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Linked Data for Libraries, Archives and Museums
This highly practical handbook teaches you how to unlock the value of your existing metadata through cleaning, reconciliation, enrichment and linking and how to streamline the process of new metadata creation. Libraries, archives and museums are facing up to the challenge of providing access to fast growing collections whilst managing cuts to budgets. Key to this is the creation, linking and publishing of good quality metadata as Linked Data that will allow their collections to be discovered, accessed and disseminated in a sustainable manner. This highly practical handbook teaches you how to unlock the value of your existing metadata through cleaning, reconciliation, enrichment and linking a...
Research Data Access and Management in Modern Libraries
Handling and archiving data should be done in a highly professional and quality-controlled manner. For academic and research libraries, it is required to know how to document data and support traceability, as well as to make it reusable and productive. However, these institutions have different requirements relating to the archiving and reusability of data. Therefore, a comprehensive source of information is required to understand data access and management within these organizations. Research Data Access and Management in Modern Libraries is a critical scholarly resource that delves into innovative data management strategies and strategy implementation in library settings and provides best ...
Climatological Data
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Nuclear Reaction Data And Nuclear Reactors - Physics, Design And Safety: Proceedings Of The Workshop
This volume provides the up-to-date information behind nuclear reactor calculations, focusing on a key role of nuclear reaction data, down to the physics of nuclear interactions. It is divided into three parts. Part 1 deals with nuclear reaction models, including neutron resonances, fission, the optical model, statistical and preequilibrium models as well as nuclear level densities. Part 2 is devoted to nuclear data filling and processing; it includes lectures on nuclear data evaluation and formatting, data libraries and services, with emphasis on nuclear-data-processing codes. Part 3 presents applications in nuclear reactor calculations, emphasizing physics, design and safety.
AI-Assisted Library Reconstruction
In an era marked by rapid technological progress, libraries find themselves at a crossroads grappling with the challenges posed by an information-rich yet digitally fragmented landscape. The conventional role of libraries, once the steadfast guardians of knowledge, faces disruption as we navigate through a sea of information abundance. This conundrum gives rise to a critical issue - how can libraries adapt and thrive in an environment dominated by the rapid evolution of artificial intelligence (AI)? AI-Assisted Library Reconstruction is a compelling solution that promises to breathe new life into these institutions, making them more dynamic, accessible, and efficient in the face of unprecede...
Data Science and Machine Learning with Python
Data Science and Machine Learning are two interconnected fields that play a pivotal role in modern technological advancements. Data science involves extracting insights and knowledge from vast amounts of data using various tools and techniques. This includes data collection, cleaning, analysis, and interpretation to uncover valuable patterns and trends. On the other hand, machine learning is a subset of artificial intelligence (AI) that focuses on developing algorithms and models capable of learning from data to make predictions and decisions. Machine learning algorithms can automatically improve their performance over time by learning from new data, making them crucial for tasks such as image recognition, natural language processing, and predictive analytics. Together, data science and machine learning empower businesses and researchers to leverage data-driven insights for informed decision-making and innovation across diverse domains. This book is intended for the first course in Data Science and Machine Learning and covers the required topics in sufficient depth to meet the requirements of the readers.
