Federal data science : transforming government and agricultural policy using artificial intelligence
著者
書誌事項
Federal data science : transforming government and agricultural policy using artificial intelligence
Academic Press, an imprint of Elsevier, c2018
大学図書館所蔵 全2件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references and index
内容説明・目次
内容説明
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.
目次
Section 1: Injecting Artificial Intelligence into Governmental Systems 1. A Day in the Life of a Federal Analyst and a Federal Contractor 2. Disseminating Government Data Effectively in the Age of Open Data 3. Machine Learning for the Government: Challenges and Statistical Difficulties 4. Making the Case for Artificial Intelligence at the Government: Guidelines to Transforming Federal Software
Section 2: Governmental Data Science Solutions Around the World 5. Agricultural Data Analytics for Environmental Monitoring in Canada 6. France’s Governmental Big Data Analytics: From Predictive to Prescriptive Using R 7. Agricultural Remote Sensing and Data Science in China 8. Data Visualization of Complex Information Through Mind Mapping in Spain and the European Union
Section 3: Federal Data Science Use Cases at the US Government 9. A Deployment Life Cycle Model for Agricultural Data Systems Using Kansei Engineering and Association Rules 10. Federal Big Data Analytics in the Health Domain: An Ontological Approach to Data Interoperability 11. Geospatial Data Discovery, Management, and Analysis at National Aeronautics and Space Administration 12. Intelligent Automation Tools and Software Engines for Managing Federal Agricultural Data 13. Transforming Governmental Data Science Teams in the Future
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