Supporting open data & models in the agri-food sector: Experiences from the RDA Agriculture Data IG & Wheat

Data Interoperability WG

V. Protonotarios (Agro-Know), I. Subirats (UN FAO), D. Madalli (ISI), J. Keizer (UN FAO) and E. Dzale (INRA)

Engagement in RDA from Southern-Eastern Europe, Mediterranean and Caucasus region Workshop

25/6/2015, Athens, Greece

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An extraordinary company that captures, organizes and adds value to the rich information available in

agricultural and biodiversity sciences, in order to make it universally accessible, useful and meaningful.

About Agro-Know

http://www.agroknow.grhttp://blog.agro-know.com

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large scale data-related projects

OpenMinTeD: Open Mining INfrastructure for TExt and Data (2015- 2018)

15 partners (incl. UoA, EBI, INRA); tech+data, requirements & evaluation

Big Data Europe: Integrating Big Data, Software and Communities for Addressing Europe’s Societal Challenges (2015-2018)

12 partners (incl. FAO); agri-food community & use cases

agINFRA: a data infrastructure to support agricultural scientific communities (2011 - 2015)

12 partners (incl. FAO); tech coordinator, evaluation, sustainability in G8 Open Data in Agriculture Action Plan for Europe

SemaGrow: Data intensive techniques to boost the real-time performance of global agricultural data infrastructures (2012 - 2015)

8 partners (incl. FAO, WUR); tech, evaluation, sustainability in G8 Open Data in Agriculture Action Plan for Europe

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indicative list of partners & clients

Food and Agriculture Organization (FAO) Global Forum on Agricultural Research (GFAR) International Fund for Agricultural Development (IFAD) The Open Data Institute (ODI) World Bank Group (WB) UK’s Dept for International Development (DFID) Michigan State University (MSU) Wageningen University & Research (WUR) French Institute of Agricultural Research (INRA) International Centre for Research in Organic Food Systems

(ICROFS)

5advocates of open (1/2)

CIARD.net: a global movement dedicated to open agricultural knowledge

Global Open Data for Agriculture and Nutrition (GODAN): make agricultural and nutritionally relevant data available, accessible, and usable for unrestricted use worldwide

6advocates of open (2/2)

The Hague Declaration aims to foster agreement about how to best enable access to facts, data and ideas for knowledge discovery in the Digital Age.

The Bouchout Declaration for Open Biodiversity Knowledge Management

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The Agricultural Data Interest Group (IGAD)

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Agricultural Data Interest Group (IGAD): a domain oriented interest group to work on all issues related to data important for the development of global agriculture

IGAD aims to represent all stakeholders collecting, producing, managing, aggregating, sharing and consuming data for agricultural research, policy formulation, and innovation.

Goal: to promote best practices in the research domain data sharing policies, data management plan, data interoperability-related aspects.

Background

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Established during the 1st RDA Plenary Meeting March 18-20, 2013, Gothenburg, Sweden

Chairs: Johannes Keizer (FAO of the United Nations) Devika Madalli (Indian Statistical Institute) Imma Subirats-Coll (FAO of the United Nations)

Representation of global agriculture research initiatives

IGAD in brief

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Ensure the application of common standards for the interoperability of research outcomes in the agri-food sector Data policies Metadata & vocabularies

Ensure active participation of major organizations & initiatives

Work closely with the Wheat Data Interoperability WG (as a use case)

Aims & objectives

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IGAD is working towards building a community of scientists, experts and Information managers to work on Soil data and common issues, as this is the International year of Soils.

IGAD and the International Year of Soils

http://www.fao.org/soils-2015/en

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Pre-meeting at RDA 6th Plenary Meeting

(Paris, September 21-22, 2015)

Organize discussions around 4 groups:1. Assess and find ways to increase participation from universities,

government and research organizations in the Agricultural sector worldwide

2. Define situation and requirements to meet Open Access and Research Data Policies in Agriculture

3. Increase data access and availability (formats, users)

4. Interoperability (policies, tools, taxonomies, standards)

Next steps (1/2)

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RDA 6th Plenary Meeting (Paris, September 23-25, 2015)

Based on the outcomes of the pre-meeting:

identify the most important & current topics for IGAD to work on;

forge collaborations among existing members; engage new members (initiatives, organizations,

individuals); leverage and use the RDA platform to function, report and

plan outreach of the results.

Next steps (2/2)

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The Wheat Data Interoperability Working Group (WDI)

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The wheat research community is facing societal challenges Wheat is the most widely grown crop in the world and provides 20% of the daily

protein and food calories in the human diet; Wheat is the 2nd most important food crop in the developing world (after rice); With a predicted world population of 9 billion in 2050, the demand for wheat is

expected to increase by 60% compared with 2010; To meet this demand, mean annual yield increases must rise from the current

level of 1% (2001-2010) to 1.6% (2011-2050).

Interoperability of Wheat related data is necessary to address these challenges A variety of new technologies are producing an important quantity of

heterogeneous data; Wheat related information and data systems are diverse; There is a lack of data harmonization and standards;

The context

16The WDI working group in brief

Endorsement: March 2014 Chairs:

Esther Dzale (INRA) Richard Fulss (CIMMYT)

Members: ~=30 members and 15 active members, Wheat scientists, data and metadata technologists

Goal: contribute to the improvement of Wheat related data interoperability by Building a common interoperability framework (metadata, data formats and

vocabularies) Providing guidelines for describing, representing and linking Wheat related

data

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WGI outcomes

1. A report of the survey of existing standards;

2. A cookbook intended for the Wheat data managers community, which provides them with guidelines on what data formats, metadata schemas, vocabularies and ontologies they should use to describe, represent and link different types of Wheat data;

3. A library of linked vocabularies and ontologies in machine readable formats with respect to the Linked Data standards;

4. A prototype which showcases the gain of interoperability

Initial plans

18Where we are

Surveys

•Landscape of Wheat related standards and their use by the community

•Comprehensive overview of Wheat related ontologies and vocabularies

Workshops

•Recommendations

•Mappings between different data formats

•Actions to conduct in order to improve the current level of Wheat related data interoperability

•Interoperability use cases

Implementa

tion

•Interactive cookbook: recommendations + guidelines

•A repository of Wheat related linked vocabularies (Bioportal)

19Examples of use cases

Title Searching for germplasm with specific traits

Description Example of searching for germplasm with specific traits - tagged with ontology terms?

Data types GermplasmPhenotype

Challenges ● Metadata very important ~ standardized format● Association of genes to traits, linked to germplasm, marker information● Need for quality controls- how confident are you of the data source?● Provenance of the germplasm- pedigree, ownership, ● Standard system for tracking germplasm, names

Title Identification of wheat genes that control root growth

Description Requires: Annotated genes (Gene Ontology, PFam, and other functional annotation)

Data types Genomic annotations? - Gene location ? (IWGS-SS ID or MIPS HCS link)

Challenges Mapping between wheat genes and orthologs from other species (deduce function by seq. similarity); Access to RNASeq data (genes that are not expressed in roots may be irrelevant) ; mapping of wheat genes and information on their function based on literature

Title Query on trial data associated with varieties

Data types Phenotypic data, GIS data, (wheat economy/production data)

Description To search wheat varieties with distribution maps, production figures, performances in wheat mega environments, associated projects worldwide plus layers of climatic data on specific wheat production areas and disease prevention information.

Challenges Phenotypic data should be linked to GIS data. Using keywords or ontology terms a system or a tool should be able to pull out such information from different websites/systems developed by wheat community.

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http://ist.blogs.inra.fr/wdi

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Assess the level of visibility and interoperability of Wheat related vocabularies and ontologies Is the vocabulary/ontology updated regularly? What license and/or copyright is used? Is the vocabulary/ontology part of any ontology communities or listing

services? Is the vocabulary/ontology used or implemented in any database/repository? Does the vocabulary/ontology interlink and/or map to other vocabularies and

ontologies? Does the vocabulary/ontology

Identify the domain covered by the ontologies and vocabularies Refine the cookbook Collect more interoperability use cases

Collect some technical details

Wheat related ontologies & vocabularies survey

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Guidelines and

Repository

What level of visibility/operability?

What content?

What formats, and technologies?

Wheat related ontologies & vocabularies survey

The Wheat related BioPortal allows one to search for terms across multiple ontologies, browse mappings between terms in different ontologies, receive recommendations on which ontologies are most relevant for a corpus, annotate text with terms from ontologies

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Target users Wheat related data managers and database developers: guidance

for determining formats for representing and storing wheat data Wheat related researchers: guidance for documenting Wheat data Software developers designing semantic-based search tools:

guidance for choosing specific vocabularies or ontologies to base on

Impacts Improved data discovery, reusability and interoperability Standardization and harmonization of data will reduce variability and

increase relevance of Wheat data related search tools.

Expected Impact

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1. The outputs of the WDI are intended to be a building block for the Wheat Initiative Wheat Information System (WheatIS) The WheatIS brings together the major wheat bioinformatics

platforms and experts and aims to create a framework for the establishment of a global Wheat Information System

2. Agriculture related communities and initiatives such as FAO AIMS, CIARD & GODAN

3. A position paper

Adoption

26Next steps

Metadata (harmonization, minimal metadata sets) Mappings Next workshop (29-30/6/2015)

Review and complete the recommendations Refine and complete the guidelines and the best practices

Finalize the repository of Wheat related vocabularies Prototyping: a semantic knowledge base

Integrate data from different data sources Provide smart search capabilities that leverage the vocabularies used against

the metadata.

Mapping exercise for researchers & organizations Identify, record and publish stakeholders of the wheat research community

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Regional adoption perspectives

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Agricultural Data IG Adoption investigated at global level

Initiatives like GODAN & CIARD e.g. Global Agricultural Concept Scheme (GACS)

Regional/National level Potential for adoption by early adopters Slow adoption of new standards and approaches in general

Wheat Data Interoperability WG Adoption a global level

Wheat Initiative Regional/National level

Identify the needs of research institutes / researchers’ needs

On the adoption of results

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Mapping exercise to identify regional stakeholders To take place by August 2015 through the Wheat Data WG Aims to identify, record and organize persons, organizations & projects

working with Wheat Data Output will be a registry that can be queried

Related activities

EU Map Big Data in agri-food research:www.akstem.com/bde

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Thank youvprot@agroknow.gr

http://www.agroknow.gr@vprot

Most of the material for this presentation was kindly provided by the chairs of the Agriculture Data IG & the Wheat Data WG