add handing of subtitle

project/dalia/query/items/metadata/one_to_one_metadata.py

@@ -6,12 +6,13 @@ from project.dalia.api_models.api_models import License, Resource
 from project.dalia.query.items.metadata.license import get_license_info
 from project.dalia.query.utils import query_dalia_dataset
 from project.dalia.query_builder.query_builder import FILTER, FunctionExpressions, OPTIONAL, QueryBuilder, VALUES
-from project.dalia.rdf.namespace import MoDalia, SCHEMA, content_inventory, educor
+from project.dalia.rdf.namespace import MoDalia, SCHEMA, content_inventory, educor, fabio
 
 _VARIABLES = {
     "lr": Variable("lr"),
     "description": Variable("description"),
     "title": Variable("title"),
+    "subtitle": Variable("subtitle"),
     "created": Variable("created"),
     "license": Variable("license"),
     "fileSize": Variable("fileSize"),
@@ -37,6 +38,7 @@ def prepare_query_for_one_to_one_metadata_for_resources(resource_uri_refs: List[
         (var_lr, RDF.type, educor.EducationalResource),
         OPTIONAL((var_lr, DCTERMS.description, _VARIABLES["description"])),
         OPTIONAL((var_lr, DCTERMS.title, _VARIABLES["title"])),
+        OPTIONAL((var_lr, fabio.hasSubtitle, _VARIABLES["subtitle"])),
         OPTIONAL((var_lr, SCHEMA.datePublished, _VARIABLES["created"])),
         OPTIONAL((var_lr, DCTERMS.license, _VARIABLES["license"])),
         OPTIONAL((var_lr, SCHEMA.fileSize, _VARIABLES["fileSize"])),
@@ -56,7 +58,7 @@ def process_result_for_one_to_one_metadata_for_resources(result) -> Resource:
 
     resource.id = str(result.lr).split("/")[-1]
     resource.slug = str(result.slug)
-    resource.title = str(result.title)
+    resource.title = str(result.title) if not result.subtitle else str(result.title) + ": " + str(result.subtitle)
     resource.description = str(result.description) if result.description else ""
     resource.url = str(result.url)
     resource.license = get_license_info(result.license) if result.license else License(id="", name="", link="")

project/dalia/rdf/namespace/fabio.py

+"""
+Terms from FaBiO, the FRBR-aligned Bibliographic Ontology
+"""
+from rdflib import URIRef
+
+NS = "http://purl.org/spar/fabio/"
+
+# Properties
+hasSubtitle = URIRef(NS + "hasSubtitle")  # https://sparontologies.github.io/fabio/current/fabio.html#d4e1689

tests/project/dalia/query/items/metadata/test_one_to_one_metadata.py

@@ -13,7 +13,7 @@ def test_prepare_query_for_one_to_one_metadata_for_resources():
     query = prepare_query_for_one_to_one_metadata_for_resources([URIRef("abc"), URIRef("def")])
 
     assert normalize(query) == dedent_and_normalize("""
-        SELECT ?lr ?description ?title ?created ?license ?fileSize ?url ?slug ?attachment  
+        SELECT ?lr ?description ?title ?subtitle ?created ?license ?fileSize ?url ?slug ?attachment  
         WHERE { 
         VALUES ( ?lr ) { 
         ( <abc> )
@@ -27,6 +27,9 @@ def test_prepare_query_for_one_to_one_metadata_for_resources():
         ?lr <http://purl.org/dc/terms/title> ?title .
         } . 
         OPTIONAL { 
+        ?lr <http://purl.org/spar/fabio/hasSubtitle> ?subtitle .
+        } . 
+        OPTIONAL { 
         ?lr <https://schema.org/datePublished> ?created .
         } . 
         OPTIONAL { 
@@ -55,6 +58,7 @@ def test_process_result_for_one_to_one_metadata_for_resources_with_minimal_resul
     result.lr = "http://some.domain/a/cool/id/is/42"
     result.slug = "my-slug"
     result.title = "My Title"
+    result.subtitle = None
     result.description = None
     result.url = "http://localhost/secret-document"
     result.license = None
@@ -95,6 +99,7 @@ def test_get_one_to_one_metadata_for_resources(triplestore):
     resources = get_one_to_one_metadata_for_resources([
         URIRef("https://id.dalia.education/learning-resource/00855e6b-ebc6-422b-a2d5-7caa58569a9b"),
         URIRef("https://id.dalia.education/learning-resource/a195da8d-b19e-4934-9511-9369e60ccaa1"),
+        URIRef("https://id.dalia.education/learning-resource/65ae2d0f-7d94-4f0b-9714-470a2c372839"),
         URIRef("http://does-not-exist/123"),
     ])
 
@@ -162,6 +167,57 @@ def test_get_one_to_one_metadata_for_resources(triplestore):
             views=None,
             comments=None,
             tags=None
+        ),
+        URIRef('https://id.dalia.education/learning-resource/65ae2d0f-7d94-4f0b-9714-470a2c372839'): Resource(
+            type=None,
+            format=None,
+            license=License(
+                id='Proprietary',
+                name='Proprietary',
+                link=''
+            ),
+            publication_date=None,
+            links=None,
+            languages=None,
+            file_size=None,
+            publisher=None,
+            doi=None,
+            learning_time=None,
+            versions=None,
+            id='65ae2d0f-7d94-4f0b-9714-470a2c372839',
+            slug='None',
+            title='WageningenX: Big Data for Agri-Food: Principles and Tools',
+            communities=None,
+            description="During this course, you will understand how and why certain principles – such as "
+                        "immutability and pure functions – enable parallel data processing (‘divide and conquer’), "
+                        "which is necessary to manage big data. From this fundamental principle, we move forward. "
+                        "Namely, how to recognize and put into practice the scalable solution that’s right for your "
+                        "situation. The insights and tools of this course are regardless of programming language, "
+                        "but user-friendly examples are provided in Python, Hadoop HDFS, and Apache Spark. Although "
+                        "these principles can also be applied to other sectors, we will use examples from the "
+                        "agri-food sector.\n\nAgri-food deserves special focus when it comes to choosing robust data "
+                        "management technologies due to its inherent variability and uncertainty. Wageningen "
+                        "University & Research’s knowledge domain is healthy food and the living environment. That "
+                        "makes our data experts especially equipped to forge the bridge between the agri-food "
+                        "business on the one hand, and data science, artificial intelligence (AI) on the other. "
+                        "\nCombining data from the latest sensing technologies with machine learning/deep learning "
+                        "methodologies, allows us to unlock insights we didn't have access to before. In the areas of "
+                        "smart farming and precision agriculture, this allows us to:\nBetter manage dairy cattle by "
+                        "combining animal-level data on behaviour, health and feed with milk production and "
+                        "composition from milking machines. Reduce the amount of fertilizers (nitrogen), pesticides ("
+                        "chemicals), and water used on crops by monitoring individual plants with a robot or drone. "
+                        "More accurately predict crop yields on a continental scale by combining current with "
+                        "historic data on soil, weather patterns and crop yields.\nIn short, this course’s "
+                        "foundational knowledge and skills for big data prepare you for the next step: to find more "
+                        "effective and scalable solutions for smarter, innovative insights.",
+            authors=None,
+            url='https://www.edx.org/learn/big-data/wageningen-university-research-big-data-for-agri-food-principles'
+                '-and-tools?',
+            image=None,
+            likes=None,
+            views=None,
+            comments=None,
+            tags=None,
         )
     }