AGROVOC recommended as a Common Agricultural Data Standard for Data Sharing Context to accelerate Data-Driven Agriculture Development in Cambodia and Nepal

AGROVOC has been recommended as a Common Agricultural Data Standard for Data Sharing Context to accelerate Data-Driven Agriculture Development in Cambodia and Nepal.

(Image source: Development GATEWAY)

Technology alone cannot lead to data interoperability: consensus-building and change management support are also required to achieve true and sustainable results.

Rice… is what Nepal and Cambodia have in common…

Data-driven agricultural development in these two countries brings up the topic of if/how agriculture and nutrition data in Nepal and Cambodia are similar enough to manage, share, and use to improve food security outcomes?

To answer this question, Development GATEWAY and its partner Athena Infonomics are implementing the Accelerating Data-Driven Agriculture Development in Cambodia and Nepal Activity – funded by USAID and led by FHI360 through the mSTAR program – to support USAID: Feed the Future stakeholders in both countries to improve their data interoperability and sharing practices.

Data Sharing Context

Within the framework of Accelerating Data-Driven Agriculture Development in Cambodia and Nepal Activity, the following challenges and key data interoperability issues were addressed:

  • In-country Feed the Future implementing partners and researchers are operating under unclear or inconsistent data openness and publication policies;
  • Data sharing happens on an ad-hoc basis, if at all, since there is lack of formal data sharing mechanisms among partners;
  • Stakeholders in both countries (Nepal and Cambodia) want an in-country resource to fill their own data sharing and analysis needs;
  • There is need of data exchange among systems;
  • Data files should be opened and interpreted;
  • Data within the file should be understood by the system.

Analysing and Deploying Data Standards

During the project, approximately 25 sample datasets, representing 3,500+ variables to find common interoperability principles and standards for structuring and defining data were analysed.

Following the recommendations to Feed the Future partners and USAID Missions, the importance of building on standards - - that already exist and are widely used by the open data community in agriculture and related sectors (e.g. data quality and interoperability resources from initiatives like AIMS.FAO.ORGGODAN and the FAIR data principles) - - was underlined.

Since USAID Feed the Future partners already follow basic data vocabularies and data management protocols, Feed the Future stakeholders are recommended to:

Adopt a standard controlled vocabulary/ontology, like the FAO of the UN AGROVOC multilingual thesaurus, to define the types and properties of variables in the dataset;

  • Use standard units of measurement and naming schemes for country-specific variables, like administrative boundaries;
  • Follow basic structural standards, like keeping data belonging to the same dataset within a single file; and
  • Document key metadata – scope, collection methodology, availability, terms of use – for the project and the dataset.

Keen to learn also about the Human Side Of Interoperability and Tools for Data Management and Storage deployed to support Accelerating Data-Driven Agriculture Development in Cambodia and Nepal Activity? Then take a look at the blog post Can Nepal and Cambodia Really Have Common Agricultural Data Standards? (source: ICTworks™)

Related:

What does Data Interoperability Require in Practice?

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