Data Science Team

To address the event-driven, rapidly changing needs of 21st- century society, water science must be open and data-driven, use the best available scientific methods, and rapidly communicate findings to the public using multiple platforms, including print, web, and social media. To support these needs, the USGS Office of Water Information (OWI) Data Science team has developed a foundation for rigorous and efficient data-driven scientific analysis, quick assembly of thematic teams and dissemination of contemporary science, and advancement of scientific computing best practices across the USGS and partners.

Jordan Read

Jordan Read

Lindsay Carr

Lindsay Carr

Jordan Walker

Jordan Walker

Luke Winslow

Luke Winslow

Emily Read

Emily Read

Laura DeCicco

Laura DeCicco

Alison Appling

Alison Appling

David Watkins

David Watkins

The OWI Data Science team, which is a cross-functional team of earth scientists, data analysts, and computer scientists, has four objective functions that are designed to increase the efficiency of USGS science and more effectively communicate its value to the Nation:


We build tools and software that enable reproducible data & modeling pipelines. The development of these tools is aligned with the architectural recommendations of the software development lifecycle best practices. We work with scientists to design, implement, and communicate reproducible workflows for earth science (primarily water science) that will satisfy USGS requirements for data access. Many of these tools take advantage of High-Throughput Computing (HTC) resources, and we often publish papers that describe novel analytical techniques, methods, and research applications.


To promote and enable more scientists to conduct efficient, data-driven analyses, we offer training in scientific computing workshops. We currently have three different workshops: Introduction to R, USGS OWI R Tools, and Advising in Scientific Computing. The Introduction to R workshops are typically 2-3 days long, are hands-on, and cover basic skills for using R for a reproducible, scalable, and transparent scientific workflow. The curriculum takes students through common data analysis workflow steps:

Training Workflow image

The USGS OWI R Tools workshop focuses on specific applications of R for earth science analyses, and teaches the basics of using OWI R packages. This course expects participants to have an intermediate level of R experience. Advising in Scientific Computing is an informal workshop where a group interested in developing their own R package can work with some of our experienced R package developers. The workshop covers version control (Git/GitHub), and package development best practices. By the end of the week, participants should have functioning package that they can continue to develop and maintain without the OWI team.

Emily Read teaching r Data Carpentry Lesson Andrew Yan helping student with R Alison Appling teaching R R workshop in Helena, MT R workshop in Ft Collins, CO R workshop in Helena, MT back of room OWI Tools Middleton, WI

Please visit our R Community website for more information on Introduction to R workshops. To learn more about USGS OWI R Tools or Advising in Scientific Computing contact <>

Visualization Portfolio

We rapidly develop and deploy visualizations on current water issues as part of the USGS Visualization Lab (VIZLAB). These visualizations involve working with USGS scientists and partners to highlight timely science in accessible and appealing visual stories.

Recent publications

We collaborate with water science practitioners to tackle water resources questions that are analytically complex and computationally challenging, broad or highly resolved in space and time, and diverse in the type or structure of supporting data. This research portfolio demonstrates the value of a data-driven scientific approach through application of data science best practices, and is accomplished using transparent, scalable, and efficient data science approaches. Our group continues to identify, expand on, and share skills in the application of modeling approaches, machine learning, algorithm development, and remote sensing image processing to water science.


Snortheim CA, PC Hanson, KD McMahon, JS Read, CC Carey, HA Dugan. 2017. Meteorological drivers of hypolimnetic anoxia in a eutrophic, north temperate lake. Ecological Modelling. 343: 39-53. doi: 10.1016/j.ecolmodel.2016.10.014


Thieler ER, SL Zeigler, LA Winslow, MK Hines, JR Read, JI Walker. in press. Smartphone-based distributed data collection enables rapid assessment of shorebird habitat suitability. PLoS ONE

Winslow LA, JA Zwart, RD Batt, HA Dugan, RI Woolway, JR Corman, PC Hanson, JS Read. in press. LakeMetabolizer: An R package for estimating lake metabolism from free-water oxygen using diverse statistical models. Inland Waters.

Brentrup JA, CE Williamson, W Colom-Montero, W Eckert, E de Eyto, H-P Grossart, Y Huot, P Isles, LB Knoll, TH Leach, CG McBride, D Pierson, F Pomati, JS Read, KC Rose, NR Samal, PA Stæhr, LA Winslow. in press. Extending the Plankton Ecology Group (PEG) model: The potential of high-frequency profiling to assess vertical and seasonal patterns of phytoplankton dynamics in lakes. Inland Waters.

Read JS, C Gries, EK Read, J Klug, PC Hanson, MR Hipsey, E Jennings, CM O’Reilly, LA Winslow, D Pierson, C McBride, DP Hamilton. in press. Generating community-built tools for data sharing and analysis in environmental networks. Inland Waters.

Dugan HA, RI Woolway, AB Santoso, JR Corman, A Jaimes, ER Nodine, VP Patil, JA Zwart, JA Brentrup, AL Hetherington, SK Oliver, JS Read, KM Winters, PC Hanson, EK Read, LA Winslow, KC Weathers. in press. Consequences of gas flux model choice on the interpretation of metabolic balance across 15 lakes. Inland Waters.

KC Rose, LA Winslow, JS Read, GJA Hansen. in press. Climate-induced warming of lakes can be either amplified or suppressed by trends in water clarity. Limnology and Oceanography Letters.

Winslow LA, S Chamberlain, AP Appling, JS Read. 2016. sbtools: A package connecting R to cloud-based data for collaborative online research. The R Journal. 8(1):387-98.

Hansen GJ, JS Read, JF Hansen, LA Winslow. 2016. Projected shifts in fish species dominance in Wisconsin lakes under climate change. Global Change Biology. doi:10.1111/gcb.13462

EK Read, M O'Rourke, GS Hong, PC Hanson, LA Winslow, S Crowley, CA Brewer, KC Weathers. 2016. Building the team for team science. Ecosphere 7(3):e01291.10.1002/ecs2.1291


O'Reilly CM*, S Sharma*, DK Gray*, SE Hampton*, JS Read, RJ Rowley, P Schneider, JD Lenters, and others. 2015. Rapid and highly variable warming of lake surface waters around the globe. Geophysical Research Letters. 42, doi:10.1002/2015GL066235. *joint first authors

Read JS, JI Walker, AP Appling, DL Blodgett, EK Read, LA Winslow. 2015. geoknife: Reproducible web-processing of large gridded datasets. Ecography. 38: 1-7. doi:10.1111/ecog.01880

Hirsch RM, SA Archfield, LA De Cicco. 2015. A bootstrap method for estimating uncertainty of water quality trends. Environmental Modelling & Software. 73: 148-66.

Read EK, V Patil, S Oliver, A Hetherington, J Brentrup, J Zwart, K Winters, J Corman, E Nodine, IR Woolway, H Dugan, A Jaimes, A Santoso, G Hong, LA Winslow, PC Hanson, KC Weathers. 2015. The importance of lake-specific characteristics for water quality across the continental US. Ecological Applications. 25: 943-955.

Hipsey MR, DP Hamilton, PC Hanson, CC Carey, JZ Coletti, JS Read, SW Ibelings, F Valesini, JD Brookes. 2015. Predicting the resilience and recovery of aquatic systems: A framework for model evolution within environmental observatories. Water Resources Research. 51. doi:10.1002/2015WR017175

Read EK, M Bucknell, M Hines, J Kreft, J Lucido, JS Read, C Schroedl, D Sibley, S Stephan, I Suftin, P Thongsavanh, J Van Den Hoek, J Walker, M Wernimont, LA Winslow, and A Yan. 2015. New insight into California's drought through open data. BAAMA Journal, 8(1).

Hirsch, RM and LA De Cicco. 2015. User guide to Exploration and Graphics for RivEr Trends (EGRET) and dataRetrieval: R packages for hydrologic data. No. 4-A10. US Geological Survey.

Gil T, F Michel, V Ratnakar, JS Read, M Hauder, C Duffy, PC Hanson, H Dugan. 2015. Supporting Open Collaboration in Science through Explicit and Linked Semantic Description of Processes. Proceedings of the Twelfth European Semantic Web Conference (ESWC), Portoroz, Slovenia, May 31-June 4 2015.

Corsi SR, LA DeCicco, MA Lutz, RM Hirsch. 2015. River chloride trends in snow-affected urban watersheds: increasing concentrations outpace urban growth rate and are common among all seasons. Science of the Total Environment. 508: 488-497. doi:10.1016/j.scitotenv.2014.12.012

Woolway RI, ID Jones, DP Hamilton, SC Maberly, K Muraoka, JS Read, RL Smyth, LA Winslow. 2015. Automated calculation of surface energy fluxes with high-frequency lake buoy data. Environmental Modelling and Software. 70: 191-198. doi:10.1016/j.envsoft.2015.04.013

Sharma S*, DK Gray*, JS Read*, CM O'Reilly*, P Schneider, A Qudrat, C Gries, S Stefanoff, SE Hampton, S Hook, JD Lenters, and others. 2015. A global database of lake surface temperatures collected by in situ and satellite methods from 1985-2009. Nature: Scientific Data. 2:150008. doi: 10.1038/sdata.2015.8. *joint first authors

Solomon CT, SE Jones, BC Weidel, I Buffam, ML Fork, J Karlsson, S Larsen, JT Lennon, JS Read, S Sadro, JE Saros. 2015. Ecosystem consequences of changing inputs of terrestrial dissolved organic matter to lakes: current knowledge and future challenges. Ecosystems. 18: 376-389. doi:10.1007/s10021-015-9848-y

Read JS, EK Read, KC Rose, LA Winslow. 2015. A method for estimating the diffuse attenuation coefficient (KdPAR) from paired temperature sensors. Limnology and Oceanography: Methods. 12: 53-61. doi:10.1002/lom3.2014.12.10006

Winslow LA, JS Read, GA Hansen, PC Hanson. 2015. Small lakes show muted climate change signal in deep-water temperatures. Geophysical Research Letters. doi:10.1002/2014GL062325

Van Den Hoek J, JS Read, LA Winslow, P Montesano, CD Markfort. 2015. Examining the utility of satellite-based wind sheltering estimates for lake hydrodynamic modeling. Remote Sensing of Environment. 156: 551-560. doi:10.1016/j.rse.2014.10.024


Hamilton DP, CC Carey, L Arvola, P Arzberger, C Brewer, JJ Cole, E Gaiser, PC Hanson, BW Ibelings, E Jennings, TK Kratz, FP Lin, CG McBride, D de Motta Marques, K Muraoka, A Nishri, B Qin, JS Read, KC Rose, E Ryder, KC Weathers, G Zhu, D Trolle, JD Brookes. 2014. A Global Lake Ecological Observatory Network (GLEON) for synthesising high-frequency sensor data for validation of deterministic ecological models. Inland Waters. 5: 49-56. doi:10.5268/IW-5.1.566

Winslow LA, JS Read, PC Hanson, EH Stanley. 2014. Does lake size matter? Combining morphology and process modeling to examine the contribution of lake classes to population-scale processes. Inland Waters. 5: 7-14. doi:10.5268/IW-5.1.740

Read JS, LA Winslow, GA Hansen, J Van Den Hoek, PC Hanson, LC Bruce, CD Markfort. 2014. Simulating 2,368 temperate lakes reveals weak coherence in stratification phenology. Ecological Modelling. 291C: 142-150. doi:10.1016/j.ecolmodel.2014.07.029

Rose KC, LA Winslow, JS Read, EK Read, C Solomon, R Adrian, PC Hanson. 2014. Improving the precision of lake ecosystem metabolism estimates by identifying predictors of model uncertainty. Limnology and Oceanography: Methods. 12: 303-312. doi:10.4319/lom.2014.12.303

Read EK, M Ivancic, PC Hanson, B Cade-Menun, and KD McMahon. 2014. Phosphorus speciation in a eutrophic lake by 31P NMR spectroscopy. Water Research. DOI: 10.1016/j.watres.2014.06.005

Watras CJ, JS Read, K Holman, Z Liu, Y Song, A Watras, S Morgan, EH Stanley. 2014. Decadal oscillation of lakes and aquifers in the upper Great Lakes region of North America: Hydroclimatic implications. Geophysical Research Letters. doi:10.1002/2013GL058679

Winslow LA, JS Read, PC Hanson, EH Stanley. 2014. Lake shoreline in the contiguous United States: Quantity, distribution and sensitivity to observation resolution. Freshwater Biology. 59: 213-223. doi:10.1111/fwb.12258

Cheruvelil KS, PA Soranno, KC Weathers, PC Hanson, SJ Goring, CT Filstrup, EK Read. 2014. Creating and maintaining high-performing collaborative research teams: the importance of diversity and interpersonal skills. Frontiers in Ecology and Evolution. 12: 31-38. DOI: 10.1890/130001

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