FOCUS on Agricultural Data Interest Group (IGAD) | RDA11 meeting
On 21 - 23 March, 2018 (Berlin, Germany), the Research Data Alliance Plenary (RDA)11: "From Data to Knowledge" welcomed 80+ (RDA Interest and RDA Working) Groups & BoF breakouts sessions, with 661 participants from 41 countries! The RDA11 plenary marks the 5 years anniversary of the RDA, and Agricultural Data Interest Group (IGAD) is proud to have been there since the beginning, and to continue contributing to a number of RDA’s support projects.
During the RDA11, different opportunities and challenges of a global data ecosystem - best practices, standards and interoperable data infrastructures fostering implementation of FAIR data, cross-disciplinary knowledge and data/driven innovation - were discussed. In this context, the IGAD focused (19-23 March 2018) particular attention on the cross-disciplinary issues in the implementation of the FAIR (Findable, Accessible, Interoperable, Re-usable) principles.
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 | FAIR PRINCIPLES TO ALL ELEMENTS OF |
Under this theme, the Agricultural Data Interest Group (IGAD) |RDA11 meeting was dedicated to the discussion of What does FAIR mean for a community like agri-food? and What does it do about it?
The IGAD event was attended by 66 participants from all over the world who shared their points on (and spread breakthroughs about) FAIR data use-cases from a lot of experience in working with data. Various presentations and discussions welcomed synergies with other RDA Groups, to accelerate FAIR-data-driven innovation together.
- and had 20 presentations covering the broader spectrum of FAIRness. A number of concrete projects for implementing FAIR principles in various agriculture-related communities were presented.
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19 March 2018 : the first IGAD|RDA11 day – was dedicated to The FAIR principles:
| The session was followed by Q&A, recommendations and suggestions basing on the previous presentations. Among the speakers of the second session - moderated by Patricia Bertin (EMBRAPA, Brazil) - there were: |
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In the breaks among the sections, participants asked questions to the speakers, and communicated with colleagues about challenges faced in: implementation of FAIR principles to meta(data), application CC0 and CC-BY licenses to data, sustainability of standards including vocabularies, identifiers.
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| The fourth session was introduced by Esther DZALE YEUMO (INRA, France), followed by: |
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The following core issues permeated all IGAD presentations and contributions: Challenges specific to semantic interoperability – such as “Interoperable” and “Reusable” - should be addressed in a collaborative way, to overcome science-intrinsic obstacles, such as discipline-specific problems.
For more details on the IGAD|RDA11 presentations, you might be interested in viewing the IGAD|RDA11 Agenda and slides on OKAD: F1000Research.
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| The IGAD Working and Discussion groups discussed their accomplishments so far and what actions should be taken forward to achieve what is planned. |
Some highlights from: “Metrics and Indicators in Agricultural Sciences” (agenda)
The group met to discuss about various linked aspects of responsible use of metrics and indicators in agricultural science. While speaking about "FAIRness" - the degree to which a digital resource is Findable, Accessible, Interoperable, and Reusable – which may be defined by increased adherence to measurable indicators, the group also presented its white paper (in progress) on responsible use of metrics and indicators in agricultural sciences. The group has reached out to the key players in the area such as: INRA through ASIRPA Project, CIRAD, CSIC-UPV, CWTS in Leiden University, WUR.
Some highlights from: “Agrisemantics” & “On-Farm Data Sharing”
Besides the outputs of this group, it has also presented a roadmap to facilitate the use of semantics in agriculture and nutrition, i.e. to guide integration of metadata production, format conversion, - to support visualization & human validation of mappings as well as access to existing semantic technologies/methodologies. The group conducted a project to demonstrate the feasibility of generating a dataset in the RFD format following the MIAPPE specification from a rich dataset about winter wheat phenotypic data. The main challenge expressed is the implementation of FAIR data to make them really interoperable.
There is need to develop good practices that will enable and facilitate the free flow and reuse of agricultural data across locations. It would be a good practice to put farmers into clusters, each sharing their farming experiences…
Some highlights from: “Wheat- & Rice Data Interoperability”
Following Wheat Data WG Guidelines (included in the FAIRsharing platform and discussed on F1000Research), the Rice Data Interoperability group is working on a cookbook intended for the Rise data managers community. This cookbook will include guidelines on metadata, vocabularies and ontologies plus a decision tree based on data and metadata description recommendations and file format recommendations. The groups also plans to develop and curate a repository of controlled vocabularies and ontologies compliant with the Linked Data standards. This should be the basis for a prospect on multi-lingual conversion of ontologies. Moreover, it is planned to release a Rice-specific data registry and good practices methods for digitization of Rice Legacy Data. How does concept of ‘FAIR use’ apply to copyright law? Even derived metadata could be subject to copyright or license restrictions. Options: (1) Share URLs only, (2) Contact the copyright holder to request permission (chances are they will allow) to share their content (‘data’). This is a complex issue related to copyright (and probably licensing), and the answer may vary depending on the country of the researcher and the location of their database. To be continued…
During groups discussion there was an interswitch with "Capacity Development" group
It was intersting to explore various areas of collaborations and how the IGAD groups can be helped in terms of education and training activities focused on agricultural science needs linked to (open) (research) data management issues. [Read on some experiences in the context of RDA/IGAD and GODAN Action]. The Capacity Development group will empower the existing collaboration with GODAN and GODAN Action. This latter is a project to enable the effective use of open data in tackling the food security and nutrition challenges by building the capacity of potential stakeholders, - to both understand the potential of research and open data for agriculture and nutrition and to engage with it practically. To assess on the current needs within IGAD in terms of capacity development and advocacy, the group will start with Wheat Data WG.
Lifelong learning around data issues is not just a way to boost our skills but also our data-driven economy. Training helps people develop skills and this would also have a tremendous added value for the productivity and competitiveness of the agricultural-related sectors.
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The IG Agricultural Data (IGAD) permeated with a number presentations and contributions interchanging its achievements with RDA representatives from Africa, Asia, Europe, Australia, US.
In particular, IGAD took part in a RDA BoF meeting : Digital Extension Advisory Services: Towards a Data Driven Disruption, and contributed to the discussions on practical issues around the implementation of the FAIR Principles and challenges in the agricultural domain during a joint working meeting among : (1) IGAD (2) IG Data Discovery Paradigms (3) IG ELIXIR Bridging Force (4) WG FAIRsharing Registry: connecting data policies, standards & databases in life sciences (5) IG Repository Platforms for Research Data.
| CONCLUSIONS OF THE IGAD RDA11 MEETING |
1. We all agree that FAIR Principles are important in the agricultural domain. But … FAIR Principles interpretation & implementation can be problematic, due to:
- Persistence of identifiers, e.g. pesticides can be only registered for a certain period of time;
- There are a relevant number of data standards not conforming the FAIR principles – e. g. they lack a mechanism for globally unique identification, do not use open and free protocols for data exchange or do not provide vocabularies that allow data to be semantically machine-accessible, – thus making it more difficult to achieve FAIR conformance. Mapping layers can help here, but there is some work to be done to convince communities that FAIR conformance is a valuable goal to achieve and to specify and implement these mapping layers;
- Ethical and legal consideration can impact the level of FAIRness.
2. There is a need to enhance targeted training and advocacy to raise awareness about how FAIR data works and which concrete benefits they can derive from a change in data-driven culture.
- What is the nexus between data FAIRness vs data value?
- What does FAIRness mean for the Agriculture community and what do we do with it?
- How can we achieve interoperability as transparently as possible for data producers?
- How to agree on right standards?
- How to provide machine readable licenses?
- How to provide tools to assess and improve the quality of the data, eg. metadata collection automation
- How to facilitate the implementation of existing recommendations?
3. Technical requirements for making data interoperable and reusable should be turned into recommendations and awareness about their existence should be widely raised.
4. Policy enforcement at institutional level and its taking back to the funders is needed.
5. Socio-cultural barrier to data FAIRification needs to be addressed through more credit, incentives.
IGAD|RDA11 concluded with lots of outputs and actions to do until next time we meet in RDA12 : Digital frontiers of global science, as part of the International Data Week|IDW 2018 : #internationaldataweek, #idw2018, @resdatall, @CODATANews, @ICSU_WDS, @aosp_africa : to be held on 5-8 November 2018, in Botswana (Africa).
It’s every time great to meet the @resdatall community - putting faces to names of collaborators, meeting new, bright people dedicated to #data, #researchdata, #DataManagementPlan, #DataScience,
#Datamanagement, #FAIRdata, #FAIRprinciples, #ResearchDataManagement, #RDM,
#openscience, #OpenData, #datasharing and much more!
Many thanks to our hosts, partners and sponsors!
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And, thanks again for your interest !
