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authorMunyoki Kilyungi2023-08-29 13:27:42 +0300
committerMunyoki Kilyungi2023-08-29 13:27:42 +0300
commite16bc2a302bf950dfdce76d8c10447b68aca5564 (patch)
treedf841e77af144e946446c854b4347d052fe02c40
parent6dd80b077cc2aeb84d9ecd4ae48186bf5a88f276 (diff)
downloadgn-gemtext-e16bc2a302bf950dfdce76d8c10447b68aca5564.tar.gz
Fix minor issues in document
Signed-off-by: Munyoki Kilyungi <me@bonfacemunyoki.com>
-rw-r--r--topics/next-gen-databases/gn-classification-scheme.gmi8
1 files changed, 4 insertions, 4 deletions
diff --git a/topics/next-gen-databases/gn-classification-scheme.gmi b/topics/next-gen-databases/gn-classification-scheme.gmi
index 2d66f3c..e65de04 100644
--- a/topics/next-gen-databases/gn-classification-scheme.gmi
+++ b/topics/next-gen-databases/gn-classification-scheme.gmi
@@ -4,13 +4,13 @@ In GeneNetwork (GN), data is grouped into specific discrete categories. Let's d
* Species: This category groups data based on different species, like humans, mice, or plants.
* Set/Group (InbredSet): This groups data according to a group of genetically similar organisms.
-* DatasetType: This classified data according to it's type. There are three main types: Genotypes (genetic makeup), Molecular Traits (molecular characteristics), and Phenotypes (observable traits).
+* DatasetType: This classifies data according to it's type. There are three main types: Genotypes, Molecular Traits, and Phenotypes.
The aforementioned classification scheme is inspired by GN's menu structure which forms the skeleton of the proposed classification. You can query metadata about this classification: "gn:ResourceClassificationScheme". This classification scheme has 3 levels:
* gnc:DatasetType
* gnc:Set
-* gn:Species.
+* gn:Species
Here's a depper look at each level:
@@ -18,7 +18,7 @@ Here's a depper look at each level:
* gnc:Set: This level includes all the members listed in the InbredSet table.
* gn:Species: This level consists of all the members from the Species table.
-The beauty of this system is that most of the resources in GN can be accurately categorized using it. Instead of using specific properties like "gnt:belongsToSpecies" or "gnt:belongsToSet," we can utilize the xkos⁰ approach. For instance, to classify a resource, we can use the concept of xkos and apply the relationship "xkos:classifiedUnder." Here's an example of a resource that has been classified:
+The beauty of this system is that most of the resources in GN can be accurately categorized using it. Instead of using specific properties like "gnt:belongsToSpecies" or "gnt:belongsToSet," we can utilize the xkos[0] approach. For instance, to classify a resource, we can use the concept of xkos and apply the relationship "xkos:classifiedUnder." Here's an example of a resource that has been classified:
```
gn:Gtexv8_sto_0220 xkos:classifiedUnder gnc:Probeset .
@@ -42,4 +42,4 @@ SELECT * WHERE {
}
```
-=> https://rdf-vocabulary.ddialliance.org/xkos.html ⁰ XKOS: An SKOS extension for representing statistical classifications.
+=> https://rdf-vocabulary.ddialliance.org/xkos.html [0] XKOS: An SKOS extension for representing statistical classifications.