19th and 20th century agriculture was spurred by three successive revolutions: the mechanical, chemical and biological revolutions. A 21st century revolution is gaining ground: the data revolution in agriculture.
We enable agricultural innovation by turning big (and little), often disparate, and sometimes messy data into actionable information.
Your data, your tools, you choose.
From enabling entirely open data, or sharing only with selected partners, to totally private data.
GEMShare™ lowers the barriers to sharing data, and doing that smartly, while enabling data providers to preserve their formal and informal IP.
Our design philosophy is to continuously add value by sticking with two familiar adages:
“Don’t reinvent the wheel” and “Stay on the cutting edge,” or, better still, “Create the cutting edge!”
Secure and private data means just that.
The data and analytical tools accessible via G.E.M.S™ live in a platform designed and implemented to address a broad spectrum of use requirements from open to private. G.E.M.S™ staff are trained in best practices and security standards, which are applied to address a broad set of data use agreements in the field of agroinformatics..
Beyond data to actionable information.
GEMSTools™ is an ever-expanding suite of analytical tools designed to cleanup messy (meta-)data, intelligently impute missing data, and apply advanced analytic methods to genomic, environmental, management and socio-economic data.
Work with data from individual trials in CSVs to high resolution satellite images. Collect and sample data in G.E.M.S before transferring it to a laptop for work in the field. Mix published data on the G.E.M.S platform with proprietary data in a secure data center. Using a combination of robust transfer protocols and containerization, G.E.M.S enables co-location of data, tools, and compute power where it is needed to solve the problem at hand.
Standardize data from disparate sources through machine-assisted spell correction and ontology matching.
Innovating in agriculture can involve decisions that span from molecules to markets. Increasingly the data and information that enable these innovation span this entire innovation value chain, and ensuring functional interoperability of G x E x M x S data forms new and valuable links along this entire chain. G.E.M.S™ is designed to to foster links across different types of data through standardization of data.
G.E.M.S™ puts FAIR principles into practice making its sharable data (and analytical tools) Findable, Accessible, Interoperable, and Reusable.
But G.E.M.S™ goes beyond FAIR to FAIR(ER), adhering to Ethical data sharing and Reproducible standards as well.