Ruixin Yang – författare

Federal Data Science serves as a guide for federal software engineers, government analysts, economists, researchers, data scientists, and engineering managers in deploying data analytics methods to governmental processes. Driven by open government (2009) and big data (2012) initiatives, federal agencies have a serious need to implement intelligent data management methods, share their data, and deploy advanced analytics to their processes. Using federal data for reactive decision making is not sufficient anymore, intelligent data systems allow for proactive activities that lead to benefits such as: improved citizen services, higher accountability, reduced delivery inefficiencies, lower costs, enhanced national insights, and better policy making.

No other government-dedicated work has been found in literature that addresses this broad topic. This book provides multiple use-cases, describes federal data science benefits, and fills the gap in this critical and timely area. Written and reviewed by academics, industry experts, and federal analysts, the problems and challenges of developing data systems for government agencies is presented by actual developers, designers, and users of those systems, providing a unique and valuable real-world perspective.

Offers a range of data science models, engineering tools, and federal use-cases Provides foundational observations into government data resources and requirements Introduces experiences and examples of data openness from the US and other countries A step-by-step guide for the conversion of government towards data-driven policy making Focuses on presenting data models that work within the constraints of the US government Presents the why, the what, and the how of injecting AI into federal culture and software systems

Data Democracy: At the Nexus of Artificial Intelligence, Software Development, and Knowledge Engineering provides a manifesto to data democracy. After reading the chapters of this book, you are informed and suitably warned! You are already part of the data republic, and you (and all of us) need to ensure that our data fall in the right hands. Everything you click, buy, swipe, try, sell, drive, or fly is a data point. But who owns the data? At this point, not you! You do not even have access to most of it. The next best empire of our planet is one who owns and controls the world's best dataset. If you consume or create data, if you are a citizen of the data republic (willingly or grudgingly), and if you are interested in making a decision or finding the truth through data-driven analysis, this book is for you. A group of experts, academics, data science researchers, and industry practitioners gathered to write this manifesto about data democracy.

The future of the data republic, life within a data democracy, and our digital freedoms An in-depth analysis of open science, open data, open source software, and their future challenges A comprehensive review of data democracy's implications within domains such as: healthcare, space exploration, earth sciences, business, and psychology The democratization of Artificial Intelligence (AI), and data issues such as: Bias, imbalance, context, and knowledge extraction A systematic review of AI methods applied to software engineering problems

Many of the challenges of the next century will have physical dimensions, such as tsunamis, hurricanes, and climate change as well as human dimensions such as economic crises, epidemics, and emergency responses. With pioneering editors and expert contributors, Advanced Geoinformation Science explores how certain technical aspects of geoinformation have been used and could be used to address such global issues. The editors and chapter authors have been involved in global initiatives such as Global Earth Observation System of Systems (GEOSS) and Digital Earth, and research problems such as air quality, public health, and cloud computing. The book delineates the problems communities are likely to face and how advanced geoinformation science can be a part of their solution. It introduces different methods in collecting spatial data as the initial feeds to geoinformation science and computing platforms. It discusses systems for data management, data integration and analysis, the geoinformation infrastructure, as well as knowledge capture, formatting, and utilization. The book then explores a variety of geoinformation applications, highlighting environmental, agriculture, and urban planning uses. Geoinformation science encompasses more than just traditional technologies such as Remote Sensing, GIS, GPS, and supporting disciplines. And although the science continues to become more multidisciplinary, the literature remains compartmentalized according to the traditional disciplinary boundaries. Capturing recent developments in geoinformation science and linking IT with a wide range of Earth sciences, the authors explain how advanced technology and concepts play a significant role in recent advancements. Enhanced with forty-four color illustrations, live examples such as GOS and AirNow, and insights from NASA, EPA, and USGS, the book provides a vision for the future and explores how to bring that vision into reality.