super

academic_observatory_workflows/workflows/orcid_telescope.py

@@ -37,7 +37,7 @@
 from google.cloud.bigquery import SourceFormat
 
 
-from academic_observatory_workflows.config import schema_folder as default_schema_folder
+from academic_observatory_workflows.config import schema_folder as default_schema_folder, Tag
 from observatory.api.client.model.dataset_release import DatasetRelease
 from observatory.platform.airflow import PreviousDagRunSensor, is_first_dag_run
 from observatory.platform.api import get_dataset_releases, get_latest_dataset_release
@@ -162,12 +162,20 @@ def __init__(
         aws_orcid_conn_id: str = "aws_orcid",
         start_date: pendulum.DateTime = pendulum.datetime(2023, 6, 1),
         schedule_interval: str = "@weekly",
-        queue: str = "remote_queue",
-        catchup: bool = False,
+        queue: str = "default",  # TODO: remote_queue
     ):
         """Construct an ORCID telescope instance"""
 
-        self.dag_id = dag_id
+        super().__init__(
+            dag_id=dag_id,
+            start_date=start_date,
+            schedule_interval=schedule_interval,
+            catchup=False,
+            airflow_conns=[observatory_api_conn_id, aws_orcid_conn_id],
+            tags=[Tag.academic_observatory],
+            queue=queue,
+        )
+
         self.cloud_workspace = cloud_workspace
         self.orcid_bucket = orcid_bucket
         self.orcid_summaries_prefix = orcid_summaries_prefix
@@ -184,10 +192,6 @@ def __init__(
         self.max_workers = max_workers
         self.observatory_api_conn_id = observatory_api_conn_id
         self.aws_orcid_conn_id = aws_orcid_conn_id
-        self.start_date = start_date
-        self.schedule_interval = schedule_interval
-        self.queue = queue
-        self.catchup = catchup
 
         external_task_id = "dag_run_complete"
         self.add_operator(