Convert a .csv table to a SALAD schema
A .csv file with the field headers: field_name, doc, type, iri
Eg:
| field_name | doc | type | iri |
|---|---|---|---|
| sample_name | The user-defined name for the sample. | string | http://edamontology.org/data_3273 |
| collection_date | The date on which the sample was collected. | string | http://purl.obolibrary.org/obo/NCIT_C81286 |
(Note that SALAD has a limited set of primitive types available to choose from.)
A context.json file with prefixes for any IRIs used in your table:
{
"edam_data": "http://edamontology.org/data_",
"ncit": "http://purl.obolibrary.org/obo/NCIT_"
}(optionally) a name for your schema class (defaults to SchemaClass if not provided.
table_salad_schema_gen.py --input schema_table.csv --context context.json --name SampleSchema
$namespaces:
ncit: http://purl.obolibrary.org/obo/NCIT_
edam_data: http://edamontology.org/data_
$graph:
- fields:
collection_date:
doc: The date on which the sample was collected.
jsonldPredicate:
_id: ncit:C81286
type: date
sample_name:
doc: The user-defined name for the sample.
jsonldPredicate:
_id: edam_data:3273
type: string
type: record
name: SampleSchema
documentRoot: 'true'table_salad_validate.py
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent