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"Baru, Chaitanya"
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Geoinformatics : cyberinfrastructure for the solid Earth sciences
Advanced information technology infrastructure is increasingly being employed in the Earth sciences to provide researchers with efficient access to massive central databases and to integrate diversely formatted information from a variety of sources. These geoinformatics initiatives enable manipulation, modeling and visualization of data in a consistent way, and are helping to develop integrated Earth models at various scales, and from the near surface to the deep interior. This book uses a series of case studies to demonstrate computer and database use across the geosciences. Chapters are thematically grouped into sections that cover data collection and management; modeling and community computational codes; visualization and data representation; knowledge management and data integration; and web services and scientific workflows. Geoinformatics is a fascinating and accessible introduction to this emerging field for readers across the solid Earth sciences and an invaluable reference for researchers interested in initiating new cyberinfrastructure projects of their own.
Book
Editorial Introduction
This special issue presents 10 articles that feature the NSF Convergence Accelerator, a program launched in 2019 by the US National Science Foundation, focusing on transitioning research to practice for social impact. Included in this special issue are related articles — ranging from an introduction to the NSF Convergence Accelerator program to descriptions of projects in phase 1 and phase 2 of the Convergence Accelerator.
Journal Article
Knowledge graphs: Introduction, history, and perspectives
Knowledge graphs (KGs) have emerged as a compelling ion for organizing the world's structured knowledge and for integrating information extracted from multiple data sources. They are also beginning to play a central role in representing information extracted by AI systems, and for improving the predictions of AI systems by giving them knowledge expressed in KGs as input. The goals of this article are to (a) introduce KGs and discuss important areas of application that have gained recent prominence; (b) situate KGs in the context of the prior work in AI; and (c) present a few contrasting perspectives that help in better understanding KGs in relation to related technologies.
Journal Article
The NSF Convergence Accelerator program
The National Science Foundation's Convergence Accelerator is a unique program offering researchers and innovators the opportunity to translate research results into tangible solutions that make a difference for society. Through an intense innovation curriculum and a mentorship program, researchers gain skills and experiences that are of use not only during this program but throughout their careers. This article describes the NSF Convergence Accelerator program and its initial funded convergence research topics—or “tracks”—funded in 2019 and 2020. In almost every track and NSF‐funded project, artificial intelligence and machine learning (AI/ML) approaches and methods are playing an essential role.
Journal Article
Knowledge Graphs: Introduction, History and, Perspectives
Knowledge graphs (KGs) have emerged as a compelling abstraction for organizing the world's structured knowledge and for integrating information extracted from multiple data sources. They are also beginning to play a central role in representing information extracted by AI systems, and for improving the predictions of AI systems by giving them knowledge expressed in KGs as input. The goals of this article are to (a) introduce KGs and discuss important areas of application that have gained recent prominence; (b) situate KGs in the context of the prior work in AI; and (c) present a few contrasting perspectives that help in better understanding KGs in relation to related technologies.
Journal Article