Leslie Hsu
Leslie Hsu is a physical scientist in the USGS Science Analytics and Synthesis (SAS) program. She coordinates the Community for Data Integration.
Leslie Hsu is coordinator of the USGS Community for Data Integration, project coordinator of the USGS Model Catalog, and part of the USGS State of the Data project.
Professional Experience
Physical Scientist, Science Data Management Branch, USGS (2015-present)
Associate Research Scientist, Geoinformatics, Lamont Doherty Earth Observatory (2013-2015)
Postdoctoral Research Scientist, Geoinformatics, Lamont Doherty Earth Observatory (2011-2013)
Postdoctoral Research Scientist, Geomorphology, University of California, Santa Cruz (2010)
Education and Certifications
University of California, Berkeley, Berkeley, CA
Ph.D in Earth & Planetary Science (2010)
Dissertation: Bedrock Erosion by Debris FlowsUniversity of Arizona, Tucson, AZ
M.S. in Geosciences (2002)
Thesis: Dating Quaternary Alluvial Fan Surfaces by Morphological Methods Based on Hillslope DiffusionHarvard University, Cambridge, MA
B.A. in Earth & Planetary Sciences (2000)
Senior thesis: Atmospheric and Oceanic Distributions of Methyl Iodide (CH3I) for Global 3-D models
Science and Products
USGS State of the Data Project: Rubric and Assessment Data
The FAIR Principles (Findable, Accessible, Interoperable, and Reusable) provide a concise and measurable strategy for optimizing the reuse of scientific data (Wilkinson et al., 2016).
In FY20, the U.S. Geological Survey initiated a research study, titled "State of the Data", to evaluate and report on the current FAIRness of USGS data. Project outputs include the USGS FAIR Rubric, which can be use
Data on the Deliverables, Sustainability, and Collaboration of Community for Data Integration Projects from 2010-2016
These four tables document the data used to draw the findings in the manuscript "Measuring sustainability of seed-funded Earth science informatics projects," by Hsu et al. Table 1, "ListProjects-data" lists the projects funded by the Community for Data Integration from 2010-2016. Table 2, "Outputs-data" lists the deliverables that were proposed and delivered to the Community for Data Integration f
Filter Total Items: 19
Community for Data Integration 2020 project report
The U.S. Geological Survey Community for Data Integration annually funds small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 12 projects funded in fiscal year 2020, outlining their goals, activities, and accomplishments.
Authors
Leslie Hsu, Emily G. Chapin, Theodore B. Barnhart, Amanda E. Cravens, Richard A. Erickson, Jason Ferrante, Aaron Fox, Nathaniel P. Hitt, Margaret Hunter, Katharine Kolb, Jared R. Peacock, Matthew D. Petkewich, Sasha C. Reed, Terry L. Sohl, Tanja N. Williamson
By
Ecosystems Mission Area, Science Analytics and Synthesis (SAS) Program, Science Synthesis, Analysis and Research Program, Community for Data Integration (CDI), Fort Collins Science Center, Southwest Biological Science Center, Upper Midwest Environmental Sciences Center, Wetland and Aquatic Research Center
State of the data: Assessing the FAIRness of USGS data
In response to recent shifts towards open science that emphasize transparency, reproducibility, and access to research data, the US Geological Survey (USGS) conducted a study to assess the degree to which USGS data assets meet the FAIR data principles (Findable, Accessible, Interoperable, and Reusable). The USGS designed and applied a methodology for quantitative analysis of FAIR characteristics.
Authors
Vivian B. Hutchison, Tamar Norkin, Lisa Zolly, Leslie Hsu
Community for data integration 2019 project report
The U.S. Geological Survey Community for Data Integration annually supports small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 14 projects supported in fiscal year 2019 and outlines their goals, activities, and accomplishments. Proposals in 2019 were encouraged to addre
Authors
Amanda N. Liford, Caitlin M. Andrews, Aparna Bamzai, Joseph A. Bard, David S. Blehert, John B. Bradford, Wesley M. Daniel, Sara L. Caldwell Eldridge, Frank Engel, Jason A. Ferrante, Amy K. Gilmer, Margaret E. Hunter, Jeanne M. Jones, Benjamin Letcher, Frances L. Lightsom, Richard R. McDonald, Leah E. Morgan, Sasha C. Reed, Leslie Hsu
By
Ecosystems Mission Area, Water Resources Mission Area, Science Synthesis, Analysis and Research Program, Science Analytics and Synthesis (SAS) Program, Volcano Hazards Program, Community for Data Integration (CDI), Geology, Geophysics, and Geochemistry Science Center, Geosciences and Environmental Change Science Center, National Wildlife Health Center, Oklahoma-Texas Water Science Center, Southwest Biological Science Center, Volcano Science Center, Western Geographic Science Center, Wetland and Aquatic Research Center , Woods Hole Coastal and Marine Science Center, Science Data Management
Community for data integration 2020 annual report
The Community for Data Integration is a community of practice whose purpose is to advance the data integration capabilities of the U.S. Geological Survey. In fiscal year 2020, the Community for Data Integration held 11 monthly forums, facilitated 13 collaboration areas, and supported 13 projects. The activities supported the broad U.S. Geological Survey priority of producing building blocks for do
Authors
Leslie Hsu, Amanda N. Liford, Grace C. Donovan
Paths to computational fluency for natural resource educators, researchers, and managers
Natural resource management and supporting research teams need computational fluency in the data and model-rich 21st century. Computational fluency describes the ability of practitioners and scientists to conduct research and represent natural systems within the computer's environment. Advancement in information synthesis for natural resource management requires more sophisticated computational ap
Authors
Richard A. Erickson, Jessica Leigh Burnett, Mark T. Wiltermuth, Edward A. Bulliner, Leslie Hsu
U.S. Geological Survey landscape science strategy 2020–2030
Across our Nation, multiple Federal, State, Tribal, and local governments are working with stakeholders and landowners to restore, conserve, and manage lands and resources to benefit fish, wildlife, and people. One of the largest Federal efforts is led by the U.S. Department of the Interior (DOI), with multiple DOI agencies working to conserve and manage public lands, resources, and cultural herit
Authors
Karen E. Jenni, Sarah K. Carter, Nicholas G. Aumen, Zachary H. Bowen, John B. Bradford, Michael A. Chotkowski, Leslie Hsu, Peter S. Murdoch, Scott W. Phillips, Kevin L. Pope, Rudy Schuster, Melanie J. Steinkamp, Jake Weltzin, George Z. Xian
Community for Data Integration 2019 annual report
The Community for Data Integration is a community of practice whose purpose is to advance the U.S. Geological Survey’s data integration capabilities. In fiscal year 2019, the Community for Data Integration held 9 monthly forums, facilitated 11 collaboration areas, held several workshops and training events, and funded 14 projects. The activities supported the U.S. Geological Survey priorities of e
Authors
Leslie Hsu, Amanda N. Liford
U.S. Geological Survey Community for Data Integration 2019 Workshop Proceedings—From big data to smart data
The U.S. Geological Survey (USGS) Community for Data Integration (CDI) Workshop was held during June 3–7, 2019, at Center Green in Boulder, Colo. The theme of the workshop was “From Big Data to Smart Data” with the purpose of bringing together the community to discuss current topics, shared challenges, and steps forward to advance twenty-first century science at the USGS. The workshop agenda was d
Authors
Leslie Hsu
USGS enterprise tools for efficient and effective management of science data
The Science Data Management Branch (SDM) of the U.S. Geological Survey (USGS) provides data management expertise and leadership and develops guidance and tools to support the USGS in providing the nation with reliable scientific information on the basis of which to describe the Earth. The SDM suite of tools supports the USGS Data Management Lifecycle by facilitating quality assurance, description,
Authors
Vivian B. Hutchison, Amanda Liford, Ricardo McClees-Funinan, Lisa Zolly, Drew Ignizio, Madison Langseth, Brandon Serna, Elizabeth Sellers, Leslie Hsu, Tamar Norkin, Marcia McNiff, Grace C. Donovan
Ecological forecasting—21st century science for 21st century management
Natural resource managers are coping with rapid changes in both environmental conditions and ecosystems. Enabled by recent advances in data collection and assimilation, short-term ecological forecasting may be a powerful tool to help resource managers anticipate impending near-term changes in ecosystem conditions or dynamics. Managers may use the information in forecasts to minimize the adverse ef
Authors
John B. Bradford, Jake Weltzin, Molly L. McCormick, Jill Baron, Zack Bowen, Sky Bristol, Daren Carlisle, Theresa Crimmins, Paul C. Cross, Joe DeVivo, Mike Dietze, Mary Freeman, Jason Goldberg, Mevin Hooten, Leslie Hsu, Karen Jenni, Jennifer L. Keisman, Jonathan Kennen, Kathy Lee, David P. Lesmes, Keith Loftin, Brian W. Miller, Peter S. Murdoch, Jana Newman, Karen L. Prentice, Imtiaz Rangwala, Jordan Read, Jennifer Sieracki, Helen Sofaer, Steve Thur, Gordon Toevs, Francisco Werner, C. LeAnn White, Timothy White, Mark T. Wiltermuth
By
Ecosystems Mission Area, Water Resources Mission Area, Science Synthesis, Analysis and Research Program, Contaminant Biology, Environmental Health Program, Science Analytics and Synthesis (SAS) Program, Eastern Ecological Science Center, Fort Collins Science Center, Kansas Water Science Center, Maryland-Delaware-D.C. Water Science Center, National Wildlife Health Center, New Jersey Water Science Center, Pacific Island Ecosystems Research Center, Southwest Biological Science Center, Upper Midwest Environmental Sciences Center, Upper Midwest Water Science Center
Community for data integration 2018 funded project report
The U.S. Geological Survey Community for Data Integration annually funds small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 10 projects funded in fiscal year 2018, outlining their goals, activities, and accomplishments.
Authors
Leslie Hsu, Caitlin M. Andrews, John B. Bradford, Daniel D. Buscombe, Katherine J. Chase, Wesley M. Daniel, Jeanne M. Jones, Pam Fuller, Benjamin B. Mirus, Matthew E. Neilson, Hans W. Vraga, Jessica J. Walker, Dennis H. Walworth, Jonathan Warrick, Jake Weltzin, Daniel J. Wieferich, Nathan J. Wood
Non-USGS Publications**
Hsu, L.; Mayorga, E.; Horsburgh, J.S.; Carter, M.R.; Lehnert, K.A.; Brantley, S.L. (2017) Enhancing Interoperability and Capabilities of Earth Science Data using the Observations Data Model 2 (ODM2), Data Science Journal. 16(1), http://doi.org/10.5334/dsj-2017-004.
Horsburgh, J.S.; Aufdenkampe, A.K.; Mayorga, E.; Lehnert, K.A.; Hsu, L.; Song, L.; Spackman Jones, A.; Damiano, S.G.; Tarboton, D.G.; Valentine, D.; Zaslavsky, I.; Whitenack, T. (2016) Observations Data Model 2: A community information model for spatially discrete Earth observations, Environmental Modelling and Software, http://doi.org/10.1016/j.envsoft.2016.01.010.
Hsu, L.; Martin, R.L.; McElroy, B.; Litwin-Miller, K.; Kim, W. (2015) Data management, sharing and reuse in experimental geomorphology: challenges, strategies, and scientific opportunities, Geomorphology, http://dx.doi.org/10.1016/j.geomorph.2015.03.039.
Hsu, L.; Lehnert, K.A.; Goodwillie, A.; Delano, J.W.; Gill, J.B.; Tivey, M.A.; Ferrini, V.L.; Carbotte, S.M.; Arko R.A. (2015) Rescue of long-tail data from the ocean bottom to the Moon: IEDA Data Rescue Mini-Awards, GeoResJ, 6:108-114, http://dx.doi.org/10.1016/j.grj.2015.02.012.
Hsu, L.; Dietrich, W.E.; Sklar, L.S. (2014) Mean and fluctuating basal forces generated by granular flows: laboratory observations in a large vertically rotating drum, Journal of Geophysical Research - Earth Surface,doi:10.1002/2013JF003078.
Kaitna, R.; Dietrich, W.E.; Hsu, L., (2014) Surface slopes, velocity profiles and fluid pressure in coarse-grained debris flows saturated with water and mud, Journal of Fluid Mechanics. doi:10.1017/jfm.2013.675.
Chen, W.-P. & Hsu L. (2013), Historic Seismicity near the Source Zone of the Great 2008 Wenchuan Earthquake: Implications for Seismic Hazards, Tectonophysics. doi:10.1016/j.tecto.2012.08.035.
Yohannes, B.; Hsu L.; Dietrich, W.E. & Hill, K. (2012), Boundary Stresses due to Impacts from Dry Granular Flows, Journal of Geophysical Research - Earth Surface, 117, F02027, doi:10.1029/2011JF002150.
Schneider, D.; Kaitna, R.; Dietrich, W.; Hsu, L.; Huggel, C. & McArdell, B. (2011), Frictional behavior of granular gravel-ice mixtures in vertically rotating drum experiments and implications for rock-ice avalanches, Cold Regions Science and Technology 69(1), 70 - 90.
Hsu, L.; Finnegan, N. J. & Brodsky, E. E. (2011), A seismic signature of river bedload transport during storm events, Geophys. Res. Lett. 38(13), L13407, http://doi.org/10.1029/2011GL047759.
Hill, K.; Yohannes, B.; Dietrich, W. & Hsu, L. (2011), Discrete Element Modeling and Large Scale Experimental Studies of Bouldery Debris Flows, in R. Genevois; D.L. Hamilton & A. Prestininzi, ed., Proceedings of the 5th International Conference on Debris Flow Hazards Mitigation, Mechanics, Prediction and Assessment, Padua, Italy, June 14-17, 2011, Italian Journal of Engineering Geology and Environment.
Kaitna, R.; Hsu, L.; Rickenmann, D. & Dietrich, W. (2011), On the development of an unsaturated front of debris flows, in R. Genevois; D.L. Hamilton & A. Prestininzi, ed., Proceedings of the 5th International Conference on Debris Flow Hazards Mitigation, Mechanics, Prediction and Assessment, Padua, Italy, June 14-17, 2011, Italian Journal of Engineering Geology and Environment.
Hsu, L.; Kaitna, R.; Dietrich, W. & Sklar, L. (2011), Boundary shear stress of granular flows, in R. Genevois; D.L. Hamilton & A. Prestininzi, ed., Proceedings of the 5th International Conference on Debris Flow Hazards Mitigation, Mechanics, Prediction and Assessment, Padua, Italy, June 14-17, 2011, Italian Journal of Engineering Geology and Environment.
Hsu, L.; Dietrich, W. E. & Sklar, L. S. (2008), Experimental study of bedrock erosion by granular flows, J. Geophys. Res. 113(F2), F02001, http://doi.org/10.1029/2007JF000778.
Hsu, L., Dietrich, W., & Sklar, L. (2007). Normal stresses, longitudinal profiles, and bedrock surface erosion by debris flows: initial findings from a large, vertically rotating drum. Debris-Flow Hazards Mitigation: Mechanics, Predictions, and Assessment, 141-150.
Hsu, L. & Bürgmann, R. (2006), Surface creep along the Longitudinal Valley fault, Taiwan from InSAR measurements, Geophys. Res. Lett. 33(6), L06312, http://doi.org/10.1029/2005GL024624.
Hsu, L. & Pelletier, J. D. (2004), Correlation and dating of Quaternary alluvial-fan surfaces using scarp diffusion, Geomorphology 60(3-4), 319 - 335, https://doi.org/10.1016/j.geomorph.2003.08.007
Bell, N.; Hsu, L.; Jacob, D. J.; Schultz, M. G.; Blake, D. R.; Butler, J. H.; King, D. B.; Lobert, J. M. & Maier-Reimer, E. (2002), Methyl iodide: Atmospheric budget and use as a tracer of marine convection in global models, J. Geophys. Res. 107(D17), 4340, http://doi.org/10.1029/2001JD001151.
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
USGS Model Catalog Tools and Metadata
Tools and metadata for the USGS Model Catalog.
USGS Model Catalog intake repository
This project contains the repository component of a modular catalog implementation.
Filter Total Items: 43
Science and Products
USGS State of the Data Project: Rubric and Assessment Data
The FAIR Principles (Findable, Accessible, Interoperable, and Reusable) provide a concise and measurable strategy for optimizing the reuse of scientific data (Wilkinson et al., 2016).
In FY20, the U.S. Geological Survey initiated a research study, titled "State of the Data", to evaluate and report on the current FAIRness of USGS data. Project outputs include the USGS FAIR Rubric, which can be use
Data on the Deliverables, Sustainability, and Collaboration of Community for Data Integration Projects from 2010-2016
These four tables document the data used to draw the findings in the manuscript "Measuring sustainability of seed-funded Earth science informatics projects," by Hsu et al. Table 1, "ListProjects-data" lists the projects funded by the Community for Data Integration from 2010-2016. Table 2, "Outputs-data" lists the deliverables that were proposed and delivered to the Community for Data Integration f
Filter Total Items: 19
Community for Data Integration 2020 project report
The U.S. Geological Survey Community for Data Integration annually funds small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 12 projects funded in fiscal year 2020, outlining their goals, activities, and accomplishments.
Authors
Leslie Hsu, Emily G. Chapin, Theodore B. Barnhart, Amanda E. Cravens, Richard A. Erickson, Jason Ferrante, Aaron Fox, Nathaniel P. Hitt, Margaret Hunter, Katharine Kolb, Jared R. Peacock, Matthew D. Petkewich, Sasha C. Reed, Terry L. Sohl, Tanja N. Williamson
By
Ecosystems Mission Area, Science Analytics and Synthesis (SAS) Program, Science Synthesis, Analysis and Research Program, Community for Data Integration (CDI), Fort Collins Science Center, Southwest Biological Science Center, Upper Midwest Environmental Sciences Center, Wetland and Aquatic Research Center
State of the data: Assessing the FAIRness of USGS data
In response to recent shifts towards open science that emphasize transparency, reproducibility, and access to research data, the US Geological Survey (USGS) conducted a study to assess the degree to which USGS data assets meet the FAIR data principles (Findable, Accessible, Interoperable, and Reusable). The USGS designed and applied a methodology for quantitative analysis of FAIR characteristics.
Authors
Vivian B. Hutchison, Tamar Norkin, Lisa Zolly, Leslie Hsu
Community for data integration 2019 project report
The U.S. Geological Survey Community for Data Integration annually supports small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 14 projects supported in fiscal year 2019 and outlines their goals, activities, and accomplishments. Proposals in 2019 were encouraged to addre
Authors
Amanda N. Liford, Caitlin M. Andrews, Aparna Bamzai, Joseph A. Bard, David S. Blehert, John B. Bradford, Wesley M. Daniel, Sara L. Caldwell Eldridge, Frank Engel, Jason A. Ferrante, Amy K. Gilmer, Margaret E. Hunter, Jeanne M. Jones, Benjamin Letcher, Frances L. Lightsom, Richard R. McDonald, Leah E. Morgan, Sasha C. Reed, Leslie Hsu
By
Ecosystems Mission Area, Water Resources Mission Area, Science Synthesis, Analysis and Research Program, Science Analytics and Synthesis (SAS) Program, Volcano Hazards Program, Community for Data Integration (CDI), Geology, Geophysics, and Geochemistry Science Center, Geosciences and Environmental Change Science Center, National Wildlife Health Center, Oklahoma-Texas Water Science Center, Southwest Biological Science Center, Volcano Science Center, Western Geographic Science Center, Wetland and Aquatic Research Center , Woods Hole Coastal and Marine Science Center, Science Data Management
Community for data integration 2020 annual report
The Community for Data Integration is a community of practice whose purpose is to advance the data integration capabilities of the U.S. Geological Survey. In fiscal year 2020, the Community for Data Integration held 11 monthly forums, facilitated 13 collaboration areas, and supported 13 projects. The activities supported the broad U.S. Geological Survey priority of producing building blocks for do
Authors
Leslie Hsu, Amanda N. Liford, Grace C. Donovan
Paths to computational fluency for natural resource educators, researchers, and managers
Natural resource management and supporting research teams need computational fluency in the data and model-rich 21st century. Computational fluency describes the ability of practitioners and scientists to conduct research and represent natural systems within the computer's environment. Advancement in information synthesis for natural resource management requires more sophisticated computational ap
Authors
Richard A. Erickson, Jessica Leigh Burnett, Mark T. Wiltermuth, Edward A. Bulliner, Leslie Hsu
U.S. Geological Survey landscape science strategy 2020–2030
Across our Nation, multiple Federal, State, Tribal, and local governments are working with stakeholders and landowners to restore, conserve, and manage lands and resources to benefit fish, wildlife, and people. One of the largest Federal efforts is led by the U.S. Department of the Interior (DOI), with multiple DOI agencies working to conserve and manage public lands, resources, and cultural herit
Authors
Karen E. Jenni, Sarah K. Carter, Nicholas G. Aumen, Zachary H. Bowen, John B. Bradford, Michael A. Chotkowski, Leslie Hsu, Peter S. Murdoch, Scott W. Phillips, Kevin L. Pope, Rudy Schuster, Melanie J. Steinkamp, Jake Weltzin, George Z. Xian
Community for Data Integration 2019 annual report
The Community for Data Integration is a community of practice whose purpose is to advance the U.S. Geological Survey’s data integration capabilities. In fiscal year 2019, the Community for Data Integration held 9 monthly forums, facilitated 11 collaboration areas, held several workshops and training events, and funded 14 projects. The activities supported the U.S. Geological Survey priorities of e
Authors
Leslie Hsu, Amanda N. Liford
U.S. Geological Survey Community for Data Integration 2019 Workshop Proceedings—From big data to smart data
The U.S. Geological Survey (USGS) Community for Data Integration (CDI) Workshop was held during June 3–7, 2019, at Center Green in Boulder, Colo. The theme of the workshop was “From Big Data to Smart Data” with the purpose of bringing together the community to discuss current topics, shared challenges, and steps forward to advance twenty-first century science at the USGS. The workshop agenda was d
Authors
Leslie Hsu
USGS enterprise tools for efficient and effective management of science data
The Science Data Management Branch (SDM) of the U.S. Geological Survey (USGS) provides data management expertise and leadership and develops guidance and tools to support the USGS in providing the nation with reliable scientific information on the basis of which to describe the Earth. The SDM suite of tools supports the USGS Data Management Lifecycle by facilitating quality assurance, description,
Authors
Vivian B. Hutchison, Amanda Liford, Ricardo McClees-Funinan, Lisa Zolly, Drew Ignizio, Madison Langseth, Brandon Serna, Elizabeth Sellers, Leslie Hsu, Tamar Norkin, Marcia McNiff, Grace C. Donovan
Ecological forecasting—21st century science for 21st century management
Natural resource managers are coping with rapid changes in both environmental conditions and ecosystems. Enabled by recent advances in data collection and assimilation, short-term ecological forecasting may be a powerful tool to help resource managers anticipate impending near-term changes in ecosystem conditions or dynamics. Managers may use the information in forecasts to minimize the adverse ef
Authors
John B. Bradford, Jake Weltzin, Molly L. McCormick, Jill Baron, Zack Bowen, Sky Bristol, Daren Carlisle, Theresa Crimmins, Paul C. Cross, Joe DeVivo, Mike Dietze, Mary Freeman, Jason Goldberg, Mevin Hooten, Leslie Hsu, Karen Jenni, Jennifer L. Keisman, Jonathan Kennen, Kathy Lee, David P. Lesmes, Keith Loftin, Brian W. Miller, Peter S. Murdoch, Jana Newman, Karen L. Prentice, Imtiaz Rangwala, Jordan Read, Jennifer Sieracki, Helen Sofaer, Steve Thur, Gordon Toevs, Francisco Werner, C. LeAnn White, Timothy White, Mark T. Wiltermuth
By
Ecosystems Mission Area, Water Resources Mission Area, Science Synthesis, Analysis and Research Program, Contaminant Biology, Environmental Health Program, Science Analytics and Synthesis (SAS) Program, Eastern Ecological Science Center, Fort Collins Science Center, Kansas Water Science Center, Maryland-Delaware-D.C. Water Science Center, National Wildlife Health Center, New Jersey Water Science Center, Pacific Island Ecosystems Research Center, Southwest Biological Science Center, Upper Midwest Environmental Sciences Center, Upper Midwest Water Science Center
Community for data integration 2018 funded project report
The U.S. Geological Survey Community for Data Integration annually funds small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 10 projects funded in fiscal year 2018, outlining their goals, activities, and accomplishments.
Authors
Leslie Hsu, Caitlin M. Andrews, John B. Bradford, Daniel D. Buscombe, Katherine J. Chase, Wesley M. Daniel, Jeanne M. Jones, Pam Fuller, Benjamin B. Mirus, Matthew E. Neilson, Hans W. Vraga, Jessica J. Walker, Dennis H. Walworth, Jonathan Warrick, Jake Weltzin, Daniel J. Wieferich, Nathan J. Wood
Non-USGS Publications**
Hsu, L.; Mayorga, E.; Horsburgh, J.S.; Carter, M.R.; Lehnert, K.A.; Brantley, S.L. (2017) Enhancing Interoperability and Capabilities of Earth Science Data using the Observations Data Model 2 (ODM2), Data Science Journal. 16(1), http://doi.org/10.5334/dsj-2017-004.
Horsburgh, J.S.; Aufdenkampe, A.K.; Mayorga, E.; Lehnert, K.A.; Hsu, L.; Song, L.; Spackman Jones, A.; Damiano, S.G.; Tarboton, D.G.; Valentine, D.; Zaslavsky, I.; Whitenack, T. (2016) Observations Data Model 2: A community information model for spatially discrete Earth observations, Environmental Modelling and Software, http://doi.org/10.1016/j.envsoft.2016.01.010.
Hsu, L.; Martin, R.L.; McElroy, B.; Litwin-Miller, K.; Kim, W. (2015) Data management, sharing and reuse in experimental geomorphology: challenges, strategies, and scientific opportunities, Geomorphology, http://dx.doi.org/10.1016/j.geomorph.2015.03.039.
Hsu, L.; Lehnert, K.A.; Goodwillie, A.; Delano, J.W.; Gill, J.B.; Tivey, M.A.; Ferrini, V.L.; Carbotte, S.M.; Arko R.A. (2015) Rescue of long-tail data from the ocean bottom to the Moon: IEDA Data Rescue Mini-Awards, GeoResJ, 6:108-114, http://dx.doi.org/10.1016/j.grj.2015.02.012.
Hsu, L.; Dietrich, W.E.; Sklar, L.S. (2014) Mean and fluctuating basal forces generated by granular flows: laboratory observations in a large vertically rotating drum, Journal of Geophysical Research - Earth Surface,doi:10.1002/2013JF003078.
Kaitna, R.; Dietrich, W.E.; Hsu, L., (2014) Surface slopes, velocity profiles and fluid pressure in coarse-grained debris flows saturated with water and mud, Journal of Fluid Mechanics. doi:10.1017/jfm.2013.675.
Chen, W.-P. & Hsu L. (2013), Historic Seismicity near the Source Zone of the Great 2008 Wenchuan Earthquake: Implications for Seismic Hazards, Tectonophysics. doi:10.1016/j.tecto.2012.08.035.
Yohannes, B.; Hsu L.; Dietrich, W.E. & Hill, K. (2012), Boundary Stresses due to Impacts from Dry Granular Flows, Journal of Geophysical Research - Earth Surface, 117, F02027, doi:10.1029/2011JF002150.
Schneider, D.; Kaitna, R.; Dietrich, W.; Hsu, L.; Huggel, C. & McArdell, B. (2011), Frictional behavior of granular gravel-ice mixtures in vertically rotating drum experiments and implications for rock-ice avalanches, Cold Regions Science and Technology 69(1), 70 - 90.
Hsu, L.; Finnegan, N. J. & Brodsky, E. E. (2011), A seismic signature of river bedload transport during storm events, Geophys. Res. Lett. 38(13), L13407, http://doi.org/10.1029/2011GL047759.
Hill, K.; Yohannes, B.; Dietrich, W. & Hsu, L. (2011), Discrete Element Modeling and Large Scale Experimental Studies of Bouldery Debris Flows, in R. Genevois; D.L. Hamilton & A. Prestininzi, ed., Proceedings of the 5th International Conference on Debris Flow Hazards Mitigation, Mechanics, Prediction and Assessment, Padua, Italy, June 14-17, 2011, Italian Journal of Engineering Geology and Environment.
Kaitna, R.; Hsu, L.; Rickenmann, D. & Dietrich, W. (2011), On the development of an unsaturated front of debris flows, in R. Genevois; D.L. Hamilton & A. Prestininzi, ed., Proceedings of the 5th International Conference on Debris Flow Hazards Mitigation, Mechanics, Prediction and Assessment, Padua, Italy, June 14-17, 2011, Italian Journal of Engineering Geology and Environment.
Hsu, L.; Kaitna, R.; Dietrich, W. & Sklar, L. (2011), Boundary shear stress of granular flows, in R. Genevois; D.L. Hamilton & A. Prestininzi, ed., Proceedings of the 5th International Conference on Debris Flow Hazards Mitigation, Mechanics, Prediction and Assessment, Padua, Italy, June 14-17, 2011, Italian Journal of Engineering Geology and Environment.
Hsu, L.; Dietrich, W. E. & Sklar, L. S. (2008), Experimental study of bedrock erosion by granular flows, J. Geophys. Res. 113(F2), F02001, http://doi.org/10.1029/2007JF000778.
Hsu, L., Dietrich, W., & Sklar, L. (2007). Normal stresses, longitudinal profiles, and bedrock surface erosion by debris flows: initial findings from a large, vertically rotating drum. Debris-Flow Hazards Mitigation: Mechanics, Predictions, and Assessment, 141-150.
Hsu, L. & Bürgmann, R. (2006), Surface creep along the Longitudinal Valley fault, Taiwan from InSAR measurements, Geophys. Res. Lett. 33(6), L06312, http://doi.org/10.1029/2005GL024624.
Hsu, L. & Pelletier, J. D. (2004), Correlation and dating of Quaternary alluvial-fan surfaces using scarp diffusion, Geomorphology 60(3-4), 319 - 335, https://doi.org/10.1016/j.geomorph.2003.08.007
Bell, N.; Hsu, L.; Jacob, D. J.; Schultz, M. G.; Blake, D. R.; Butler, J. H.; King, D. B.; Lobert, J. M. & Maier-Reimer, E. (2002), Methyl iodide: Atmospheric budget and use as a tracer of marine convection in global models, J. Geophys. Res. 107(D17), 4340, http://doi.org/10.1029/2001JD001151.
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
USGS Model Catalog Tools and Metadata
Tools and metadata for the USGS Model Catalog.
USGS Model Catalog intake repository
This project contains the repository component of a modular catalog implementation.
Filter Total Items: 43