Add column type mapping and enhance validation

Introduced a backend mapping for column expected types, improving validation and error handling. Updated UI to highlight default and corrected values, with additional detailed validation for data collection parameters.

backend/app/schemas.py

@@ -163,24 +163,19 @@ class DataCollectionParameters(BaseModel):
                 ) from e
         return v
 
-    @field_validator("oscillation", "targetresolution", mode="before")
+    @field_validator("oscillation", mode="before")
     @classmethod
     def positive_float_validator(cls, v):
-        logger.debug(f"Running positive_float_validator for value: {v}")
-        if v is not None:
-            try:
-                v = float(v)
-                if v <= 0:
-                    logger.error(f"Validation failed: '{v}' is not greater than 0.")
-                    raise ValueError(
-                        f"'{v}' is not valid. Value must be a positive float."
-                    )
-            except (ValueError, TypeError) as e:
-                logger.error(f"Validation failed: '{v}' caused error {str(e)}")
-                raise ValueError(
-                    f"'{v}' is not valid. Value must be a positive float."
-                ) from e
-        logger.debug(f"Validation succeeded for value: {v}")
+        if v is None:
+            return None
+        try:
+            v = float(v)
+            if v <= 0:
+                raise ValueError(f"'{v}' is not valid. Value must be a positive float.")
+        except (ValueError, TypeError) as e:
+            raise ValueError(
+                f"'{v}' is not valid. Value must be a positive float."
+            ) from e
         return v
 
     @field_validator("exposure", mode="before")