diff --git a/src/pie_datasets/core/__init__.py b/src/pie_datasets/core/__init__.py
index e81adf7b..22f4bd7a 100644
--- a/src/pie_datasets/core/__init__.py
+++ b/src/pie_datasets/core/__init__.py
@@ -1,5 +1,5 @@
 from .builder import ArrowBasedBuilder, GeneratorBasedBuilder
-from .dataset import Dataset, IterableDataset
+from .dataset import Dataset, IterableDataset, concatenate_datasets
 from .dataset_dict import DatasetDict, load_dataset
 
 __all__ = [
@@ -9,4 +9,5 @@
     "IterableDataset",
     "DatasetDict",
     "load_dataset",
+    "concatenate_datasets",
 ]
diff --git a/src/pie_datasets/core/dataset.py b/src/pie_datasets/core/dataset.py
index ca18f0b0..ccaa77b2 100644
--- a/src/pie_datasets/core/dataset.py
+++ b/src/pie_datasets/core/dataset.py
@@ -588,3 +588,52 @@ def get_pie_dataset_type(
         raise TypeError(
             f"the dataset must be of type Dataset or IterableDataset, but is of type {type(hf_dataset)}"
         )
+
+
+def _add_dset_name_to_document(doc: Document, name: str) -> Document:
+    if not hasattr(doc, "metadata"):
+        raise ValueError(
+            f"Document does not have metadata attribute which required to save the dataset name: {doc}"
+        )
+    if "dataset_name" in doc.metadata:
+        raise ValueError(
+            f"Document already has a dataset_name attribute: {doc.metadata['dataset']}"
+        )
+    doc.metadata["dataset_name"] = name
+    return doc
+
+
+def concatenate_datasets(
+    dsets: Union[
+        List[Dataset], List[IterableDataset], Dict[str, Dataset], Dict[str, IterableDataset]
+    ]
+) -> Union[Dataset, IterableDataset]:
+    """Concatenate multiple datasets into a single dataset.
+
+    The datasets must have the same
+    document type.
+    Args:
+        dsets: A list of datasets or a dictionary with dataset names as keys and datasets as values. If a dictionary is
+            provided, the dataset names will be added to the documents as metadata.
+    Returns:
+        A new dataset that is the concatenation of the input datasets.
+    """
+
+    if isinstance(dsets, dict):
+        dsets = [
+            dset.map(_add_dset_name_to_document, fn_kwargs={"name": name})
+            for name, dset in dsets.items()
+        ]
+
+    if len(dsets) == 0:
+        raise ValueError("No datasets to concatenate")
+
+    document_type = dsets[0].document_type
+    for doc in dsets[1:]:
+        if not doc.document_type == document_type:
+            raise ValueError("All datasets must have the same document type to concatenate")
+
+    result_hf = datasets.concatenate_datasets(dsets)
+    pie_dataset_type = get_pie_dataset_type(dsets[0])
+
+    return pie_dataset_type.from_hf_dataset(result_hf, document_type=document_type)