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7 Data Science
Pages 145-164

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From page 145...
... The value of data comes when they are analyzed to provide information that is used to make decisions based on insights and understandings derived from data. Advances in data storage, communications, and processing have led to new research methods and tools that were simply not possible just one decade ago (NIH, 2018)
From page 146...
... Scientific breakthroughs in food and agricultural disciplines in the next 10-15 years will increasingly address the predictive and prescriptive levels of understanding. Our understanding of the fundamental scientific underpinnings of the biological, chemical, physical, and socioeconomic elements of the food and agricultural system can benefit from better data access, data integration, and data analytics.
From page 147...
... and each may have positive or negative impacts on genotypes. GEMS data are in a wide variety of formats, in
From page 148...
... . Example: Improvements in Sensor Technology and Data Velocity Enabling Real-Time Continuous Monitoring in Agriculture.
From page 149...
... Continuous measurements such as these will improve the calibration and performance of water- and nutrient-use models, and may lead to a new understanding of how plants use water and nutrients. Integrating these farm-scale sensor technologies with seasonal or hyper-local weather forecasts, or with measures of water availability in connected ecosystems via the IoT, creates opportunities to manage farm ecosystems integrated with natural ecosystems (e.g., ecohydrology)
From page 150...
... Increased data velocity will enable dynamic control of agricultural equipment in motion in real time -- such as precision planters, sprayers, and irrigation -- and enable real-time continuous monitoring of individual livestock in a herd using wearable (and other) sensors for precision livestock applications, using advanced technologies such as microfluidics, sound analyzers, image-detection techniques, sweat and salivary sensing, serodiagnosis (diagnosis based on blood sera)
From page 151...
... The FAIR data principles are a set of guiding principles that could facilitate data standardization and interoperability for scientific data management and stewardships. The principles are organized around four concepts: findable, accessible, interoperable, and reuseable (Wilkinson et al., 2016)
From page 152...
... CyVerse is a dynamic virtual organization led by the University of Arizona alongside the Texas Advanced Computing Center, Cold Spring Harbor Laboratory, and the University of North Carolina at Wilmington. • USDA VegScapec is a National Agricultural Statistical Service (NASS)
From page 153...
... . Anonymizing geospatial data without distorting its granularity is a known problem which does not yet have an adequate solution.
From page 154...
... . Robots can be designed to harvest crops at a higher volume and faster pace than human laborers, to monitor crop and soil health using computer vision and deep-learning algorithms that analyze data captured by drones, and to more accurately predict crop
From page 155...
... . Box 7-4 on robotic milking provides an example of integrating AI with sensor technologies in animal agriculture.
From page 156...
... Issues in scalability, such as performance and latency, need to be addressed in order to realize pervasive use of blockchain technology in the food system. 3.3  Opportunity 3: IoT IoT is the network of physical devices embedded with electronics, software, sensors, actuators, and connectivity which enables these "things" to connect and exchange data creating opportunities for more direct integration of the physical world into computer-based systems, resulting in efficiency improvements, economic benefits, and reduced human exertions (Wasik, 2013; Morgan, 2014)
From page 157...
... . The emergence of quantum computing could be used to explore natural phenomena in the physical world -- phenomena that traditional computing paradigms are ill suited to represent at scale.
From page 158...
... 4.  BARRIERS TO SUCCESS Data science is a rapidly evolving field and data science skills for working with Big Data are in high demand in all sectors, including food and agricultural research and agricultural economics (Woodward, 2016)
From page 159...
... The American Farm Bureau Federation developed the Privacy and Security Principles for Farm Data (AFBF, 2014) , which lays out 13 data principles, but these are only guidelines.
From page 160...
... 2018. Alibaba Cloud and CAS Launch One of the World's Most Powerful Public Public Quantum Computing Services.
From page 161...
... 2018. Intel Starts Testing Smallest "Sping Qubit" Chip for Quantum Computing.
From page 162...
... 2016. IBM PAIRS Curated Big Data Service for Accelerated Geospatial Data Analytics and Discover, 2016 IEEE International Conference on Big Data.
From page 163...
... Computing Community Consortium white paper. Available at https://arxiv.org/ftp/arxiv/papers/1705/1705.01993.pdf (accessed March 15, 2018)
From page 164...
... pone.0163477 (accessed March 15, 2018)


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