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The enormous increase in digital scholarly data and computing power combined with recent advances in text mining, linguistics, network science, and scientometrics make it possible to scientifically study the structure and evolution of science on a large scale. This paper discusses the challenges of this 'BIG science of science' – also called 'computational(More)
This article presents the results of a 7-year-long quest into the development of a "dream tool" for our research in information science and scientometrics and more recently, network science. The results are two cyberinfrastructures (CI): The Cyberinfrastructure for Information Visualization and the Network Workbench that enjoy a growing national and(More)
With advances in computing techniques, a large amount of high-resolution high-quality multimedia data (video and audio, etc.) has been collected in research laboratories in various scientific disciplines, particularly in social and behavioral studies. How to automatically and effectively discover new knowledge from rich multimedia data poses a compelling(More)
Today, research communities comprise scholars and practitioners from multiple disciplines. An example is network science that aims at the study of small, medium, and large-scale network datasets collected in social and behavioral science, physics, biology, and other disciplines. At an increasing rate, the scientists that invent and implement new algorithms(More)
Introduction Today, terabytes of scholarly data are available from different data providers. 1,2,3 The datasets differ by type, cost, size, quality, coverage, contents, and ease of access. All data providers support search: some support local citation and coauthor network traversal. None supports the large-scale analysis, modeling and visualization of(More)
This chapter presents the results of a seven-year long quest into the development of a " dream tool " for our research in scientometrics (Börner et al. 2003) and more recently, network science (Börner et al. in press). The results are two cyberinfrastructures: The Cyberinfrastructure for Information Visualization and the Network Workbench that enjoy a(More)
Goal: Develop a large-scale network analysis, modeling and visualization toolkit for physics, biomedical, and social science research. Outline What is " Network Science " and its challenges Major contributions of Network Workbench (NWB) Present the underlying technologies – NWB tool architecture Hand on NWB tool Review some large scale network analysis and(More)
Upland and lowland rices (Oryza sativa) are the two most important rice ecotypes adapted to agricultural ecosystems of contrasting soil water conditions. Consequently, they have distinguished genetic features associated with drought resistance. As they are essential germplasm resources for breeding water-saving and drought-resistant rice, effective methods(More)
The stress-induced epimutations could be inherited over generations and play important roles in plant adaption to stressful environments. Upland rice has been domesticated in water-limited environments for thousands of years and accumulated drought-induced epimutations of DNA methylation, making it epigenetically differentiated from lowland rice. To study(More)