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‘Fit-for-purpose?’ – challenges and opportunities for applications of blockchain technology in the future of healthcare
Blockchain is a shared distributed digital ledger technology that can better facilitate data management, provenance and security, and has the potential to transform healthcare. Importantly, blockchain represents a data architecture, whose application goes far beyond Bitcoin – the cryptocurrency that relies on blockchain and has popularized the technology. In the health sector, blockchain is being aggressively explored by various stakeholders to optimize business processes, lower costs, improve patient outcomes, enhance compliance, and enable better use of healthcare-related data. However, critical in assessing whether blockchain can fulfill the hype of a technology characterized as ‘revolutionary’ and ‘disruptive’, is the need to ensure that blockchain design elements consider actual healthcare needs from the diverse perspectives of consumers, patients, providers, and regulators. In addition, answering the real needs of healthcare stakeholders, blockchain approaches must also be responsive to the unique challenges faced in healthcare compared to other sectors of the economy. In this sense, ensuring that a health blockchain is ‘fit-for-purpose’ is pivotal. This concept forms the basis for this article, where we share views from a multidisciplinary group of practitioners at the forefront of blockchain conceptualization, development, and deployment.
Journal Article
Driving Data Projects
Digital transformation and data projects are not new and yet, for many, they are a challenge. Driving Data Projects is a compelling guide that empowers data teams and professionals to navigate the complexities of data projects, fostering a more data-informed culture within their organizations. With practical insights and step-by-step methodologies, this guide provides a clear path how to drive data projects effectively in any organization, regardless of its sector or maturity level whilst also demonstrating how to overcome the overwhelming feelings of where to start and how to not lose momentum. This book offers the keys to identifying opportunities for driving data projects and how to overcome challenges to drive successful data initiatives. Driving Data Projects is highly practical and provides reflections, worksheets, checklists, activities, and tools making it accessible to students new to driving data projects and culture change. This book is also a must-have guide for data teams and professionals committed to unleashing the transformative power of data in their organizations.
eBook
Distributed computing pearls
\"Computers and computer networks are one of the most incredible inventions of the 20th century, having an ever-expanding role in our daily lives by enabling complex human activities in areas such as entertainment, education, and commerce. One of the most challenging problems in computer science for the 21st century is to improve the design of distributed systems where computing devices have to work together as a team to achieve common goals. In this book, the author has tried to gently introduce the general reader to some of the most fundamental issues and classical results of computer science underlying the design of algorithms for distributed systems, so that the reader can get a feel of the nature of this exciting and fascinating field called distributed computing. The book will appeal to the educated layperson, while computer-knowledgeable readers will be able to learn something new.\"--Page 4 of cover.
Book
Fog and Edge Computing
</P> <b>A comprehensive guide to Fog and Edge applications, architectures, and technologies</b> <p>Recent years have seen the explosive growth of the Internet of Things (IoT): the internet- connected network of devices that includes everything from personal electronics and home appliances to automobiles and industrial machinery. Responding to the ever-increasing bandwidth demands and privacy concerns of the IoT, Fog and Edge computing concepts have developed to collect, analyze, and process data closer to devices and more efficiently than traditional cloud architecture. <p><i>Fog and Edge Computing: Principles and Paradigms</i>provides a comprehensive overview of the state-of-the-art applications and architectures driving this dynamic field of computing while highlighting potential research directions and emerging technologies. <p>Exploring topics such as developing scalable architectures, moving from closed systems to open systems, and ethical issues rising from data sensing, this timely book addresses both the challenges and opportunities that Fog and Edge computing presents. Contributions from leading IoT experts discuss federating Edge resources, middleware design issues, data management and predictive analysis, smart transportation and surveillance applications, and more. A coordinated and integrated presentation of topics helps readers gain thorough knowledge of the foundations, applications, and issues that are central to Fog and Edge computing. This valuable resource: <ul> <li>Discusses IoT and new computing paradigms in the domain such as Fog, Edge and Mist</li> <li>Provides insights on transitioning from current Cloud-centric and 4G/5G wireless environments to Fog computing</li> <li>Examines methods to optimize virtualized, pooled, and shared resources</li> <li>Identifies potential technical challenges and offers suggestions for possible solutions</li> <li>Discusses major components of Fog and Edge computing architectures such as middleware, interaction protocols, and autonomic management</li> <li>Includes access to a website portal for advanced online resources</li> </ul> <p><i>Fog and Edge Computing: Principles and Paradigms</i>is an essential source of up-to-date information for systems architects, developers, researchers, and advanced undergraduate and graduate students in fields of computer science and engineering.
eBook
Cloud Computing
Designed for researchers, engineers, IT professionals, and graduate students in parallel and cloud computing, this volume covers the state of the art in cloud computing theory and practice. It spans the background, concepts, services, and middleware of cloud computing. A range of scientific researchers and professors in cloud computing, grid computing, high-performance computing, and Internet computing discuss enabling techniques, system implementation, service functionalities, and various applications. Numerous case studies are included throughout the text.
eBook
Computing : from the abacus to the iPad
This volume chronicles the history of computing devices, from simple tabulators such as the abacus and the earliest analog calculators to the tablet computer.
Book
Python Data Cleaning and Preparation Best Practices
Take your data preparation skills to the next level by converting any type of data asset into a structured, formatted, and readily usable dataset
Key Features
Maximize the value of your data through effective data cleaning methodsEnhance your data skills using strategies for handling structured and unstructured dataElevate the quality of your data products by testing and validating your data pipelinesPurchase of the print or Kindle book includes a free PDF eBook
Book Description
Professionals face several challenges in effectively leveraging data in today's data-driven world. One of the main challenges is the low quality of data products, often caused by inaccurate, incomplete, or inconsistent data. Another significant challenge is the lack of skills among data professionals to analyze unstructured data, leading to valuable insights being missed that are difficult or impossible to obtain from structured data alone. To help you tackle these challenges, this book will take you on a journey through the upstream data pipeline, which includes the ingestion of data from various sources, the validation and profiling of data for high-quality end tables, and writing data to different sinks. You’ll focus on structured data by performing essential tasks, such as cleaning and encoding datasets and handling missing values and outliers, before learning how to manipulate unstructured data with simple techniques. You’ll also be introduced to a variety of natural language processing techniques, from tokenization to vector models, as well as techniques to structure images, videos, and audio. By the end of this book, you’ll be proficient in data cleaning and preparation techniques for both structured and unstructured data.
What you will learn
Ingest data from different sources and write it to the required sinksProfile and validate data pipelines for better quality controlGet up to speed with grouping, merging, and joining structured dataHandle missing values and outliers in structured datasetsImplement techniques to manipulate and transform time series dataApply structure to text, image, voice, and other unstructured data
Who this book is for
Whether you're a data analyst, data engineer, data scientist, or a data professional responsible for data preparation and cleaning, this book is for you. Working knowledge of Python programming is needed to get the most out of this book.
eBook