Journals increasingly require data underlying publications to be shared
or deposited within an accessible database or repository – as a
condition for publication.
…and there are a growing number of data journals, that provide
citations similar to those for publications – may be used as KPIs…
Why share data? Journal requirements
Piwowar, H.A et al.
Why share data? Citation advantages
Publicly available data was significantly (p = 0.006)
associated with a 69% increase in citations, independently
of journal impact factor, date of publication, and author
country of origin ...
“The goal is to turn data into information, and information into insight.”
– Carly Fiorina, former executive, president, and chair of Hewlett-Packard
Hey Cigi, should I direct seed or transplant my rice?
How should I manage my crop?
Real-time decision support for farmers
Easy natural language as an interface
Smart artificial intelligence trained by
CGIAR and partners
Leveraging open, harmonized and
interoperable “small” data into
queriable large data pool
1. Making data FAIR: Technical support towards CGIAR Center and partner
efforts to make data Findable, Accessible, Interoperable, and Reusable.
2. Enabling data discovery: Enable the contextually-linked discovery of
resources (research outputs, experts, geographies) across CGIAR.
3. Building capacity: Facilitate FAIR data and comfort with Big Data technologies
- the power and the risks (in-person; guidance materials; webinars).
4. Enabling data exploration, analysis, visualization: Leverage interoperability
and reusability to allow semantic exploration and seamless “plug and play”
with analytical and visualization tools.
How is the Platform helping with CGIAR’s FAIRy tale?
Support for Center repositories to implement CG Core Metadata Schema; tools
to facilitate repository and data-level metadata entry using CG Core elements,
Refine and develop Crop Ontology, AgrO, SociO; invest in tools to enable data
Facilitate standardization of agronomic trial data at collection rather than at
archiving, via ontology-based field book (field-testing starts early 2019)
Support for Interoperability...
Support for Reusability (best practices in privacy/ethics)……
Getting to (and leveraging) FAIR…
Click to see other data these
authors may have published
Filter to find data in GARDIAN
based on these controlled
GARDIAN algorithms attempt to find pubs
related to dataset – and vice versa
GARDIAN brings in
data from Genebanks
Zoom in on map and drop pin for pop-
up summary of “rice rainfed yield” for
the country (Benin) – from SPAM 2005;
data from 2010 and 2015 coming soon
…or use polygon feature for summary
of “rice rainfed yield” in a particular
area of interest…
Collaborate and convene around data and
Developing Technical Partnerships
Providing Shared Services (data and tools)
Providing Technical Training
Supporting six Communities of Practice
Mini-Grants for Key Datasets
Data-Driven Agronomy | CIAT
Crop Modeling | CIMMYT
Geospatial Analysis | IFPRI
Livestock Data | Univ. Edinburgh
Ontologies | Bioversity Int’l
Socio-Economic Data | CIMMYT
Innovation process to enhance data
science research in CRPs
5 pilots (100K ea); 1 scale-up (250K)
- Data use
- Revealing Food System Flows
- Monitoring Pests & Diseases
- Disrupting Impact Assessment
- Empowering Data-Driven Farming
S. Mohapatra: Head, Marketing & Communications
C. Kacou: Interim Head of ICT Unit
M. Bernard: Head Knowledge Management
P. Kouame: Data Manager