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Clark K: Practical Project Management
for Librarians

Practical Project Management for Librarians

How to Design, Deploy, and Sustain an Effective Data Governance Program

Data Governance

This book offers practical guidance to information management professionals seeking to implement web archiving programmes of their own. It is essential reading for those who need to collect and preserve specific elements of the web - from national domains or individual subject areas to an organization's own website.

Archiving Websites

Building A Culture of Teamwork and Trust

Empowering Library Staff and Customers

Information use is changing rapidly in the digital age, leading to complex intellectual property and ownership issues. Exploring the ethical implications of this new environment, specifically as they relate to information professionals, this book offers guidance on making ethical choices.

Ethics, Information, and Technology

Artificial Intelligence for Libraries

Five Factors That Improve Employee Engagement and Satisfaction

Creating Healthy Library Workplaces

Asia Pacific Modern

Libraries and the Colonial Public in Vietnam

Bibliotactics

Proceedings of the British Academy

Materiality looms large in the world of archives in storage, conservation, and shape or materials of the records. How does this materiality change in the digital age? The way digital techniques and materialities transform our engagement with archives is highlighted and explored throughout Archival Materialities in a Digital Age.

Archival Materialities in a Digital Age

Mathematical Modelling for Big Data Analytics is a comprehensive guidebook that explores the use of mathematical models and algorithms for analyzing large and complex datasets. The book covers a range of topics, including statistical modeling, machine learning, optimization techniques, and data visualization, and provides practical examples and case studies to demonstrate their applications in real-world scenarios. Users will find a clear and accessible resource to enhance their skills in mathematical modeling and data analysis for big data analytics. Real-world examples and case studies demonstrate how to approach and solve complex data analysis problems using mathematical modeling techniques. This book will help readers understand how to translate mathematical models and algorithms into practical solutions for real-world problems. Coverage of the theoretical foundations of big data analytics, including qualitative and quantitative analytics techniques, digital twins, machine learning, deep learning, optimization, and visualization techniques make this a must have resource.

Practical Project Management for Librarians

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