CGLabs use cases
Ani Ghosh, Prakash Jha, Julian Ramirez-Villegas
Digital Dynamism for Adaptive Food Systems
CGIAR Big Data in Agriculture Convention 2020
October 21, 2020
YHRGeorgetown Spring 2024 America should Take Her Share
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2020 BIG DATA CG Labs Use Cases
1. CGLabs use cases
Ani Ghosh, Prakash Jha, Julian Ramirez-Villegas
Digital Dynamism for Adaptive Food Systems
CGIAR Big Data in Agriculture Convention 2020
October 21, 2020
2. What is CGLabs?
For users
โข A portable workstation
โข Access to terminals or
notebooks with git
integrations
For system admins
Complete Jupyterhub
experience without the
complicated setup
3. CGLabs
CGIAR data
mapped into
GARDIAN
1. CCAFS-Climate
2. MapSPAM
3. HC27โฆ
Other datasets
available in the internet
My own or my
Centerโs local
data
Link
Download
SFTP transfer/Filezilla
1. CHIRPS
2. SoilGrids
3. โฆ
BVI-CIAT DV
IFPRIโs DV
โฆ
Data
Computing resource
Cloud resource
(AWS, GCP, Azure)
Local Cluster
at my center
Code sharing
GitHub
4. Use case: Crop suitability prediction
Challenges
i) Downloading past and future climate data with
slow internet speed
ii) Process 100s of simulation models (ecocrop,
random forest) with 40+crops and climate
scenario combinations
ecocrop
download
5. Use case: Crop suitability prediction
Changes in common bean suitability (A) current; (B) Future
Kenya Ethiopia
6. Use case: Yield prediction at scale
Challenge
WOFOST/DSSAT simulation with large
number of parameters
wofost
DSSAT
7. Wheat yield potential (WOFOST)
Use case: Yield prediction at scale
Effect of varying planting dates on bean yield (DSSAT)
8. Is it customizable?
โข Yes! Check out https://github.com/SCiO-systems/cgspatial-notebook
โข Need to add more R or Python packages?
Add your r-install command here
install.packages(โterraโ)
9. What would we like to see in the future?
โข Hardware-native docker install with ----
โข Automatic connection to storage (S3, GCS or local file systems)
โข Shared storage between users
โข Cluster (e.g. Kubernetes) support
โข Ability to auto-scale in the cloud
โข Choice of selecting Spot/Preemptible Instances to reduce your cost