Updates the premier textbook for students and librarians needing to know the landscape of current databases and how to search them. Librarians need to know of existing databases, and they must be able to teach search capabilities and strategies to library users. This practical guide introduces librarians to a broad spectrum of fee-based and freely available databases and explains how to teach them. The updated 6th edition of this well-regarded text covers new databases on the market as well as updates to older databases. It also explains underlying information structures and demonstrates how to search most effectively. It introduces readers to several recent changes, such as the move away from metadata-based indexing to full text indexing by vendors covering newspaper content. Business databases receive greater emphasis. As in the previous editions, this book takes a real-world approach, covering topics from basic and advanced search tools to online subject databases. Each chapter includes a thorough discussion, a recap, concrete examples, exercises, and points to consider, making it an ideal text for courses in database searching as well as a trustworthy professional resource.

Exploring the U.S. Census
Exploring the U.S. Census

Author: Frank Donnelly

Publisher: SAGE Publications

Published: 2019-10-07

Total Pages: 364

ISBN-13: 1544355432

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Exploring the U.S. Census gives social science students and researchers alike the tools to understand, extract, process, and analyze data from the decennial census, the American Community Survey, and other data collected by the U.S. Census Bureau. Donnelly′s text provides a thorough background on the data collection methods, structures, and potential pitfalls of the census for unfamiliar researchers, collecting information previously available only in widely disparate sources into one handy guide. Hands-on, applied exercises at the end of the chapters help readers dive into the data. Along the way, the author shows how best to analyze census data with open-source software and tools. Readers can freely evaluate the data on their own computers, in keeping with the free and open data provided by the Census Bureau. By placing the census in the context of the open data movement, this text makes the history and practice of the census relevant so readers can understand what a crucial resource the census is for research and knowledge.

Data Governance
Data Governance

Author: John Ladley

Publisher: Academic Press

Published: 2019-11-08

Total Pages: 352

ISBN-13: 0128158328

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Managing data continues to grow as a necessity for modern organizations. There are seemingly infinite opportunities for organic growth, reduction of costs, and creation of new products and services. It has become apparent that none of these opportunities can happen smoothly without data governance. The cost of exponential data growth and privacy / security concerns are becoming burdensome. Organizations will encounter unexpected consequences in new sources of risk. The solution to these challenges is also data governance; ensuring balance between risk and opportunity. Data Governance, Second Edition, is for any executive, manager or data professional who needs to understand or implement a data governance program. It is required to ensure consistent, accurate and reliable data across their organization. This book offers an overview of why data governance is needed, how to design, initiate, and execute a program and how to keep the program sustainable. This valuable resource provides comprehensive guidance to beginning professionals, managers or analysts looking to improve their processes, and advanced students in Data Management and related courses. With the provided framework and case studies all professionals in the data governance field will gain key insights into launching successful and money-saving data governance program. - Incorporates industry changes, lessons learned and new approaches - Explores various ways in which data analysts and managers can ensure consistent, accurate and reliable data across their organizations - Includes new case studies which detail real-world situations - Explores all of the capabilities an organization must adopt to become data driven - Provides guidance on various approaches to data governance, to determine whether an organization should be low profile, central controlled, agile, or traditional - Provides guidance on using technology and separating vendor hype from sincere delivery of necessary capabilities - Offers readers insights into how their organizations can improve the value of their data, through data quality, data strategy and data literacy - Provides up to 75% brand-new content compared to the first edition

Artificial Intelligence in Healthcare
Artificial Intelligence in Healthcare

Author: Adam Bohr

Publisher: Academic Press

Published: 2020-06-21

Total Pages: 385

ISBN-13: 0128184396

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Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data

The Electronic Resources Troubleshooting Guide
The Electronic Resources Troubleshooting Guide

Author: Holly Talbott

Publisher: American Library Association

Published: 2020-11-06

Total Pages: 184

ISBN-13: 0838947913

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A library user can’t access an article. Your log in credentials won’t work. In the realm of electronic resources everything runs smoothly—until suddenly, without warning, it doesn’t. Invariably, systems will break down, but a trial and error approach to finding out what’s wrong is highly inefficient. This hands-on guide from two expert ERM librarians walks you through the essentials of troubleshooting. It outlines a methodical process that will help you identify the source of a problem even when it’s not obvious and take steps to reach a resolution. With the goal of developing a library-wide workflow in mind, this guide will teach you how to familiarize yourself with the components of electronic resources, using flowchart diagrams of common access chains such as discovery services, knowledge bases, research guides, and library services platforms; navigate the complete triage and troubleshooting workflow, illustrated through 14 in-depth examples; recognize the symptoms of common access disruptions; conduct efficient troubleshooting interviews; manage help tickets and design problem reports that capture key information without overburdening the user; create publicly available help pages for problems originating with users’ devices or computers; communicate with vendors and IT personnel for speedy resolutions, providing dozens of clear definitions of library and technology terms that will help you minimize confusion; and customize your own troubleshooting workflow chart for common use across departments and staff hierarchies.

Knowledge Discovery in Big Data from Astronomy and Earth Observation
Knowledge Discovery in Big Data from Astronomy and Earth Observation

Author: Petr Skoda

Publisher: Elsevier

Published: 2020-04-09

Total Pages: 472

ISBN-13: 0128191546

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Knowledge Discovery in Big Data from Astronomy and Earth Observation: Astrogeoinformatics bridges the gap between astronomy and geoscience in the context of applications, techniques and key principles of big data. Machine learning and parallel computing are increasingly becoming cross-disciplinary as the phenomena of Big Data is becoming common place. This book provides insight into the common workflows and data science tools used for big data in astronomy and geoscience. After establishing similarity in data gathering, pre-processing and handling, the data science aspects are illustrated in the context of both fields. Software, hardware and algorithms of big data are addressed. Finally, the book offers insight into the emerging science which combines data and expertise from both fields in studying the effect of cosmos on the earth and its inhabitants.

Basic Laboratory Methods for Biotechnology
Basic Laboratory Methods for Biotechnology

Author: Lisa A. Seidman

Publisher: CRC Press

Published: 2021-12-29

Total Pages: 1210

ISBN-13: 1000480763

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Basic Laboratory Methods for Biotechnology, Third Edition is a versatile textbook that provides students with a solid foundation to pursue employment in the biotech industry and can later serve as a practical reference to ensure success at each stage in their career. The authors focus on basic principles and methods while skillfully including recent innovations and industry trends throughout. Fundamental laboratory skills are emphasized, and boxed content provides step by step laboratory method instructions for ease of reference at any point in the students’ progress. Worked through examples and practice problems and solutions assist student comprehension. Coverage includes safety practices and instructions on using common laboratory instruments. Key Features: Provides a valuable reference for laboratory professionals at all stages of their careers. Focuses on basic principles and methods to provide students with the knowledge needed to begin a career in the Biotechnology industry. Describes fundamental laboratory skills. Includes laboratory scenario-based questions that require students to write or discuss their answers to ensure they have mastered the chapter content. Updates reflect recent innovations and regulatory requirements to ensure students stay up to date. Tables, a detailed glossary, practice problems and solutions, case studies and anecdotes provide students with the tools needed to master the content.

Knowledge Management in the Development of Data-Intensive Systems
Knowledge Management in the Development of Data-Intensive Systems

Author: Ivan Mistrik

Publisher: CRC Press

Published: 2021-06-15

Total Pages: 342

ISBN-13: 1000387410

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Data-intensive systems are software applications that process and generate Big Data. Data-intensive systems support the use of large amounts of data strategically and efficiently to provide intelligence. For example, examining industrial sensor data or business process data can enhance production, guide proactive improvements of development processes, or optimize supply chain systems. Designing data-intensive software systems is difficult because distribution of knowledge across stakeholders creates a symmetry of ignorance, because a shared vision of the future requires the development of new knowledge that extends and synthesizes existing knowledge. Knowledge Management in the Development of Data-Intensive Systems addresses new challenges arising from knowledge management in the development of data-intensive software systems. These challenges concern requirements, architectural design, detailed design, implementation and maintenance. The book covers the current state and future directions of knowledge management in development of data-intensive software systems. The book features both academic and industrial contributions which discuss the role software engineering can play for addressing challenges that confront developing, maintaining and evolving systems;data-intensive software systems of cloud and mobile services; and the scalability requirements they imply. The book features software engineering approaches that can efficiently deal with data-intensive systems as well as applications and use cases benefiting from data-intensive systems. Providing a comprehensive reference on the notion of data-intensive systems from a technical and non-technical perspective, the book focuses uniquely on software engineering and knowledge management in the design and maintenance of data-intensive systems. The book covers constructing, deploying, and maintaining high quality software products and software engineering in and for dynamic and flexible environments. This book provides a holistic guide for those who need to understand the impact of variability on all aspects of the software life cycle. It leverages practical experience and evidence to look ahead at the challenges faced by organizations in a fast-moving world with increasingly fast-changing customer requirements and expectations.

Open Access Databases and Datasets for Drug Discovery
Open Access Databases and Datasets for Drug Discovery

Author: Antoine Daina

Publisher: John Wiley & Sons

Published: 2023-12-26

Total Pages: 357

ISBN-13: 3527348395

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Open Access Databases and Datasets for Drug Discovery Timely resource discussing the future of data-driven drug discovery and the growing number of open-source databases With an overview of 90 freely accessible databases and datasets on all aspects of drug design, development, and discovery, Open Access Databases and Datasets for Drug Discovery is a comprehensive guide to the vast amount of “free data” available to today’s pharmaceutical researchers. The applicability of open-source data for drug discovery and development is analyzed, and their usefulness in comparison with commercially available tools is evaluated. The most relevant databases for small molecules, drugs and druglike substances, ligand design, protein 3D structures (both experimental and calculated), and human drug targets are described in depth, including practical examples of how to access and work with the data. The first part is focused on databases for small molecules, followed by databases for macromolecular targets and diseases. The final part shows how to integrate various open-source tools into the academic and industrial drug discovery and development process. Contributed to and edited by experts with long-time experience in the field, Open Access Databases and Datasets for Drug Discovery includes information on: An extensive listing of open access databases and datasets for computer-aided drug design PubChem as a chemical database for drug discovery, DrugBank Online, and bioisosteric replacement for drug discovery supported by the SwissBioisostere database The Protein Data Bank (PDB) and macromolecular structure data supporting computer-aided drug design, and the SWISS-MODEL repository of 3D protein structures and models PDB-REDO in computational aided drug design (CADD), and using Pharos/TCRD for discovering druggable targets Unmatched in scope and thoroughly reviewing small and large open data sources relevant for rational drug design, Open Access Databases and Datasets for Drug Discovery is an essential reference for medicinal and pharmaceutical chemists, and any scientists involved in the drug discovery and drug development.