`cur_land_use` was an enum before LinkML

[mslarae13]

Something that I think was missed during the migration to LinkML

cur_land_use (https://genomicsstandardsconsortium.github.io/mixs/0001080/) has Range: [String](https://genomicsstandardsconsortium.github.io/mixs/String/)

However, it also has

string_serialization: '[cities|farmstead|industrial areas|roads/railroads|rock|sand|gravel|mudflats|salt flats|badlands|permanent snow or ice|saline seeps|mines/quarries|oil waste areas|small grains|row crops|vegetable crops|horticultural plants (e.g. tulips)|marshlands (grass,sedges,rushes)|tundra (mosses,lichens)|rangeland|pastureland (grasslands used for livestock grazing)|hayland|meadows (grasses,alfalfa,fescue,bromegrass,timothy)|shrub land (e.g. mesquite,sage-brush,creosote bush,shrub oak,eucalyptus)|successional shrub land (tree saplings,hazels,sumacs,chokecherry,shrub dogwoods,blackberries)|shrub crops (blueberries,nursery ornamentals,filberts)|vine crops (grapes)|conifers (e.g. pine,spruce,fir,cypress)|hardwoods (e.g. oak,hickory,elm,aspen)|intermixed hardwood and conifers|tropical (e.g. mangrove,palms)|rainforest (evergreen forest receiving >406 cm annual rainfall)|swamp (permanent or semi-permanent water body dominated by woody plants)|crop trees (nuts,fruit,christmas trees,nursery trees)]'

I suspect this should've been an enum. But an enum couldn't be made directly, as you should include examples in the enum permissible values

See NMDC's update: https://microbiomedata.github.io/nmdc-schema/CurLandUseEnum/

MIxS should also provide this enum, and provide the examples and information in () in an attribute of the enum.

FYI @turbomam

[mslarae13]

related to https://github.com/GenomicsStandardsConsortium/mixs/issues/905

https://github.com/GenomicsStandardsConsortium/mixs/issues/905#issuecomment-2821326758

[turbomam]

Yes, the dreaded string_serialization comes from the 'Value syntax' in https://github.com/GenomicsStandardsConsortium/mixs6.2_release_candidate/blob/main/GSC-excel-harmonized-repaired/mixs_v6.xlsx.harmonized.tsv

I agree that I should be an enumeration with examples and will work on that now

[turbomam]

See also

• #905
• #373
• #333

[turbomam]

PS the description isn't very good either

Present state of sample site

There are many states that a site could be in beyond the what in which the land is being used

[turbomam]

And is this supposed to be aligned with any other system?

• https://www.fao.org/geospatial/resources/detail/en/c/1024744/?utm_source=chatgpt.com
• https://land.copernicus.eu/content/corine-land-cover-nomenclature-guidelines/html/?utm_source=chatgpt.com
• https://land.copernicus.eu/en/products/corine-land-cover?utm_source=chatgpt.com
• https://www.fao.org/4/x0596e/x0596e01f.htm?utm_source=chatgpt.com
• https://www.fao.org/land-water/land/land-governance/land-resources-planning-toolbox/category/details/en/c/1036361/?utm_source=chatgpt.com
• https://www.nrcs.usda.gov/sites/default/files/2022-09/EQIP_Land_Eligibility_and_NPPH_Land_Use_Chart.pdf?utm_source=chatgpt.com
• https://www.nrcs.usda.gov/conservation-basics/natural-resource-concerns/land-use?utm_source=chatgpt.com

[turbomam]

Is this aligned with EnvO

[turbomam]

To what degree should MIxS capture the fact that https://en.wikipedia.org/wiki/Pinus_pinaster aka http://purl.obolibrary.org/obo/NCBITaxon_71647 is a "conifer" ? Is that word synonymous with https://en.wikipedia.org/wiki/Pinales? or https://en.wikipedia.org/wiki/Pinidae ?

See also https://en.wikipedia.org/wiki/Conifer

[turbomam]

table of frequently used values from INSDC Biosamples

ncbi_metadata.biosamples_attributes.cur_land_use.csv

[turbomam]

From ChatGPT

Comparison of INSDC/NCBI Biosample cur_land_use Values with Pipe-Separated List and LinkML Enumeration

Observations:

1. Direct Matches:

Some of the values in the INSDC biosample data are direct matches to categories from both the pipe-separated list and LinkML enumeration. Examples include:

• row crops, pastureland (grasslands used for livestock grazing), mines/quarries, sand, crop trees (nuts, fruit, christmas trees, nursery trees), conifers (e.g. pine, spruce, fir, cypress), and marshlands (grass, sedges, rushes).

2. Category Variations:

Some categories in the INSDC biosample data have slight variations in terminology but align with categories in the enumeration. Examples include:

• agriculture, agricultural, and crop which could be aligned with row crops, vegetable crops, or crop trees.
• grass/herbaceous cover and grassland could relate to meadows or pastureland.
• agricultural experiment and arable field might fit with row crops or small grains.

3. Unaccounted Values:

There are several land use categories in the biosample data that do not appear directly in either the pipe-separated list or the LinkML enumeration. These may represent specific or unique land uses. For example:

• abandoned grassland, arable cropland for long-term experimentation, no-till system, temperate coniferous forest, National Park, fertilized meadow, and unfertilized pasture grazed by cattle.

4. Overlapping Terms:

Some terms have overlapping meaning but differ slightly in phrasing:

• shrub land (e.g. mesquite, sage-brush, creosote bush, shrub oak, eucalyptus) and shrub crops (blueberries, nursery ornamentals, filberts) align with shrub land and shrub crops in the enumeration, though with additional specificity in the biosample data.

---

Summary of Key Comparisons:

High Match:

Terms like row crops, industrial areas, conifers, hardwoods, pastureland, marshlands, vine crops, and shrub land match directly or closely with both the pipe-separated list and LinkML enumeration.

Moderate Match:

Terms such as agriculture, agricultural, and crop are commonly found in the biosample data but appear more generally in the enumeration (e.g., under row crops, vegetable crops, crop trees).

Missing/Unique:

The biosample data contains specific land use terms not covered by either list (e.g., abandoned grassland, temperate coniferous forest, fertilized meadow, no-till system, National Park).

---

Suggestions:

To better align with the biosample data:

1. Extend the LinkML enumeration to include terms like agriculture, arable field, fertilized meadow, unfertilized pasture, and National Park that appear in the biosample counts.
2. Adjust terminology: Consider consolidating overlapping terms (e.g., grassland, grass/herbaceous cover, and meadows) to reduce ambiguity and improve consistency across data sources.
3. Handle variations: Allow for aliases or synonyms in the LinkML model to capture terms like agricultural experiment or temperate woodland that are used less commonly.