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FAIR is an international set of principles for improving the findability, accessibility, interoperability, and reusability of research data and other digital products. The PIs for this CDI project planned and hosted a workshop of USGS data stakeholders, data professionals, and managers of USGS data systems from across the Bureau’s Mission Areas. Workshop participants shared case studies that fostered collaborative discussions, resulting in recommended actions and goals to make USGS research data more FAIR. Project PIs are using the workshop results to produce a roadmap for adopting FAIR principles in USGS. The FAIR Roadmap will be foundational to FY2021 CDI activities to ensure the persistence and usability of...
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Deep learning is a computer analysis technique inspired by the human brain’s ability to learn. It involves several layers of artificial neural networks to learn and subsequently recognize patterns in data, forming the basis of many state-of-the-art applications from self-driving cars to drug discovery and cancer detection. Deep neural networks are capable of learning many levels of abstraction, and thus outperform many other types of automated classification algorithms. This project developed software tools, resources, and two training workshops that will allow USGS scientists to apply deep learning to remotely sensed imagery and to better understand natural hazards and habitats across the Nation. The tools and...
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Insect pests cost billions of dollars per year globally, negatively impacting food crops and infrastructure and contributing to the spread of disease. Timely information regarding developmental stages of pests can facilitate early detection and control, increasing efficiency and effectiveness. To address this need, the USA National Phenology Network (USA-NPN) created a suite of “Pheno Forecast” map products relevant to science and management. Pheno Forecasts indicate, for a specified day, the status of the insect’s target life cycle stage in real time across the contiguous United States. These risk maps enhance decision-making and short-term planning by both natural resource managers and members of the public. ...
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USGS data are one of the most valuable assets of the organization, and it is critical that we ensure our scientists and staff produce and manage data in such a way that at the completion of a project, the data continues to be accessible in useable formats, documented so it can be understood, and preserved properly for future uses. Principal Investigator : Vivian B Hutchison Cooperator/Partner : Lisa Zolly, Michelle Y Chang, Heather S Henkel, Thomas E Burley, Chatfield Thomas A, Carly Strasser The goals of this project included: produce three online training modules that relay the importance of data management, best practices for planning, and guidance for preparing science data to share; target audiences of...
The purpose of this project was to establish and support a USGS Mobile Environment website to provide support of portable hardware devices, application development and application delivery. The development of a framework to fully support this endeavor will require input and involvement by Core Science Systems, Enterprise Information, Science Quality and Integrity, Office of Communication, Publishing and the mobile community. Principal Investigator : Lorna A Schmid, David L Govoni, Sky Bristol, Tim Kern Benefits One-stop shop to provide detailed support information across USGS Mission Areas Actual functioning mobile applications, built collectively Deliverables Trained Mobile Community Workshop held July 17...
What USGS programs use citizen science? How can projects be best designed while meeting policy requirements? What are the most effective volunteer recruitment methods? What data should be collected to ensure validation and how should data be stored? What standard protocols are most easily used by volunteers? Can data from multiple projects be integrated to support new research or existing science questions? To help answer these and other questions, the USGS CDI supported the development of the Citizen Science Working Group (CSWG) in August 2011 and funded the Working Group’s proposal to hold a USGS Citizen Science Workshop in fiscal year 2012. The USGS Citizen Science Workshop goals were: To raise awareness of...
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USGS will soon transition to the international metadata standards known collectively as ISO 19115. The open-ended nature of ISO benefits with much greater flexibility and vocabulary to describe research products. However, that flexibility means few constraints that can guide authors and ensure standardized, robust documentation across the bureau. This project proposed that the USGS data community develop content specifications to define standard USGS ISO metadata content requirements. These specifications would be modular in order to meet documentation needs of the diverse range of research data that USGS produces. Using the specifications, metadata authors will be guided to include appropriate metadata fields for...
An additional product not originally on the funded activities list was organized for the newly-formed Science Data Coordinator Network. The Network invited 2 representatives from each of the USGS geographic areas, and several mission areas, to participate in a Data Management Workshop. The Workshop was organized by Viv Hutchison and taught by Tom Chatfield of the Bureau of Land Management. The course was very well received and requests to repeat the workshop have been numerous. This response emphasizes the need for data management training in the USGS, thus the creation of USGS specific training materials. Data management education in USGS is critical to building a culture that understands its importance and incorporates...