diff --git a/shared/mongodb/classes/__init__.py b/shared/mongodb/classes/__init__.py
index 129df79..af91d95 100755
--- a/shared/mongodb/classes/__init__.py
+++ b/shared/mongodb/classes/__init__.py
@@ -1,6 +1 @@
-"""Database classes module content."""
-
-from __future__ import annotations
-
-from .dataset import Dataset
 from .visual_communication import VisualCommunication
diff --git a/shared/mongodb/classes/dataset.py b/shared/mongodb/classes/dataset.py
deleted file mode 100755
index 633c533..0000000
--- a/shared/mongodb/classes/dataset.py
+++ /dev/null
@@ -1,67 +0,0 @@
-"""Definition of database Dataset class."""
-
-from __future__ import annotations
-
-import logging
-import random
-from datetime import UTC, datetime
-
-from pydantic import BaseModel, Field
-from pymongo.collection import Collection
-
-
-class Dataset(BaseModel):
-    """Database Dataset model."""
-
-    create_time: datetime = Field(default_factory=lambda: datetime.now(UTC))
-    train_names: list[str]
-    test_names: list[str]
-    validation_names: list[str]
-
-    @classmethod
-    def fraction_map(cls) -> dict[str, float]:
-        """Dict with train, test and validation fractions."""
-        # define map
-        split_map = {
-            'train': 0.7,
-            'test': 0.2,
-            'validation': 0.1,
-        }
-        # sanity check
-        assert sum(split_map.values()) == 1.0
-        return split_map
-
-    @classmethod
-    def new_from_name_list(
-        cls,
-        name_list: list[str],
-    ) -> Dataset:
-        """Generate new dataset from list of filenames."""
-        # calculate split fractions
-        fraction_map = cls.fraction_map()
-        num_total = len(name_list)
-        num_validation = round(num_total * fraction_map['validation'])
-        num_test = round(num_total * fraction_map['test'])
-        # split data
-        validation_name_list = random.choices(name_list, k=num_validation)
-        name_list = [name for name in name_list if name not in validation_name_list]
-        test_name_list = random.choices(name_list, k=num_test)
-        train_name_list = [name for name in name_list if name not in test_name_list]
-        # instantiate object
-        dataset = Dataset(
-            train_names=train_name_list,
-            test_names=test_name_list,
-            validation_names=validation_name_list,
-        )
-        logging.debug('finished')
-        return dataset
-
-    def save(
-        self,
-        collection: Collection,
-    ) -> None:
-        """Save dataset to database."""
-        res = collection.insert_one(
-            document=self.model_dump(),
-        )
-        logging.debug('inserted document: %s', res)