The Value of Collaboration & ACARN's Data Sharing Infrastructure - Sean Smukler, UBC
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Science
Why sharing data is important for agricultural adaptation research and how the data sharing infrastructure developed by ACARN can enable sharing of data sets across regions and researchers.
4
Ray et al. (2019) Climate change has likely already affected
global food production. PLOS ONE 14(5)
-24.5%
5.1%
Bruker TENSOR 37 FTIR
Diffuse Reflectance Infrared Fourier Transform (DRIFT)
FT-IR TENSOR with HTS-XT plate reader for
automated Mid-IR
Micro-plate prepped for FT-MIR analysis
FTIR Results and Potential
10-20% the cost of standard wet chemistry
Growing Recognition of Public Data Archiving
• Tri-Agency Open Access Policy May 1, 2015 – peer-reviewed
publications must be freely accessible within 12 months of publication
• CIHR only must deposit bioinformatics, atomic, and molecular
coordinate data into the appropriate public database
• Databases such as figshare, Dryad, TreeBASE, and GenBank
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Benefits of Data-sharing
• Prevents loss from hardware malfunction or obsolescence
• Preserves data when researchers move to different projects
or retire
• Facilitates good metadata production
• Enables regional analysis and modeling
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To Deposit or Not Deposit
• Real or perceived costs to share
• BC’s Personal Information Protection
Act (PIPA)
• Collaborator trust
10
Roche DG, Lanfear R, Binning SA, Haff TM, Schwanz LE, et al. (2014) Troubleshooting Public Data Archiving: Suggestions to
Increase Participation. PLOS Biology 12(1)
Illustration credit: Ainsley Seago
Development of a BC Agricultural Data-sharing Infrastructure
for Climate Adaptation Research
December 15th 2017- March 20th, 2018
• Jason Lussier, the BC Agricultural Climate Adaptation Research
Network
• Dr. Lauchlan Fraser, Thompson Rivers University
• Dr. Sean Smukler, University of British Columbia
• Dr. Juli Carrillo, University of British Columbia
• Serena Black, BC Forage Council
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BC Agricultural Soil Data-sharing
Working Group
• March 24, 2018 PRSSS
The Role of Soil in
Climate Change
Adaptation
• October 5, 2018 - Soil
Database Development
Workshop
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Data
• BC Nutrient database
• ~5000 crop, soil amendment
data
• ~ 2000 soil data (e.g. past FAIP
project)
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Sampling across LFV
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LULC TYPE TOTAL PLOTS
Annual Crop 100
Field Margin & Hedgerow 18
Riparian Buffer 14
Grassland 52
Perennial Crop 100
Forest/Forest Patch 15
Wetland 10
Total 309
Next Steps
• Make the soils and amendment data flow operational
• Recruit participants
• Develop field and lab protocols
• Repeat for other datasets
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Editor's Notes
Ensure scientists are focused on research that is most relevant for producers and policy
Sharing data, methodologies and results among researchers
Developing joint coordinated research projects
Enhancing knowledge transfer from researchers to producers
Training future researchers and outreach specialist
http://www.science.gc.ca/eic/site/063.nsf/eng/h_F6765465.html?OpenDocument
Tri-agency policy
3.1 Peer-reviewed Journal Publications
Grant recipients are required to ensure that any peer-reviewed journal publications arising from Agency-supported research are freely accessible within 12 months of publication.
Recipients of CIHR funding are required to adhere with the following responsibilities:
Deposit bioinformatics, atomic, and molecular coordinate data into the appropriate public database (e.g. gene sequences deposited in GenBank) immediately upon publication of research results.
Decision Aid System for Integrated Pest Management Molly Thurston
Technology and data for adaptation Svan Lembke & Lee Cartier
The LFV is in the southwest corner of the province
We stratified sampling using a conditional latin hyper cube method across 7 LULC types
We collected 309 samples
The plot methods were similar to the ones I had previously described