Merge origin/main into html branch

Resolved poetry.lock merge conflict by regenerating the lock file from pyproject.toml.
This brings the html branch up to date with the latest main branch changes including
the modules merge (PR #38).

Fixes conflicts in PR #42.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

Author: realmarcin

Makefile

@@ -11,6 +11,7 @@ RUN = poetry run
 SCHEMA_NAME = $(shell ${SHELL} ./utils/get-value.sh name)
 SOURCE_SCHEMA_PATH = $(shell ${SHELL} ./utils/get-value.sh source_schema_path)
 SOURCE_SCHEMA_DIR = $(dir $(SOURCE_SCHEMA_PATH))
+SOURCE_SCHEMA_ALL = $(SOURCE_SCHEMA_DIR)$(patsubst %.yaml,%_all.yaml,$(notdir $(SOURCE_SCHEMA_PATH)))
 SRC = src
 DEST = project
 PYMODEL = $(SRC)/$(SCHEMA_NAME)/datamodel
@@ -101,15 +102,27 @@ compile-sheets:
 gen-examples:
 	cp src/data/examples/* $(EXAMPLEDIR)
 
+# Build the combined schema
+# Also write proper yaml header to it
+.PHONY: full-schema
+full-schema: $(SOURCE_SCHEMA_ALL)
+
+$(SOURCE_SCHEMA_ALL):
+	@echo "Generating D4D-Full schema with merged imports..."
+	$(RUN) gen-linkml -o $@ -f 'yaml' $(SOURCE_SCHEMA_PATH)
+	@echo '---' | cat - $@ > $@.tmp && mv $@.tmp $@
+
 # generates all project files
 
-gen-project: $(PYMODEL)
+gen-project: $(PYMODEL) $(SOURCE_SCHEMA_ALL)
 	$(RUN) gen-project -I python -I jsonschema -I jsonld -I owl ${GEN_PARGS} -d $(DEST) $(SOURCE_SCHEMA_PATH) && mv $(DEST)/*.py $(PYMODEL)
 
+
 test: test-schema test-python test-examples
 
-test-schema:
-	$(RUN) gen-project ${GEN_PARGS} -d tmp $(SOURCE_SCHEMA_PATH)
+# Test the schema - use the full materialized version
+test-schema: $(SOURCE_SCHEMA_ALL)
+	$(RUN) gen-project ${GEN_PARGS} -d tmp $(SOURCE_SCHEMA_ALL)
 
 test-python:
 	$(RUN) python -m unittest discover

README.md

@@ -1,3 +1,5 @@
+Executive Order 14168: This repository is under review for potential modification in compliance with Administration directives.
+
 # data-sheets-schema
 
 A LinkML schema for Datasheets for Datasets model as published in [Datasheets for Datasets](https://m-cacm.acm.org/magazines/2021/12/256932-datasheets-for-datasets/fulltext). Inspired by datasheets as used in the electronics and other industries, Gebru et al. proposed that every dataset "be accompanied with a datasheet that documents its motivation, composition, collection process, recommended uses, and so on". To this end the authors create a series of topics and over 50 questions addressing different aspects of datasets, also useful in an AI/ML context. An example of completed datasheet for datasets can be found here: