Harnessing the Data Revolution

Harnessing Data for 21st Century Science and Engineering (aka Harnessing the Data Revolution, HDR) is one of NSF\u27s six Big Research Ideas, aimed at supporting fundamental research in data science and engineering; developing a cohesive, federated approach to the research data infrastructure needed to power this revolution; and developing of a 21st-century data-capable workforce. HDR will enable new modes of data-driven discovery allowing researchers to ask and answer new questions in frontier science and engineering, generate new knowledge and understanding by working with domain experts, and accelerate discovery and innovation. This initiative builds on NSF\u27s history of data science investments. The HDR Big Idea is particularly well-suited for collaborations and partnerships with industry. After providing an overview of HDR, we will explore areas for potential collaboration and partnership with industry. As the only federal agency supporting all fields of science and engineering, NSF is uniquely positioned to help ensure that our country\u27s future is one enriched and improved by data

Data Science R&D: Current Activities, Future Directions

https://www.youtube.com/watch?v=MNcx2Iwt_v

CYberinfrastructure for COmparative effectiveness REsearch (CYCORE): improving data from cancer clinical trials

Improved approaches and methodologies are needed to conduct comparative effectiveness research (CER) in oncology. While cancer therapies continue to emerge at a rapid pace, the review, synthesis, and dissemination of evidence-based interventions across clinical trials lag in comparison. Rigorous and systematic testing of competing therapies has been clouded by age-old problems: poor patient adherence, inability to objectively measure the environmental influences on health, lack of knowledge about patients’ lifestyle behaviors that may affect cancer’s progression and recurrence, and limited ability to compile and interpret the wide range of variables that must be considered in the cancer treatment. This lack of data integration limits the potential for patients and clinicians to engage in fully informed decision-making regarding cancer prevention, treatment, and survivorship care, and the translation of research results into mainstream medical care. Particularly important, as noted in a 2009 report on CER to the President and Congress, the limited focus on health behavior-change interventions was a major hindrance in this research landscape (DHHS 2009). This paper describes an initiative to improve CER for cancer by addressing several of these limitations. The Cyberinfrastructure for Comparative Effectiveness Research (CYCORE) project, informed by the National Science Foundation’s 2007 report “Cyberinfrastructure Vision for 21st Century Discovery” has, as its central aim, the creation of a prototype for a user-friendly, open-source cyberinfrastructure (CI) that supports acquisition, storage, visualization, analysis, and sharing of data important for cancer-related CER. Although still under development, the process of gathering requirements for CYCORE has revealed new ways in which CI design can significantly improve the collection and analysis of a wide variety of data types, and has resulted in new and important partnerships among cancer researchers engaged in advancing health-related CI

Harnessing the data revolution: a perspective from the National Science Foundation

Presented at the National data integrity conference: data sharing: the how, why, when and when not to share held on June 2-3, 2016 at University of Colorado, Denver, Colorado. The National Data Integrity Conference is a gathering of people sharing new challenges and solutions regarding research data and integrity. This conference aims to provide attendees with both an understanding of data integrity issues and impart practical tools and skills to deal with them. Topics addressed will include data privacy, openness, policy, education and the impacts of sharing data, how to do it, when to do it, and when not to. Speakers and audience members come from diverse fields such as: Academic Research; Information Technology; Quality Assurance; Regulatory Compliance; Private Industry; Grant Funding; Government.Dr. Baru is involved with the Big Data program and interdisciplinary and inter-agency Data Science-related activities. He co-chairs the NITRD inter-agency Big Data Senior Steering Group and coordinates and expands upon SDSC's myriad data-centric initiatives, all aimed at leveraging advancements in high-performance computing and data analysis to accelerate research and discovery.PowerPoint presentation given on June 2, 2016.This talk will introduce NSF's vision for moving beyond isolated standalone approaches for data science, services, and infrastructure, towards a cohesive, federated, national-scale approach that will harness the data revolution and transform US science, engineering, and education over the next decade and beyond

The geon portal: Accelerating knowledge discovery in the geosciences

Geoscience studies produce data from various observations, experiments, and simulations at an enormous rate. With proliferation of applications and data formats, the geoscience research community faces many challenges in effectively managing and sharing resources and in efficiently integrating and analyzing the data. In this paper, we discuss how this challenge is being addressed by the GEON Portal, a Web based distributed resource management system that provides integrated access to data and tools needed for knowledge discovery in the geosciences. Unlike previous data management efforts that were either data-driven or applicationdriven, the GEON Portal provides facilities for efficient sharing, discovery and integration of both data and services that use geoscience data. We identify the challenges involved in managing geonscientific resources and provide solutions that exploit the syntactic, semantic, temporal and spatial metadata associated with the resources. One of our goals is is to provide some insight into the challenges involved in providing a comprehensive scientific data management solution based on our experiences with geoscientific data. Categories and Subject Descriptors H.3.3 [Information Search and Retrieval]: Query formulation, Search process; H.3.5 [Online Information Systems]: Web-base

A Science Collaboration Environment for the Network for Earthquake Engineering Simulation

The vision of cyberinfrastructure is to provide “the comprehensive infrastructure needed to capitalize on dramatic advances in information technology, ” in support of science and engineering applications. The development of collaboration environments based on “science portals ” plays an important role in achieving this cyberinfrastructure vision. While online, discipline-specific problem solving environments have been in use for many years, the attempt to create a common cyberinfrastructure for this purpose is a more recent development. In this paper, we address the current effort for building such a science collaboration portal as a joint effort between the GEON (GEOsciences Network) and NEES (Network for Earthquake Engineering Simulation) projects. In particular, we present recent work in developing portlets for providing access to computational simulation tools