Integrate AgriSchemas, KnetMiner, and FAIRAgro guidelines#1806
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Arnedeklerk wants to merge 9 commits intoelixir-europe:masterfrom
Open
Integrate AgriSchemas, KnetMiner, and FAIRAgro guidelines#1806Arnedeklerk wants to merge 9 commits intoelixir-europe:masterfrom
Arnedeklerk wants to merge 9 commits intoelixir-europe:masterfrom
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Added AgriSchemas solutions for lightweight data schematisation. Included MIAPPE-to-AgriSchemas mapping and FAIRAgro soil variable context. Added KnetMiner SPARQL endpoints and AI integration considerations. Updated tool links and updated contributor metadata. Please review!
Arnedeklerk
requested review from
GilOliveira,
bianchini88 and
floradanna
as code owners
bianchini88
requested changes
Mar 12, 2026
Author
|
@bianchini88 Hi, hopefully I have understood what you have commented. |
Member
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@Arnedeklerk Please check wether all mentioned tools are in the tools and resources list, for example: |
Author
Member
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@Arnedeklerk thanks a lot for these suggestions, lets bring all changes for this in one branch/pull request. This will be needed for the GitHub Actions and will also improve reviewing (see also my comment in the other PR) |
Added new entries for AgriSchemas and updated descriptions for existing tools.
Author
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@bedroesb Hi, strange that those counted as duplicate entries, no? Maybe they were meant to be in a different order or something? |
Member
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@Arnedeklerk I agree that this was strange, they were already present on master: https://github.com/elixir-europe/rdmkit/pull/1814/changes but that should not affect the branch here 🤔 |
GilOliveira
approved these changes
Mar 16, 2026
Member
|
@NielsGeudens Tagging you to also have a look at this. |
Improved entry for MIAPPE
bianchini88
reviewed
Mar 18, 2026
| fairsharing: 1943d4 | ||
| tess: CSV | ||
| url: https://tools.ietf.org/html/rfc4180 | ||
| - description: Extends schema.org and Bioschemas to provide a pragmatic, "farm-to-fork" pathway for the automatic integration of large, semi-structured datasets in exploratory research. |
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Suggested change
| - description: Extends schema.org and Bioschemas to provide a pragmatic, "farm-to-fork" pathway for the automatic integration of large, semi-structured datasets in exploratory research. | |
| - description: Extends Schema.org and Bioschemas to provide a pragmatic, "farm-to-fork" pathway for the automatic integration of large, semi-structured datasets in exploratory research. |
| The following practices help improve interoperability and reuse of agro-ecology datasets across disciplines and infrastructures: | ||
| * Adopt community metadata standards where possible, selecting those that best match your data types and community expectations. For example, guidance on recommended standards and how they map to common agroecology data types is collected via the [AgroServ FAIRSharing collection](https://doi.org/10.25504/FAIRsharing.f397c2), which links out to discipline- and technology-specific best practices. | ||
| * Use {% tool "agrischemas" %} to implement a lightweight, low-formal schematisation approach. Unlike complex OWL-based ontologies, AgriSchemas extends {% tool "schema-org" %} and {% tool "bioschemas" %} to provide a pragmatic "farm-to-fork" pathway for sharing large, semi-structured datasets. | ||
| * Leverage the successful mapping of {% tool "miappe" %} (Minimum Information About a Plant Phenotyping Experiment) to AgriSchemas. This allows researchers to bridge the gap between genomic data and phenotypic observations, such as investigating gene function based on expression measured in field trials. |
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Suggested change
| * Leverage the successful mapping of {% tool "miappe" %} (Minimum Information About a Plant Phenotyping Experiment) to AgriSchemas. This allows researchers to bridge the gap between genomic data and phenotypic observations, such as investigating gene function based on expression measured in field trials. | |
| * Leverage the successful mapping of {% tool "miappe" %} to AgriSchemas. This allows researchers to bridge the gap between genomic data and phenotypic observations, such as investigating gene function based on expression measured in field trials. |
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Added AgriSchemas solutions for lightweight data schematisation.
Included MIAPPE-to-AgriSchemas mapping and FAIRAgro soil variable context.
Added KnetMiner SPARQL endpoints and AI integration considerations.
Updated tool links and updated contributor metadata.
Please review!