Dorris Scott – författare
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3 produkter
3 produkter
856 kr
Skickas inom 10-15 vardagar
Librarians understand the need to store, use and analyze data related to their collection, patrons and institution, and there has been consistent interest over the last 10 years to improve data management, analysis, and visualization skills within the profession. However, librarians find it difficult to move from out-of-the-box proprietary software applications to the skills necessary to perform the range of data science actions in code. This book will focus on teaching R through relevant examples and skills that librarians need in their day-to-day lives that includes visualizations but goes much further to include web scraping, working with maps, creating interactive reports, machine learning, and others. While there’s a place for theory, ethics, and statistical methods, librarians need a tool to help them acquire enough facility with R to utilize data science skills in their daily work, no matter what type of library they work at (academic, public or special). By walking through each skill and its application to library work before walking the reader through each line of code, this book will support librarians who want to apply data science in their daily work. Hands-On Data Science for Librarians is intended for librarians (and other information professionals) in any library type (public, academic or special) as well as graduate students in library and information science (LIS).Key Features: Only data science book available geared toward librarians that includes step-by-step code examples Examples include all library types (public, academic, special) Relevant datasets Accessible to non-technical professionals Focused on job skills and their applications
2 197 kr
Skickas inom 10-15 vardagar
Librarians understand the need to store, use and analyze data related to their collection, patrons and institution, and there has been consistent interest over the last 10 years to improve data management, analysis, and visualization skills within the profession. However, librarians find it difficult to move from out-of-the-box proprietary software applications to the skills necessary to perform the range of data science actions in code. This book will focus on teaching R through relevant examples and skills that librarians need in their day-to-day lives that includes visualizations but goes much further to include web scraping, working with maps, creating interactive reports, machine learning, and others. While there’s a place for theory, ethics, and statistical methods, librarians need a tool to help them acquire enough facility with R to utilize data science skills in their daily work, no matter what type of library they work at (academic, public or special). By walking through each skill and its application to library work before walking the reader through each line of code, this book will support librarians who want to apply data science in their daily work. Hands-On Data Science for Librarians is intended for librarians (and other information professionals) in any library type (public, academic or special) as well as graduate students in library and information science (LIS).Key Features: Only data science book available geared toward librarians that includes step-by-step code examples Examples include all library types (public, academic, special) Relevant datasets Accessible to non-technical professionals Focused on job skills and their applications
Art, Science, and Magic of the Data Curation Network
A Retrospective on Cross-Institutional Collaboration
Häftad, Engelska, 2023
332 kr
Skickas inom 3-6 vardagar
The Data Curation Network (DCN) is a membership organization of institutional and non-profit data repositories whose vision is to advance open research by making data more ethical, reusable, and understandable. Although initially conceived of and established through grant funding, the DCN transitioned to a sustainable, member-funded organization in July 2021, and is now composed of almost 50 data curators from 17 institutions.The Art, Science, and Magic of the Data Curation Network: A Retrospective on Cross Institutional Collaboration captures the results of a project retrospective meeting and describes the necessary components of the DCN’s sustained collaboration in the hopes that the insights will be of use to other collaborative efforts. In particular, the authors describe the successes of the community and challenges of launching a cross-institutional network. Additionally, this publication details the administrative, tool-based, and trust-based structures necessary for establishing this community, the “radical collaboration” that is the cornerstone of the DCN, and potential future collaborations to address shared challenges in libraries and research data management. This in-depth case study provides an overview of the critical work of launching a collaborative network and transitioning to sustainability. This publication will be of special interest to research librarians, data curators, and anyone interested in academic community building.