It takes the average reader 5 hours and 46 minutes to read Big Data Science and Analytics for Smart Sustainable Urbanism by Simon Elias Bibri
Assuming a reading speed of 250 words per minute. Learn more
We are living at the dawn of what has been termed ‘the fourth paradigm of science,’ a scientific revolution that is marked by both the emergence of big data science and analytics, and by the increasing adoption of the underlying technologies in scientific and scholarly research practices. Everything about science development or knowledge production is fundamentally changing thanks to the ever-increasing deluge of data. This is the primary fuel of the new age, which powerful computational processes or analytics algorithms are using to generate valuable knowledge for enhanced decision-making, and deep insights pertaining to a wide variety of practical uses and applications. This book addresses the complex interplay of the scientific, technological, and social dimensions of the city, and what it entails in terms of the systemic implications for smart sustainable urbanism. In concrete terms, it explores the interdisciplinary and transdisciplinary field of smart sustainable urbanism and the unprecedented paradigmatic shifts and practical advances it is undergoing in light of big data science and analytics. This new era of science and technology embodies an unprecedentedly transformative and constitutive power—manifested not only in the form of revolutionizing science and transforming knowledge, but also in advancing social practices, producing new discourses, catalyzing major shifts, and fostering societal transitions. Of particular relevance, it is instigating a massive change in the way both smart cities and sustainable cities are studied and understood, and in how they are planned, designed, operated, managed, and governed in the face of urbanization. This relates to what has been dubbed data-driven smart sustainable urbanism, an emerging approach based on a computational understanding of city systems and processes that reduces urban life to logical and algorithmic rules and procedures, while also harnessing urban big data to provide a more holistic and integrated view or synoptic intelligence of the city. This is increasingly being directed towards improving, advancing, and maintaining the contribution of both sustainable cities and smart cities to the goals of sustainable development. This timely and multifaceted book is aimed at a broad readership. As such, it will appeal to urban scientists, data scientists, urbanists, planners, engineers, designers, policymakers, philosophers of science, and futurists, as well as all readers interested in an overview of the pivotal role of big data science and analytics in advancing every academic discipline and social practice concerned with data–intensive science and its application, particularly in relation to sustainability.
Big Data Science and Analytics for Smart Sustainable Urbanism by Simon Elias Bibri is 337 pages long, and a total of 86,609 words.
This makes it 114% the length of the average book. It also has 106% more words than the average book.
The average oral reading speed is 183 words per minute. This means it takes 7 hours and 53 minutes to read Big Data Science and Analytics for Smart Sustainable Urbanism aloud.
Big Data Science and Analytics for Smart Sustainable Urbanism is suitable for students ages 12 and up.
Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.
When deciding what to show young students always use your best judgement and consult a professional.
Big Data Science and Analytics for Smart Sustainable Urbanism by Simon Elias Bibri is sold by several retailers and bookshops. However, Read Time works with Amazon to provide an easier way to purchase books.
To buy Big Data Science and Analytics for Smart Sustainable Urbanism by Simon Elias Bibri on Amazon click the button below.
Buy Big Data Science and Analytics for Smart Sustainable Urbanism on Amazon