Developing Data Interoperability using standards: A Wheat Community use case

 

The International Wheat Initiative (IWI) has identified easy access and interoperability of all wheat-related data as a top priority for the wheat research community (and agriculture in general), which is in line with FAIR (findable, accessible, interoperable, re-usable) data principles.

Interoperability - - understood as a the ability of two or more systems to cooperate to exchange and interpret shared data/information - -  is a growing concern for different research communities - -  as the need to interpret the deluge of (managed, published, and reused) data obtained through high-throughput technologies grows ...

To face the challenge of data interoperability in wheat research communitymembers of the Wheat Data Interoperability Working Group (WG) 

- - one of the WGs of the Research Data Alliance (RDA) and the only WG of the Agriculture Data Interoperability Interest Group (IGAD) - - 

published the Wheat Data Interoperability Guidelines, which provide information on the best practices (in terms of use of data formatsmetadata standards and ontologies),  tools, recommendations and examples on how to create, manage and share data related to Wheat.

This joint effort of the Wheat Research Community is presented in the recently published article : 

Dzale Yeumo E, Alaux M, Arnaud E et al. Developing data interoperability using standards: A wheat community use case [version 1]. F1000Research 2017, 6:1843 (doi: 10.12688/f1000research.12234.1), 

distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Enjoy the reading !  

community-driven approach for data interoperability guidelines design, validation, publishing and adoption - - described in detail in the aforementioned article - - is generalizable to other (agricultural) domains.

In particular, built on existing standards and practices, the Wheat Data Interoperability Guidelines present a selected set of recommendations on how to publish and manage data types identified by the wheat research community as the most important for the coming years, such as: 

sequence variants :
the nucleotide differences between two (or several) sequences at the same locus (usually between a reference sequence and another sequence). 

genome annotations
a process of attributing structural and functional information to sequences. 

phenotypes
the observable characteristics of an organism resulting from interactions between genes and the environment in which it grows. 

germplasm data
living genetic resources such as seeds or tissue, maintained for the purpose of breeding, preservation, and other research uses because it contains the information for a species’ genetic makeup, a valuable natural resource of plant diversity.

gene expression analysis measures the abundance of the mRNA molecules, and gives us insight into the regulation of the genes of interest.

physical maps 
built using molecular biology techniques, like fingerprinting, to examine DNA molecules in order to show sequence features positions. 

The Wheat Data Interoperability Guidelines of the WDI-WG are intended for data producers, data managers, data consumers, and software developers

The adoption of this guidelines - - that constitute a key building block for FAIR data sharing infrastructures -  - will facilitate the depositing of data within well recognized repositories in addition to make them easily understandable and reusable.
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