Translating Diverse Environmental Data into Reliable Information

Translating Diverse Environmental Data into Reliable Information
Author :
Publisher : Academic Press
Total Pages : 502
Release :
ISBN-10 : 9780128124475
ISBN-13 : 0128124474
Rating : 4/5 (474 Downloads)

Book Synopsis Translating Diverse Environmental Data into Reliable Information by : Daniel A. Vallero

Download or read book Translating Diverse Environmental Data into Reliable Information written by Daniel A. Vallero and published by Academic Press. This book was released on 2017-09-15 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: Translating Diverse Environmental Data into Reliable Information: How to Coordinate Evidence from Different Sources is a resource for building environmental knowledge, particularly in the era of Big Data. Environmental scientists, engineers, educators and students will find it essential to determine data needs, assess their quality, and efficiently manage their findings. Decision makers can explore new open access databases and tools, especially portals and dashboards. The book demonstrates how environmental knowledgebases are and can be built to meet the needs of modern students and professionals. Topics covered include concepts and principles that underpin air, water, and other public health and ecological topics. Integrated and systems perspectives are woven throughout, with clues on how to build and apply interdisciplinary data, which can increasingly be obtained from sources ranging from peer-reviewed research appearing in scientific journals to information gathered by citizen scientists. This opens the door to using vast amounts of open data and the necessary quality assurance and metadata considerations for their countless applications. - Provides tools to manage data of varying sizes and quality - Identifies both opportunities and cautions in using "other people's data - Updates physical, chemical and biological factors that must be considered in risk evaluations and life cycle assessments - Applies to data collected by academic, governmental, businesses, and citizen scientists across environmental systems - Improves readers' ability to organize and visualize their work in the age of Big Data


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