Reusable Software and Open Data To Optimize Agriculture
Abstract: Humans need a secure and sustainable food supply, and science can help. We have an opportunity to transform agriculture by combining knowledge of organisms and ecosystems to engineer ecosystems that sustainably produce food, fuel, and other services. The challenge is that the information we have. Measurements, theories, and laws found in publications, notebooks, measurements, software, and human brains are difficult to combine. We homogenize, encode, and automate the synthesis of data and mechanistic understanding in a way that links understanding at different scales and across domains. This allows extrapolation, prediction, and assessment. Reusable components allow automated construction of new knowledge that can be used to assess, predict, and optimize agro-ecosystems. Developing reusable software and open-access databases is hard, and examples will illustrate how we use the Predictive Ecosystem Analyzer (PEcAn, pecanproject.org), the Biofuel Ecophysiological Traits and Yields database (BETYdb, betydb.org), and ecophysiological crop models to predict crop yield, decide which crops to plant, and which traits can be selected for the next generation of data driven crop improvement. A next step is to automate the use of sensors mounted on robots, drones, and tractors to assess plants in the field. The TERRA Reference Phenotyping Platform (TERRA-Ref, terraref.github.io) will provide an open access database and computing platform on which researchers can use and develop tools that use sensor data to assess and manage agricultural and other terrestrial ecosystems. TERRA-Ref will adopt existing standards and develop modular software components and common interfaces, in collaboration with researchers from iPlant, NEON, AgMIP, USDA, rOpenSci, ARPA-E, many scientists and industry partners. Our goal is to advance science by enabling efficient use, reuse, exchange, and creation of knowledge. --- Invited talk for the "Informatics for Reproducibility in Earth and Environmental Science Research" session at the American Geophysical Union Fall Meeting, Dec 17 2015.
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Reusable Software and Open Data To Optimize Agriculture
- 1. Reusable Software and Open Data To Optimize Agriculture David LeBauer AGU 2015 Fall Meetings @dlebauer
- 2. Overview Ideas: Software: Modular, Reusable, and Useable Data: Harmonization, Distribution Workflows: Reproducible, Automated Science: Cumulative and Synthetic Examples: PEcAn ProjectBETYdb TERRA Ref
- 3. Agriculture: Model and Application Food, fuel, and other ecosystem services (e.g. C, N, H2O) Basic science: genes to organism to ecosystem Engineering applications: computing, data collection, prediction Enzyme Ecosystem Continent
- 4. Overview Ideas: Software: Modular, Reusable, and Useable Data: Harmonization, Distribution Workflows: Reproducible, Automated Science: Cumulative and Synthetic Examples: PEcAn ProjectBETYdb TERRA Ref betydb.org github.com/pecanproject/bety @BETYdatabase
- 5. BETYdb Database for meta-analysis (BETYdb) Model-data synthesis, provenance (PEcAn) Link Genomics to Phenomics (TERRA Ref)
- 6. Primary Research Measurement PublicationAnalysis LeBauer 2008, 2010
- 7. Spreadsheet Publication Extraction Analysis… Publication Extraction Meta Analysis LeBauer and Treseder 2008
- 8. BETYdb: Data entry Workflow BETYdb.org →docs →data entry workflow LeBauer et al, in prep Technicians Enter and CheckScientist Identifies Data
- 9. Open Data Entry and QAQC Shared Spreadsheets Issue Tracker
- 10. Data Access /search?search=Salix+vcmax RWeb Application + API BETYdb.org →docs →Data Access PEcAn
- 11. Overview Ideas: Software: Modular, Reusable, and Useable Data: Harmonization, Distribution Workflows: Reproducible, Automated Science: Cumulative and Synthetic Examples: PEcAn ProjectBETYdb TERRA Ref pecanproject.org github.com/pecanproject/pecan @PEcAnproject
- 12. Ecosystem Modeling c. 2009
- 13. PEcAn LeBauer et al, 2013 Ecological Model-data Synthesis
- 14. PEcAn: complex models in complex workflows Modeling Information Systems Dietze 2016 Princeton University Press BioCro / Wimovac Crop Model Humphries and Long, 2005 Miguez et al 2009
- 15. Ecosystem Modeling c. 2012 Select Site Configure Run Visualize, ExportRun Model Dietze, Kooper, LeBauer 2012
- 16. LeBauer et al 2013 Given available data, How well do we know parameters? How does this affect prediction? What should we collect? PEcAn: Sensitivity Analysis & Variance Decomposition
- 17. PEcAn, Automated Dietze et al 2014
- 18. BETYdb + PEcAn BETYdb is PEcAn’s informatics backend Provides data, workflow and data provenance Federated network of databases
- 19. Overview Ideas: Software: Modular, Reusable, and Useable Data: Harmonization, Distribution Workflows: Reproducible, Automated Science: Cumulative and Synthetic Examples: PEcAn ProjectBETYdb TERRA Ref terraref.ncsa.illinois.edu github.com/terraref @terra_ref
- 20. TERRA: Better Breeding Through Science We have increased yields many times in the last 60 years. What new opportunities does modern science provide? University of Illinois Integrated Pest Management • Use scientific understanding to select for traits • Replace manual measurement with remote sensing • Target specific genes and phenotypes in crosses
- 21. ARPA-E TERRA Program Six Funded Teams $30 m in awards $5 m in sensors TERRA Ref: Public reference data HPC Computing
- 22. TERRA Ref: An Agricultural Observatory Similar to and informed by: Large Synoptic Survey Telescope National Ecological Observatory Network
- 23. Open: Science, Data, Software Useable: Useful and Familiar to Scientists, Breeders, Precision Ag Modular: Extensible, Distributed, Automated, Interoperable Interdisciplinary: Genes to Ecosystems with Robots, Vision, Statistics Scalable: From Mobile Devices to High Performance Computers terraref.ncsa.illinois.edu @terra_ref github.com/terraref TERRA Reference Data and Computing
- 24. Sensor Data Sources Lemnatec Indoor Danforth, St. Louis Lemnatec Field USDA ALRC, Maricopa, AZ Tractor and UAV Kansas State Plus, other teams, public, (sharing optional) Shared Sorghum genomics and germplasm,
- 25. Reference Data Raw Sequence Data Aligned Reads SNPs Images Spectra Point clouds Shapes Biomass, Growth Tissue Chemistry Photosynthesis Yield Stress Tolerance Ecosystem Services
- 26. Big Data Volume & Velocity Imaging Spectrometers: VNIR ~3-4 TB/d SWIR ~1 TB/d 3D Laser Scanner ~ 1 TB/d 4 Year Total: 1 - 40 PB VNIR SWIR 3D … Everything else
- 27. Computing and Storage Roger Server: 1PB online, GIS optimized Nebula: NCSA Open Stack Server Blue Waters: 10 PB tape storage Your Local: [Desktop, HPC, or Sensor Platform]
- 28. Data Products Standards Committee Paul Bartlett Near Earth Autonomy Jeff White USDA ALARC, ICASA Melba Crawford Purdue University Michael Gore, Elodie Garazave Cornell University Matt Colgan Blue River Christer Janssen PNNL Barnabas Poczos Carnegie Mellon Alex Thomasson Texas A&M University Cheryl Porter University of Florida, AgMIP, USDA Shawn Serbin Brookhaven National Lab, PEcAn Shelly Petroy Christine Laney NEON Carolyn J. Lawrence-Dill Iowa State, AgBioData Eric Lyons University of Arizona, CoGE Ted Habermann HDF Group Participants • Project representatives • Domain Experts • Scientific Community (You)* Responsibilities • Define Data • Revise, Improve • Training, Outreach * github.com/terraref/reference-data/issues
- 29. Computing Pipeline Data Uploaded via API Triggers Analytical Pipeline Generates and Stores Data, Metadata Users select data, launch VM: Favorite Software Data Mounted HPC Access States can be Shared, Archived
- 30. Acknowledgements Projects: PEcAn, NCSA, BrownDog, Plants In Silico, CyberGIS, National Data Service, USDA, AgMIP, National Data Service Data: Providers and Curators Mentors: Mike Dietze, Steve Long, Kathleen Treseder Funding: NSF, EBI, ARPA-E, DOE, NASA
- 31. Contact Web GitHub s Twitter a David LeBauer dlebauer@illinois.edu dlebauer @dlebauer BETYdb betydb.org pecanproject/bety @BETYdatabase PEcAn Project pecaproject.org pecanproject/pecan @PEcAnproject TERRA Ref terraref.ncsa.illinois.edu terraref @terra_ref
- 32. PIs Amy Colin-Marshal, Steve Long, James O’Dwyer, Diwakar Shukla Plants in Silico Multi-scale modeling platform to predict crop response to climate change
- 33. Plants in Silico: Modular Architecture Zhu et al, 2015 Plant Cell Environ