diff --git a/djangomain/settings/settings.py b/djangomain/settings/settings.py
index fcc75774..abd34119 100644
--- a/djangomain/settings/settings.py
+++ b/djangomain/settings/settings.py
@@ -287,3 +287,6 @@
         crossorigin="anonymous",
     )
 )
+
+
+DATA_UPLOAD_MAX_NUMBER_FIELDS = None
diff --git a/importing/functions.py b/importing/functions.py
index 10806d0a..bf143439 100755
--- a/importing/functions.py
+++ b/importing/functions.py
@@ -23,7 +23,8 @@
 from django.db.models import FileField
 
 from formatting.models import Classification, Format
-from measurement.models import Measurement
+from importing.models import DataImport
+from measurement.models import Measurement, Report
 from station.models import Station
 
 unix_epoch = np.datetime64(0, "s")
@@ -262,7 +263,7 @@ def standardise_datetime(date_time: Any, datetime_format: str) -> datetime:
 
 
 def save_temp_data_to_permanent(
-    station: Station, file_format: Format, file: FileField
+    data_import: DataImport,
 ) -> tuple[datetime, datetime, int]:
     """Function to pass the temporary import to the final table.
 
@@ -278,14 +279,21 @@ def save_temp_data_to_permanent(
     Args:
         data_import_temp: DataImportTemp object.
     """
+    station = data_import.station
+    file_format = data_import.format
+    file = data_import.rawfile
+
+    # Delete exiting measurements and reports for the same data_import_id
+    Measurement.objects.filter(data_import_id=data_import.data_import_id).delete()
+    Report.objects.filter(data_import_id=data_import.data_import_id).delete()
 
-    all_data = construct_matrix(file, file_format, station)
+    all_data = construct_matrix(file, file_format, station, data_import)
     if not all_data:
         msg = "No data to import. Is the chosen format correct?"
         getLogger().error(msg)
         raise ValidationError(msg)
 
-    must_cols = ["station_id", "variable_id", "date", "value"]
+    must_cols = ["data_import_id", "station_id", "variable_id", "date", "value"]
     start_date = all_data[0]["date"].iloc[0]
     end_date = all_data[0]["date"].iloc[-1]
     num_records = len(all_data[0])
@@ -301,12 +309,18 @@ def save_temp_data_to_permanent(
         records = table.to_dict("records")
         variable_id = table["variable_id"].iloc[0]
 
-        # Delete existing data between the date ranges
+        # Delete existing data between the date ranges. Needed for data not linked
+        # to a data_import_id. Both measurements and reports are deleted.
         Measurement.timescale.filter(
             time__range=[start_date, end_date],
             station_id=station.station_id,
             variable_id=variable_id,
         ).delete()
+        Report.objects.filter(
+            time__range=[start_date, end_date],
+            station_id=station.station_id,
+            variable_id=variable_id,
+        ).delete()
 
         # Bulk add new data
         model_instances = [Measurement(**record) for record in records]
@@ -321,7 +335,12 @@ def save_temp_data_to_permanent(
     return start_date, end_date, num_records
 
 
-def construct_matrix(matrix_source, file_format, station) -> list[pd.DataFrame]:
+def construct_matrix(
+    matrix_source: FileField,
+    file_format: Format,
+    station: Station,
+    data_import: DataImport,
+) -> list[pd.DataFrame]:
     """Construct the "matrix" or results table. Does various cleaning / simple
     transformations depending on the date format, type of data (accumulated,
     incremental...) and deals with NANs.
@@ -443,6 +462,7 @@ def construct_matrix(matrix_source, file_format, station) -> list[pd.DataFrame]:
                 data["value"] = data["value"] * float(classification.resolution)
         data["station_id"] = station.station_id
         data["variable_id"] = classification.variable.variable_id
+        data["data_import_id"] = data_import.data_import_id
 
         # Add the data to the main list
         to_ingest.append(data)
diff --git a/importing/tasks.py b/importing/tasks.py
index 809d523f..bfcbb237 100644
--- a/importing/tasks.py
+++ b/importing/tasks.py
@@ -24,9 +24,7 @@ def ingest_data(data_import_pk: int) -> None:
     try:
         getLogger("huey").info("Ingesting data for %s", data_import)
         data_import.start_date, data_import.end_date, data_import.records = (
-            save_temp_data_to_permanent(
-                data_import.station, data_import.format, data_import.rawfile
-            )
+            save_temp_data_to_permanent(data_import)
         )
         data_import.status = "C"
         data_import.log = "Data ingestion completed successfully"
diff --git a/measurement/migrations/0015_measurement_data_import_report_data_import.py b/measurement/migrations/0015_measurement_data_import_report_data_import.py
new file mode 100644
index 00000000..51741a13
--- /dev/null
+++ b/measurement/migrations/0015_measurement_data_import_report_data_import.py
@@ -0,0 +1,25 @@
+# Generated by Django 5.1.1 on 2024-10-08 12:51
+
+import django.db.models.deletion
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('importing', '0006_alter_dataimport_data_import_id_and_more'),
+        ('measurement', '0014_alter_report_completeness'),
+    ]
+
+    operations = [
+        migrations.AddField(
+            model_name='measurement',
+            name='data_import',
+            field=models.ForeignKey(blank=True, help_text='Data import this measurement belongs to.', null=True, on_delete=django.db.models.deletion.CASCADE, to='importing.dataimport'),
+        ),
+        migrations.AddField(
+            model_name='report',
+            name='data_import',
+            field=models.ForeignKey(blank=True, help_text='Data import this measurement belongs to.', null=True, on_delete=django.db.models.deletion.CASCADE, to='importing.dataimport'),
+        ),
+    ]
diff --git a/measurement/models.py b/measurement/models.py
index 0853d43d..7f499182 100755
--- a/measurement/models.py
+++ b/measurement/models.py
@@ -17,6 +17,7 @@
 from django.db import models
 from timescale.db.models.models import TimescaleDateTimeField, TimescaleModel
 
+from importing.models import DataImport
 from management.models import apply_add_permissions_to_standard_group
 from station.models import Station
 from variable.models import Variable
@@ -46,6 +47,13 @@ class MeasurementBase(TimescaleModel):
 
     time: TimescaleDateTimeField
 
+    data_import = models.ForeignKey(
+        DataImport,
+        on_delete=models.CASCADE,
+        null=True,
+        blank=True,
+        help_text="Data import this measurement belongs to.",
+    )
     station = models.ForeignKey(
         Station,
         on_delete=models.PROTECT,
diff --git a/measurement/reporting.py b/measurement/reporting.py
index d2bb5a69..9cfd0b42 100644
--- a/measurement/reporting.py
+++ b/measurement/reporting.py
@@ -3,6 +3,7 @@
 
 import pandas as pd
 
+from importing.models import DataImport
 from measurement.models import Measurement, Report
 from station.models import Station
 from variable.models import Variable
@@ -34,6 +35,17 @@ def calculate_reports(
     daily = hourly.resample("D").agg(operation)
     monthly = daily.resample("MS").agg(operation)
 
+    # Get the right data_import for each period. We use the mode to get the most common
+    # data_import value in the period.
+    def mode(x: pd.Series) -> str | None:
+        modes = x.mode()
+        return modes[0] if not modes.empty else None
+
+    cols2 = ["time", "data_import_id"]
+    hourly["data_import_id"] = data[cols2].resample("H", on="time").agg(mode)
+    daily["data_import_id"] = data[cols2].resample("D", on="time").agg(mode)
+    monthly["data_import_id"] = data[cols2].resample("MS", on="time").agg(mode)
+
     # Put everything together
     hourly["report_type"] = "hourly"
     daily["report_type"] = "daily"
@@ -145,9 +157,13 @@ def save_report_data(data: pd.DataFrame) -> None:
         data: The dataframe with the report data.
     """
     data_ = data.dropna(axis=1, how="all").dropna(axis=0, subset=["value"])
+    data_import_avail = "data_import_id" in data_.columns
     Report.objects.bulk_create(
         [
             Report(
+                data_import=DataImport.objects.get(pk=row["data_import_id"])
+                if data_import_avail and not pd.isna(row["data_import_id"])
+                else None,
                 station=Station.objects.get(station_code=row["station"]),
                 variable=Variable.objects.get(variable_code=row["variable"]),
                 time=time,
diff --git a/tests/importing/test_functions.py b/tests/importing/test_functions.py
index ee1ed226..9abcaef9 100755
--- a/tests/importing/test_functions.py
+++ b/tests/importing/test_functions.py
@@ -29,6 +29,7 @@ class TestMatrixFunctions(TestCase):
 
     def setUp(self):
         from formatting.models import Format
+        from importing.models import DataImport
         from station.models import TIMEZONES, Station
 
         self.file_format = Format.objects.get(format_id=45)
@@ -37,6 +38,12 @@ def setUp(self):
         )
         self.station = Station.objects.get(station_id=8)
         self.station.timezone = TIMEZONES[0][0]
+        self.data_import = DataImport.objects.create(
+            owner=self.station.owner,
+            station=self.station,
+            format=self.file_format,
+            rawfile=self.data_file,
+        )
 
     def test_preformat_matrix(self):
         from importing.functions import read_data_to_import
@@ -51,7 +58,7 @@ def test_construct_matrix(self):
         from variable.models import Variable
 
         variables_data = construct_matrix(
-            self.data_file, self.file_format, self.station
+            self.data_file, self.file_format, self.station, self.data_import
         )
         self.assertEqual(len(variables_data), 2)
         vars = list(
diff --git a/tests/measurement/test_reporting.py b/tests/measurement/test_reporting.py
index 98945b9a..eed50bec 100644
--- a/tests/measurement/test_reporting.py
+++ b/tests/measurement/test_reporting.py
@@ -26,6 +26,7 @@ def test_calculate_reports(self):
         data = pd.DataFrame(
             {
                 "time": time,
+                "data_import_id": None,
                 "value": np.linspace(1, 5, len(time)),
                 "maximum": np.linspace(1, 5, len(time)) + 1,
                 "minimum": np.linspace(1, 5, len(time)) - 1,
@@ -53,6 +54,7 @@ def test_calculate_reports(self):
                 "value",
                 "maximum",
                 "minimum",
+                "data_import_id",
                 "report_type",
                 "station",
                 "variable",
@@ -181,6 +183,7 @@ def test_save_report_data(self):
             {
                 "station": [self.station.station_code],
                 "variable": [self.variable.variable_code],
+                "data_import_id": [None],
                 "time": time,
                 "value": [1.0],
                 "report_type": ["hourly"],
@@ -259,6 +262,7 @@ def test_get_report_data(self):
             [
                 "id",
                 "time",
+                "data_import_id",
                 "station",
                 "variable",
                 "value",