diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 2a39f5b..6c9cfca 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -39,12 +39,12 @@ repos:
     -   id: yamllint
         exclude: pre-commit-config.yaml
 -   repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: "v0.14.8"
+    rev: "v0.14.10"
     hooks:
     -   id: ruff-format
     -   id: ruff-check
 -   repo: https://github.com/rhysd/actionlint
-    rev: v1.7.9
+    rev: v1.7.10
     hooks:
     -   id: actionlint
 -   repo: https://gitlab.com/vojko.pribudic.foss/pre-commit-update
diff --git a/CITATION.cff b/CITATION.cff
index 147b9da..daea164 100644
--- a/CITATION.cff
+++ b/CITATION.cff
@@ -129,3 +129,29 @@ references:
       JUMP (cpg0000-jump-pilot) was used to help demonstrate CytoDataFrame performance
       with large data. See here for more information:
       https://github.com/broadinstitute/cellpainting-gallery
+  - type: article
+    authors:
+      - family-names: Blin
+        given-names: Guillaume
+      - family-names: Sadurska
+        given-names: Dominika
+      - family-names: Portero Migueles
+        given-names: Rafael
+      - family-names: Chen
+        given-names: Ni
+      - family-names: Watson
+        given-names: James A.
+      - family-names: Lowell
+        given-names: Sally
+    title: "Nessys: A new set of tools for the automated detection of nuclei within intact tissues and dense 3D cultures"
+    journal: PLoS Biology
+    volume: "17"
+    issue: "8"
+    pages: e3000388
+    year: 2019
+    doi: "10.1371/journal.pbio.3000388"
+    url: "https://doi.org/10.1371/journal.pbio.3000388"
+    notes: >
+      This work used the file "6001240_labels.zarr" from the DISCEPTS imaging
+      dataset, available through the Image Data Resource (IDR) under accession
+      number idr0062.
diff --git a/docs/src/examples/learning_to_fly_with_ome-arrow.ipynb b/docs/src/examples/learning_to_fly_with_ome-arrow.ipynb
index 2dce2d3..f1ff777 100644
--- a/docs/src/examples/learning_to_fly_with_ome-arrow.ipynb
+++ b/docs/src/examples/learning_to_fly_with_ome-arrow.ipynb
@@ -34,7 +34,7 @@
        "2D image, single-channel - shape (T=1, C=1, Z=1, Y=512, X=512)"
       ],
       "text/plain": [
-       "<ome_arrow.core.OMEArrow at 0x176418210>"
+       "<ome_arrow.core.OMEArrow at 0x13a0b4e50>"
       ]
      },
      "execution_count": 2,
@@ -129,7 +129,7 @@
        "3D image (z-stack), multi-channel (2 channels) - shape (T=1, C=2, Z=22, Y=128, X=128)"
       ],
       "text/plain": [
-       "<ome_arrow.core.OMEArrow at 0x17be69110>"
+       "<ome_arrow.core.OMEArrow at 0x1769ec4d0>"
       ]
      },
      "execution_count": 5,
@@ -160,19 +160,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "id": "383e1f10-b32f-47cb-9906-15dd9947b09a",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "e438f2316a4b4348b00283242d346c63",
+       "model_id": "ee038f8ceae842e5b6190bcf038c1318",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "Widget(value='<iframe src=\"http://localhost:63799/index.html?ui=P_0x17bdef790_0&reconnect=auto\" class=\"pyvista…"
+       "Widget(value='<iframe src=\"http://localhost:55663/index.html?ui=P_0x176969190_0&reconnect=auto\" class=\"pyvista…"
       ]
      },
      "metadata": {},
@@ -198,7 +198,7 @@
     {
      "data": {
       "text/plain": [
-       "<pyvista.plotting.plotter.Plotter at 0x17bdef790>"
+       "<pyvista.plotting.plotter.Plotter at 0x176969190>"
       ]
      },
      "execution_count": 6,
@@ -208,7 +208,10 @@
    ],
    "source": [
     "# we can visualize the stack using pyvista for 3D rendering\n",
-    "stack.view(how=\"pyvista\")"
+    "# note: we use manually specified scaling values here\n",
+    "# and can also default to what the image metadata provides\n",
+    "# with `scaling_values=None` (the default).\n",
+    "stack.view(how=\"pyvista\", scaling_values=(1, 0.1, 0.1))"
    ]
   },
   {
@@ -223,7 +226,7 @@
        "3D image (z-stack), multi-channel (2 channels) - shape (T=1, C=2, Z=22, Y=128, X=128)"
       ],
       "text/plain": [
-       "<ome_arrow.core.OMEArrow at 0x1059985d0>"
+       "<ome_arrow.core.OMEArrow at 0x176975c90>"
       ]
      },
      "execution_count": 7,
@@ -261,7 +264,7 @@
        "3D image (z-stack), multi-channel (2 channels) - shape (T=1, C=2, Z=22, Y=128, X=128)"
       ],
       "text/plain": [
-       "<ome_arrow.core.OMEArrow at 0x17f463c90>"
+       "<ome_arrow.core.OMEArrow at 0x1769edf10>"
       ]
      },
      "execution_count": 8,
@@ -299,7 +302,7 @@
        "3D image (z-stack), multi-channel (2 channels) - shape (T=1, C=2, Z=22, Y=128, X=128)"
       ],
       "text/plain": [
-       "<ome_arrow.core.OMEArrow at 0x17f434490>"
+       "<ome_arrow.core.OMEArrow at 0x177425050>"
       ]
      },
      "execution_count": 9,
@@ -337,7 +340,7 @@
        "3D image (z-stack), multi-channel (2 channels) - shape (T=1, C=2, Z=22, Y=128, X=128)"
       ],
       "text/plain": [
-       "<ome_arrow.core.OMEArrow at 0x17bf44390>"
+       "<ome_arrow.core.OMEArrow at 0x17f865210>"
       ]
      },
      "execution_count": 10,
@@ -375,7 +378,7 @@
        "2D image, single-channel - shape (T=1, C=1, Z=1, Y=30, X=30)"
       ],
       "text/plain": [
-       "<ome_arrow.core.OMEArrow at 0x35ff46510>"
+       "<ome_arrow.core.OMEArrow at 0x361f2e390>"
       ]
      },
      "execution_count": 11,
@@ -408,7 +411,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "id": "eddf849a",
    "metadata": {},
    "outputs": [
@@ -418,7 +421,7 @@
        "2D image, single-channel - shape (T=1, C=1, Z=1, Y=73, X=97)"
       ],
       "text/plain": [
-       "<ome_arrow.core.OMEArrow at 0x35ff67e10>"
+       "<ome_arrow.core.OMEArrow at 0x35e57e5d0>"
       ]
      },
      "execution_count": 12,
@@ -452,6 +455,61 @@
     "# by default, the image and metadata are shown\n",
     "oa_image"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "83e92796",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "b56ade44cbaa43b78d356f4d123574f1",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Widget(value='<iframe src=\"http://localhost:55663/index.html?ui=P_0x17f96e490_2&reconnect=auto\" class=\"pyvista…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "                        <details>\n",
+       "                        <summary>Static snapshot (for non-interactive view)</summary>\n",
+       "                        <img 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\" />\n",
+       "                        </details>\n",
+       "                        "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<pyvista.plotting.plotter.Plotter at 0x17f96e490>"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# read a 3d zarr image from IDR\n",
+    "oa_image = OMEArrow(data=\"../../../tests/data/idr0062A/6001240_labels.zarr\")\n",
+    "# show the image using pyvista\n",
+    "oa_image.view(how=\"pyvista\")"
+   ]
   }
  ],
  "metadata": {
diff --git a/docs/src/examples/learning_to_fly_with_ome-arrow.py b/docs/src/examples/learning_to_fly_with_ome-arrow.py
index 23c21f2..d37ef0f 100644
--- a/docs/src/examples/learning_to_fly_with_ome-arrow.py
+++ b/docs/src/examples/learning_to_fly_with_ome-arrow.py
@@ -44,7 +44,10 @@
 stack
 
 # we can visualize the stack using pyvista for 3D rendering
-stack.view(how="pyvista")
+# note: we use manually specified scaling values here
+# and can also default to what the image metadata provides
+# with `scaling_values=None` (the default).
+stack.view(how="pyvista", scaling_values=(1, 0.1, 0.1))
 
 # here we demonstrate that the data can be exported again
 # into numpy format and re-imported
@@ -95,3 +98,8 @@
 )
 # by default, the image and metadata are shown
 oa_image
+
+# read a 3d zarr image from IDR
+oa_image = OMEArrow(data="../../../tests/data/idr0062A/6001240_labels.zarr")
+# show the image using pyvista
+oa_image.view(how="pyvista")
diff --git a/pyproject.toml b/pyproject.toml
index 3301d11..9dc4d9e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -84,6 +84,15 @@ lint.select = [
   "C4",
   # mccabe
   "C90",
+  # pydocstyle (docstring presence)
+  "D100",
+  "D101",
+  "D102",
+  "D103",
+  "D104",
+  "D105",
+  "D106",
+  "D107",
   # pycodestyle
   "E",
   # pyflakes
@@ -102,6 +111,8 @@ lint.select = [
 lint.per-file-ignores."*" = [ "ANN401", "C901", "PLC0415", "PLR0912", "PLR0913", "PLR0915", "PLR2004" ]
 # Ignore `F401` (unused imports) for `__init__.py` file
 lint.per-file-ignores."__init__.py" = [ "F401" ]
+# ignore docstring presence checks for docs
+lint.per-file-ignores."docs/*" = [ "D100", "D101", "D102", "D103", "D104", "D105", "D106", "D107" ]
 # ignore typing rules for tests
 lint.per-file-ignores."tests/*" = [ "ANN201", "E501", "PLR0913", "PLR2004" ]
 
diff --git a/src/ome_arrow/core.py b/src/ome_arrow/core.py
index 81c2d74..7f7d810 100644
--- a/src/ome_arrow/core.py
+++ b/src/ome_arrow/core.py
@@ -299,7 +299,7 @@ def view(
         opacity: str | float = "sigmoid",
         clim: tuple[float, float] | None = None,
         show_axes: bool = True,
-        scaling_values: tuple[float, float, float] | None = (1.0, 0.1, 0.1),
+        scaling_values: tuple[float, float, float] | None = None,
     ) -> matplotlib.figure.Figure | "pyvista.Plotter":
         """
         Render an OME-Arrow record using Matplotlib or PyVista.
@@ -337,7 +337,10 @@ def view(
         clim: Contrast limits (``(low, high)``) for PyVista rendering.
         show_axes: If ``True``, display axes in the PyVista scene.
         scaling_values: Physical scale multipliers for the (x, y, z) axes used by
-            PyVista, typically to express anisotropy. Defaults to ``(1.0, 0.1, 0.1)``.
+            PyVista, typically to express anisotropy. If ``None``, uses metadata
+            scaling from the OME-Arrow record (pixels_meta.physical_size_x/y/z).
+            These scaling values will default to 1µm if metadata is missing in
+            source image metadata.
 
         Returns:
         matplotlib.figure.Figure | pyvista.Plotter:
diff --git a/src/ome_arrow/ingest.py b/src/ome_arrow/ingest.py
index a77d0f9..2f9e40e 100644
--- a/src/ome_arrow/ingest.py
+++ b/src/ome_arrow/ingest.py
@@ -3,6 +3,7 @@
 """
 
 import itertools
+import json
 import re
 import warnings
 from datetime import datetime, timezone
@@ -20,6 +21,129 @@
 from ome_arrow.meta import OME_ARROW_STRUCT, OME_ARROW_TAG_TYPE, OME_ARROW_TAG_VERSION
 
 
+def _normalize_unit(unit: str | None) -> str | None:
+    if not unit:
+        return None
+    u = unit.strip().lower()
+    if u in {"micrometer", "micrometre", "micron", "microns", "um", "µm"}:
+        return "µm"
+    if u in {"nanometer", "nanometre", "nm"}:
+        return "nm"
+    return unit
+
+
+def _read_physical_pixel_sizes(
+    img: BioImage,
+) -> tuple[float, float, float, str | None, bool]:
+    pps = getattr(img, "physical_pixel_sizes", None)
+    if pps is None:
+        return 1.0, 1.0, 1.0, None, False
+
+    vx = getattr(pps, "X", None) or getattr(pps, "x", None)
+    vy = getattr(pps, "Y", None) or getattr(pps, "y", None)
+    vz = getattr(pps, "Z", None) or getattr(pps, "z", None)
+
+    if vx is None and vy is None and vz is None:
+        return 1.0, 1.0, 1.0, None, False
+
+    try:
+        psize_x = float(vx or 1.0)
+        psize_y = float(vy or 1.0)
+        psize_z = float(vz or 1.0)
+    except Exception:
+        return 1.0, 1.0, 1.0, None, False
+
+    unit = getattr(pps, "unit", None) or getattr(pps, "units", None)
+    unit = _normalize_unit(str(unit)) if unit is not None else None
+
+    return psize_x, psize_y, psize_z, unit, True
+
+
+def _load_zarr_attrs(zarr_path: Path) -> dict:
+    zarr_json = zarr_path / "zarr.json"
+    if zarr_json.exists():
+        try:
+            data = json.loads(zarr_json.read_text())
+            return data.get("attributes") or data.get("attrs") or {}
+        except Exception:
+            return {}
+    zattrs = zarr_path / ".zattrs"
+    if zattrs.exists():
+        try:
+            return json.loads(zattrs.read_text())
+        except Exception:
+            return {}
+    return {}
+
+
+def _extract_multiscales(attrs: dict) -> list[dict]:
+    if not isinstance(attrs, dict):
+        return []
+    ome = attrs.get("ome")
+    if isinstance(ome, dict) and isinstance(ome.get("multiscales"), list):
+        return ome["multiscales"]
+    if isinstance(attrs.get("multiscales"), list):
+        return attrs["multiscales"]
+    return []
+
+
+def _read_ngff_scale(zarr_path: Path) -> tuple[float, float, float, str | None] | None:
+    zarr_root = zarr_path
+    for parent in [zarr_path, *list(zarr_path.parents)]:
+        if parent.suffix.lower() in {".zarr", ".ome.zarr"}:
+            zarr_root = parent
+            break
+
+    for candidate in (zarr_path, zarr_root):
+        attrs = _load_zarr_attrs(candidate)
+        multiscales = _extract_multiscales(attrs)
+        if multiscales:
+            break
+    else:
+        return None
+
+    ms = multiscales[0]
+    axes = ms.get("axes") or []
+    datasets = ms.get("datasets") or []
+    if not axes or not datasets:
+        return None
+
+    ds = next((d for d in datasets if str(d.get("path")) == "0"), datasets[0])
+    cts = ds.get("coordinateTransformations") or []
+    scale_ct = next((ct for ct in cts if ct.get("type") == "scale"), None)
+    if not scale_ct:
+        return None
+
+    scale = scale_ct.get("scale") or []
+    if len(scale) != len(axes):
+        return None
+
+    axis_scale: dict[str, float] = {}
+    axis_unit: dict[str, str] = {}
+    for i, ax in enumerate(axes):
+        name = str(ax.get("name", "")).lower()
+        if name in {"x", "y", "z"}:
+            try:
+                axis_scale[name] = float(scale[i])
+            except Exception:
+                continue
+            unit = _normalize_unit(ax.get("unit"))
+            if unit:
+                axis_unit[name] = unit
+
+    if not axis_scale:
+        return None
+
+    psize_x = axis_scale.get("x", 1.0)
+    psize_y = axis_scale.get("y", 1.0)
+    psize_z = axis_scale.get("z", 1.0)
+
+    units = [axis_unit.get(a) for a in ("x", "y", "z") if axis_unit.get(a)]
+    unit = units[0] if units and len(set(units)) == 1 else None
+
+    return psize_x, psize_y, psize_z, unit
+
+
 def to_ome_arrow(
     type_: str = OME_ARROW_TAG_TYPE,
     version: str = OME_ARROW_TAG_VERSION,
@@ -338,13 +462,8 @@ def from_tiff(
     if size_x <= 0 or size_y <= 0:
         raise ValueError("Image must have positive Y and X dims.")
 
-    pps = getattr(img, "physical_pixel_sizes", None)
-    try:
-        psize_x = float(getattr(pps, "X", None) or 1.0)
-        psize_y = float(getattr(pps, "Y", None) or 1.0)
-        psize_z = float(getattr(pps, "Z", None) or 1.0)
-    except Exception:
-        psize_x = psize_y = psize_z = 1.0
+    psize_x, psize_y, psize_z, unit, _pps_valid = _read_physical_pixel_sizes(img)
+    psize_unit = unit or "µm"
 
     # --- NEW: coerce top-level strings --------------------------------
     img_id = str(image_id or p.stem)
@@ -394,7 +513,7 @@ def from_tiff(
         physical_size_x=psize_x,
         physical_size_y=psize_y,
         physical_size_z=psize_z,
-        physical_size_unit="µm",
+        physical_size_unit=psize_unit,
         channels=channels,
         planes=planes,
         masks=None,
@@ -410,6 +529,20 @@ def from_stack_pattern_path(
     image_id: Optional[str] = None,
     name: Optional[str] = None,
 ) -> pa.StructScalar:
+    """Build an OME-Arrow record from a filename pattern describing a stack.
+
+    Args:
+        pattern_path: Path or pattern string describing the stack layout.
+        default_dim_for_unspecified: Dimension to use when tokens lack a dim.
+        map_series_to: Dimension to map series tokens to (e.g., "T"), or None.
+        clamp_to_uint16: Whether to clamp pixel values to uint16.
+        channel_names: Optional list of channel names to apply.
+        image_id: Optional image identifier override.
+        name: Optional display name override.
+
+    Returns:
+        A validated OME-Arrow StructScalar describing the stack.
+    """
     path = Path(pattern_path)
     folder = path.parent
     line = path.name.strip()
@@ -741,13 +874,15 @@ def from_ome_zarr(
     if size_x <= 0 or size_y <= 0:
         raise ValueError("Image must have positive Y and X dimensions.")
 
-    pps = getattr(img, "physical_pixel_sizes", None)
-    try:
-        psize_x = float(getattr(pps, "X", None) or 1.0)
-        psize_y = float(getattr(pps, "Y", None) or 1.0)
-        psize_z = float(getattr(pps, "Z", None) or 1.0)
-    except Exception:
-        psize_x = psize_y = psize_z = 1.0
+    psize_x, psize_y, psize_z, unit, pps_valid = _read_physical_pixel_sizes(img)
+    psize_unit = unit or "µm"
+
+    if not pps_valid:
+        ngff_scale = _read_ngff_scale(p)
+        if ngff_scale is not None:
+            psize_x, psize_y, psize_z, unit = ngff_scale
+            if unit:
+                psize_unit = unit
 
     img_id = str(image_id or p.stem)
     display_name = str(name or p.name)
@@ -805,7 +940,7 @@ def from_ome_zarr(
         physical_size_x=psize_x,
         physical_size_y=psize_y,
         physical_size_z=psize_z,
-        physical_size_unit="µm",
+        physical_size_unit=psize_unit,
         channels=channels,
         planes=planes,
         masks=None,
diff --git a/src/ome_arrow/view.py b/src/ome_arrow/view.py
index 2ec719b..303475a 100644
--- a/src/ome_arrow/view.py
+++ b/src/ome_arrow/view.py
@@ -33,6 +33,23 @@ def view_matplotlib(
     cmap: str = "gray",
     show: bool = True,
 ) -> tuple[Figure, Axes, AxesImage]:
+    """Render a single (t, c, z) plane with Matplotlib.
+
+    Args:
+        data: OME-Arrow row or dict containing pixels_meta and planes.
+        tcz: (t, c, z) indices of the plane to render.
+        autoscale: If True, infer vmin/vmax from the image data.
+        vmin: Explicit lower display limit for intensity scaling.
+        vmax: Explicit upper display limit for intensity scaling.
+        cmap: Matplotlib colormap name.
+        show: Whether to display the plot immediately.
+
+    Returns:
+        A tuple of (figure, axes, image) from Matplotlib.
+
+    Raises:
+        ValueError: If the requested plane is missing or pixel sizes mismatch.
+    """
     if isinstance(data, pa.StructScalar):
         data = data.as_py()
 
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@@ -0,0 +1 @@
+{"chunk_grid":{"configuration":{"chunk_shape":[1,10,512,512]},"name":"regular"},"chunk_key_encoding":{"name":"default"},"codecs":[{"configuration":{"chunk_shape":[1,1,256,256],"codecs":[{"configuration":{"endian":"little"},"name":"bytes"},{"configuration":{"blocksize":0,"clevel":5,"cname":"zstd","shuffle":"shuffle","typesize":2},"name":"blosc"}],"index_codecs":[{"configuration":{"endian":"little"},"name":"bytes"},{"name":"crc32c"}]},"name":"sharding_indexed"}],"data_type":"uint16","dimension_names":["c","z","y","x"],"fill_value":0,"node_type":"array","shape":[2,236,275,271],"zarr_format":3}
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diff --git a/tests/data/idr0062A/6001240_labels.zarr/6001240_labels.zarr/ro-crate-metadata.json b/tests/data/idr0062A/6001240_labels.zarr/6001240_labels.zarr/ro-crate-metadata.json
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--- /dev/null
+++ b/tests/data/idr0062A/6001240_labels.zarr/6001240_labels.zarr/ro-crate-metadata.json
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+{
+  "@context": [
+    "https://w3id.org/ro/crate/1.1/context",
+    {
+      "organism_classification": "https://schema.org/taxonomicRange",
+      "BioChemEntity": "https://schema.org/BioChemEntity",
+      "channel": "https://www.openmicroscopy.org/Schemas/Documentation/Generated/OME-2016-06/ome_xsd.html#Channel",
+      "obo": "http://purl.obolibrary.org/obo/",
+      "FBcv": "http://ontobee.org/ontology/FBcv/",
+      "acquisiton_method": {
+        "@reverse": "https://schema.org/result",
+        "@type": "@id"
+      },
+      "biological_entity": "https://schema.org/about",
+      "biosample": "http://purl.obolibrary.org/obo/OBI_0002648",
+      "preparation_method": "https://www.wikidata.org/wiki/Property:P1537",
+      "specimen": "http://purl.obolibrary.org/obo/HSO_0000308"
+    }
+  ],
+  "@graph": [
+    {
+      "@id": "./",
+      "@type": "Dataset",
+      "name": "dataset name",
+      "description": "dataset description",
+      "licence": "https://creativecommons.org/licenses/by/4.0/"
+    },
+    {
+      "@id": "ro-crate-metadata.json",
+      "@type": "CreativeWork",
+      "conformsTo": {
+        "@id": "https://w3id.org/ro/crate/1.1"
+      },
+      "about": {
+        "@id": "./"
+      }
+    }
+  ]
+}
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diff --git a/tests/data/idr0062A/6001240_labels.zarr/labels/0/3/zarr.json b/tests/data/idr0062A/6001240_labels.zarr/labels/0/3/zarr.json
new file mode 100644
index 0000000..a7742ba
--- /dev/null
+++ b/tests/data/idr0062A/6001240_labels.zarr/labels/0/3/zarr.json
@@ -0,0 +1 @@
+{"chunk_grid":{"configuration":{"chunk_shape":[1,10,512,512]},"name":"regular"},"chunk_key_encoding":{"name":"default"},"codecs":[{"configuration":{"chunk_shape":[1,1,256,256],"codecs":[{"name":"bytes"},{"configuration":{"blocksize":0,"clevel":5,"cname":"zstd","shuffle":"bitshuffle","typesize":1},"name":"blosc"}],"index_codecs":[{"configuration":{"endian":"little"},"name":"bytes"},{"name":"crc32c"}]},"name":"sharding_indexed"}],"data_type":"int8","dimension_names":["c","z","y","x"],"fill_value":0,"node_type":"array","shape":[1,236,34,33],"zarr_format":3}
diff --git a/tests/data/idr0062A/6001240_labels.zarr/labels/0/zarr.json b/tests/data/idr0062A/6001240_labels.zarr/labels/0/zarr.json
new file mode 100644
index 0000000..91d4569
--- /dev/null
+++ b/tests/data/idr0062A/6001240_labels.zarr/labels/0/zarr.json
@@ -0,0 +1 @@
+{"attributes": {"ome": {"version": "0.5", "image-label": {"colors": [{"label-value": 1, "rgba": [128, 128, 128, 128]}, {"label-value": 2, "rgba": [128, 128, 128, 128]}, {"label-value": 3, "rgba": [128, 128, 128, 128]}, {"label-value": 4, "rgba": [128, 128, 128, 128]}, {"label-value": 5, "rgba": [128, 128, 128, 128]}, {"label-value": 6, "rgba": [128, 128, 128, 128]}, {"label-value": 7, "rgba": [128, 128, 128, 128]}, {"label-value": 8, "rgba": [128, 128, 128, 128]}, {"label-value": 9, "rgba": [128, 128, 128, 128]}, {"label-value": 10, "rgba": [128, 128, 128, 128]}, {"label-value": 11, "rgba": [128, 128, 128, 128]}, {"label-value": 12, "rgba": [128, 128, 128, 128]}, {"label-value": 13, "rgba": [128, 128, 128, 128]}, {"label-value": 14, "rgba": [128, 128, 128, 128]}, {"label-value": 15, "rgba": [128, 128, 128, 128]}, {"label-value": 16, "rgba": [128, 128, 128, 128]}, {"label-value": 17, "rgba": [128, 128, 128, 128]}, {"label-value": 18, "rgba": [128, 128, 128, 128]}, {"label-value": 19, "rgba": [128, 128, 128, 128]}, {"label-value": 20, "rgba": [128, 128, 128, 128]}, {"label-value": 21, "rgba": [128, 128, 128, 128]}, {"label-value": 22, "rgba": [128, 128, 128, 128]}, {"label-value": 23, "rgba": [128, 128, 128, 128]}, {"label-value": 24, "rgba": [128, 128, 128, 128]}, {"label-value": 25, "rgba": [128, 128, 128, 128]}, {"label-value": 26, "rgba": [128, 128, 128, 128]}, {"label-value": 27, "rgba": [128, 128, 128, 128]}, {"label-value": 28, "rgba": [128, 128, 128, 128]}, {"label-value": 29, "rgba": [128, 128, 128, 128]}, {"label-value": 30, "rgba": [128, 128, 128, 128]}, {"label-value": 31, "rgba": [128, 128, 128, 128]}, {"label-value": 32, "rgba": [128, 128, 128, 128]}, {"label-value": 33, "rgba": [128, 128, 128, 128]}, {"label-value": 34, "rgba": [128, 128, 128, 128]}, {"label-value": 35, "rgba": [128, 128, 128, 128]}, {"label-value": 36, "rgba": [128, 128, 128, 128]}, {"label-value": 37, "rgba": [128, 128, 128, 128]}, {"label-value": 38, "rgba": [128, 128, 128, 128]}, {"label-value": 39, "rgba": [128, 128, 128, 128]}, {"label-value": 40, "rgba": [128, 128, 128, 128]}, {"label-value": 41, "rgba": [128, 128, 128, 128]}, {"label-value": 42, "rgba": [128, 128, 128, 128]}, {"label-value": 43, "rgba": [128, 128, 128, 128]}, {"label-value": 44, "rgba": [128, 128, 128, 128]}, {"label-value": 45, "rgba": [128, 128, 128, 128]}, {"label-value": 46, "rgba": [128, 128, 128, 128]}, {"label-value": 47, "rgba": [128, 128, 128, 128]}, {"label-value": 48, "rgba": [128, 128, 128, 128]}, {"label-value": 49, "rgba": [128, 128, 128, 128]}, {"label-value": 50, "rgba": [128, 128, 128, 128]}, {"label-value": 51, "rgba": [128, 128, 128, 128]}, {"label-value": 52, "rgba": [128, 128, 128, 128]}, {"label-value": 53, "rgba": [128, 128, 128, 128]}, {"label-value": 54, "rgba": [128, 128, 128, 128]}, {"label-value": 55, "rgba": [128, 128, 128, 128]}, {"label-value": 56, "rgba": [128, 128, 128, 128]}, {"label-value": 57, "rgba": [128, 128, 128, 128]}, {"label-value": 58, "rgba": [128, 128, 128, 128]}, {"label-value": 59, "rgba": [128, 128, 128, 128]}, {"label-value": 60, "rgba": [128, 128, 128, 128]}, {"label-value": 61, "rgba": [128, 128, 128, 128]}], "properties": [{"label-value": 1, "omero:roiId": 1380887, "omero:shapeId": 1664569}, {"label-value": 2, "omero:roiId": 1380888, "omero:shapeId": 1664617}, {"label-value": 3, "omero:roiId": 1380889, "omero:shapeId": 1664664}, {"label-value": 4, "omero:roiId": 1380890, "omero:shapeId": 1664709}, {"label-value": 5, "omero:roiId": 1380891, "omero:shapeId": 1664749}, {"label-value": 6, "omero:roiId": 1380892, "omero:shapeId": 1664787}, {"label-value": 7, "omero:roiId": 1380893, "omero:shapeId": 1664826}, {"label-value": 8, "omero:roiId": 1380894, "omero:shapeId": 1664859}, {"label-value": 9, "omero:roiId": 1380895, "omero:shapeId": 1664898}, {"label-value": 10, "omero:roiId": 1380896, "omero:shapeId": 1664932}, {"label-value": 11, "omero:roiId": 1380897, "omero:shapeId": 1664967}, {"label-value": 12, "omero:roiId": 1380898, "omero:shapeId": 1665000}, {"label-value": 13, "omero:roiId": 1380899, "omero:shapeId": 1665036}, {"label-value": 14, "omero:roiId": 1380900, "omero:shapeId": 1665078}, {"label-value": 15, "omero:roiId": 1380901, "omero:shapeId": 1665118}, {"label-value": 16, "omero:roiId": 1380902, "omero:shapeId": 1665156}, {"label-value": 17, "omero:roiId": 1380903, "omero:shapeId": 1665200}, {"label-value": 18, "omero:roiId": 1380904, "omero:shapeId": 1665238}, {"label-value": 19, "omero:roiId": 1380905, "omero:shapeId": 1665283}, {"label-value": 20, "omero:roiId": 1380906, "omero:shapeId": 1665319}, {"label-value": 21, "omero:roiId": 1380907, "omero:shapeId": 1665356}, {"label-value": 22, "omero:roiId": 1380908, "omero:shapeId": 1665396}, {"label-value": 23, "omero:roiId": 1380909, "omero:shapeId": 1665428}, {"label-value": 24, "omero:roiId": 1380910, "omero:shapeId": 1665467}, {"label-value": 25, "omero:roiId": 1380911, "omero:shapeId": 1665513}, {"label-value": 26, "omero:roiId": 1380912, "omero:shapeId": 1665541}, {"label-value": 27, "omero:roiId": 1380913, "omero:shapeId": 1665575}, {"label-value": 28, "omero:roiId": 1380914, "omero:shapeId": 1665611}, {"label-value": 29, "omero:roiId": 1380915, "omero:shapeId": 1665662}, {"label-value": 30, "omero:roiId": 1380916, "omero:shapeId": 1665709}, {"label-value": 31, "omero:roiId": 1380917, "omero:shapeId": 1665743}, {"label-value": 32, "omero:roiId": 1380918, "omero:shapeId": 1665777}, {"label-value": 33, "omero:roiId": 1380919, "omero:shapeId": 1665808}, {"label-value": 34, "omero:roiId": 1380920, "omero:shapeId": 1665853}, {"label-value": 35, "omero:roiId": 1380921, "omero:shapeId": 1665891}, {"label-value": 36, "omero:roiId": 1380922, "omero:shapeId": 1665935}, {"label-value": 37, "omero:roiId": 1380923, "omero:shapeId": 1665970}, {"label-value": 38, "omero:roiId": 1380924, "omero:shapeId": 1666013}, {"label-value": 39, "omero:roiId": 1380925, "omero:shapeId": 1666052}, {"label-value": 40, "omero:roiId": 1380926, "omero:shapeId": 1666085}, {"label-value": 41, "omero:roiId": 1380927, "omero:shapeId": 1666118}, {"label-value": 42, "omero:roiId": 1380928, "omero:shapeId": 1666158}, {"label-value": 43, "omero:roiId": 1380929, "omero:shapeId": 1666194}, {"label-value": 44, "omero:roiId": 1380930, "omero:shapeId": 1666235}, {"label-value": 45, "omero:roiId": 1380931, "omero:shapeId": 1666268}, {"label-value": 46, "omero:roiId": 1380932, "omero:shapeId": 1666307}, {"label-value": 47, "omero:roiId": 1380933, "omero:shapeId": 1666338}, {"label-value": 48, "omero:roiId": 1380934, "omero:shapeId": 1666378}, {"label-value": 49, "omero:roiId": 1380935, "omero:shapeId": 1666411}, {"label-value": 50, "omero:roiId": 1380936, "omero:shapeId": 1666446}, {"label-value": 51, "omero:roiId": 1380937, "omero:shapeId": 1666481}, {"label-value": 52, "omero:roiId": 1380938, "omero:shapeId": 1666518}, {"label-value": 53, "omero:roiId": 1380939, "omero:shapeId": 1666558}, {"label-value": 54, "omero:roiId": 1380940, "omero:shapeId": 1666596}, {"label-value": 55, "omero:roiId": 1380941, "omero:shapeId": 1666671}, {"label-value": 56, "omero:roiId": 1380942, "omero:shapeId": 1666711}, {"label-value": 57, "omero:roiId": 1380943, "omero:shapeId": 1666746}, {"label-value": 58, "omero:roiId": 1380944, "omero:shapeId": 1666789}, {"label-value": 59, "omero:roiId": 1380945, "omero:shapeId": 1666826}, {"label-value": 60, "omero:roiId": 1380946, "omero:shapeId": 1666846}, {"label-value": 61, "omero:roiId": 1380947, "omero:shapeId": 1666891}], "source": {"image": "../.."}}, "multiscales": [{"axes": [{"name": "c", "type": "channel"}, {"name": "z", "type": "space", "unit": "micrometer"}, {"name": "y", "type": "space", "unit": "micrometer"}, {"name": "x", "type": "space", "unit": "micrometer"}], "datasets": [{"coordinateTransformations": [{"scale": [1.0, 0.5002025531914894, 0.3603981534640209, 0.3603981534640209], "type": "scale"}], "path": "0"}, {"coordinateTransformations": [{"scale": [1.0, 0.5002025531914894, 0.7207963069280418, 0.7207963069280418], "type": "scale"}], "path": "1"}, {"coordinateTransformations": [{"scale": [1.0, 0.5002025531914894, 1.4415926138560835, 1.4415926138560835], "type": "scale"}], "path": "2"}, {"coordinateTransformations": [{"scale": [1.0, 0.5002025531914894, 2.883185227712167, 2.883185227712167], "type": "scale"}], "path": "3"}], "name": "0"}]}}, "zarr_format": 3, "node_type": "group"}
diff --git a/tests/data/idr0062A/6001240_labels.zarr/labels/zarr.json b/tests/data/idr0062A/6001240_labels.zarr/labels/zarr.json
new file mode 100644
index 0000000..cde99cd
--- /dev/null
+++ b/tests/data/idr0062A/6001240_labels.zarr/labels/zarr.json
@@ -0,0 +1 @@
+{"attributes": {"ome": {"labels": ["0"]}}, "zarr_format": 3, "node_type": "group"}
diff --git a/tests/data/idr0062A/6001240_labels.zarr/zarr.json b/tests/data/idr0062A/6001240_labels.zarr/zarr.json
new file mode 100644
index 0000000..24e6ef0
--- /dev/null
+++ b/tests/data/idr0062A/6001240_labels.zarr/zarr.json
@@ -0,0 +1 @@
+{"attributes": {"ome": {"version": "0.5", "_creator": {"name": "omero-zarr"}, "multiscales": [{"axes": [{"name": "c", "type": "channel"}, {"name": "z", "type": "space", "unit": "micrometer"}, {"name": "y", "type": "space", "unit": "micrometer"}, {"name": "x", "type": "space", "unit": "micrometer"}], "datasets": [{"coordinateTransformations": [{"scale": [1.0, 0.5002025531914894, 0.3603981534640209, 0.3603981534640209], "type": "scale"}], "path": "0"}, {"coordinateTransformations": [{"scale": [1.0, 0.5002025531914894, 0.7207963069280418, 0.7207963069280418], "type": "scale"}], "path": "1"}, {"coordinateTransformations": [{"scale": [1.0, 0.5002025531914894, 1.4415926138560835, 1.4415926138560835], "type": "scale"}], "path": "2"}]}], "omero": {"channels": [{"active": true, "coefficient": 1.0, "color": "0000FF", "family": "linear", "inverted": false, "label": "LaminB1", "window": {"end": 1500.0, "max": 65535.0, "min": 0.0, "start": 0.0}}, {"active": true, "coefficient": 1.0, "color": "FFFF00", "family": "linear", "inverted": false, "label": "Dapi", "window": {"end": 1500.0, "max": 65535.0, "min": 0.0, "start": 0.0}}], "id": 1, "rdefs": {"defaultT": 0, "defaultZ": 118, "model": "color"}}}}, "zarr_format": 3, "node_type": "group"}
diff --git a/tests/test_scaling.py b/tests/test_scaling.py
new file mode 100644
index 0000000..090e470
--- /dev/null
+++ b/tests/test_scaling.py
@@ -0,0 +1,100 @@
+"""
+Scaling metadata tests for OME-TIFF and OME-Zarr.
+"""
+
+from __future__ import annotations
+
+import json
+from pathlib import Path
+
+import pytest
+from bioio import BioImage
+from bioio_ome_tiff import Reader as OMETiffReader
+from bioio_tifffile import Reader as TiffReader
+
+from ome_arrow.core import OMEArrow
+
+
+def _read_ngff_scale(zarr_group: Path) -> tuple[float, float, float, str | None]:
+    # Read NGFF metadata from the group-level attributes.
+    attrs = json.loads((zarr_group / "zarr.json").read_text()).get("attributes", {})
+    multiscales = attrs.get("ome", {}).get("multiscales", [])
+    assert multiscales, "Expected NGFF multiscales metadata in zarr.json"
+    ms = multiscales[0]
+    axes = ms.get("axes", [])
+    datasets = ms.get("datasets", [])
+    assert axes and datasets, "Expected axes/datasets metadata in NGFF multiscales"
+
+    # Find the scale transform for the base (path="0") dataset.
+    ds = next((d for d in datasets if str(d.get("path")) == "0"), datasets[0])
+    cts = ds.get("coordinateTransformations", [])
+    scale_ct = next((ct for ct in cts if ct.get("type") == "scale"), None)
+    assert scale_ct, "Expected scale coordinateTransformations in NGFF metadata"
+
+    scale = scale_ct.get("scale", [])
+    assert len(scale) == len(axes), "Scale length must match axes length"
+
+    # Map axis names to scale values and units, only for spatial axes.
+    axis_scale = {}
+    axis_unit = {}
+    for i, ax in enumerate(axes):
+        name = str(ax.get("name", "")).lower()
+        if name in {"x", "y", "z"}:
+            axis_scale[name] = float(scale[i])
+            unit = ax.get("unit")
+            if unit:
+                axis_unit[name] = str(unit)
+
+    # Default to 1.0 when a spatial axis is missing in metadata.
+    psize_x = axis_scale.get("x", 1.0)
+    psize_y = axis_scale.get("y", 1.0)
+    psize_z = axis_scale.get("z", 1.0)
+    # Use the unit only if all provided spatial units agree.
+    units = [axis_unit.get(a) for a in ("x", "y", "z") if axis_unit.get(a)]
+    unit = units[0] if units and len(set(units)) == 1 else None
+    return psize_x, psize_y, psize_z, unit
+
+
+def test_ome_zarr_scale_from_metadata() -> None:
+    """
+    Ensure NGFF scale metadata is mapped into OME-Arrow physical sizes.
+    """
+    zarr_path = Path("tests/data/idr0062A/6001240_labels.zarr/labels/0")
+    expected_x, expected_y, expected_z, unit = _read_ngff_scale(zarr_path)
+
+    obj = OMEArrow(str(zarr_path))
+    pm = obj.data.as_py()["pixels_meta"]
+
+    assert pm["physical_size_x"] == pytest.approx(expected_x)
+    assert pm["physical_size_y"] == pytest.approx(expected_y)
+    assert pm["physical_size_z"] == pytest.approx(expected_z)
+    if unit is not None:
+        assert pm["physical_size_x_unit"] == "µm"
+        assert pm["physical_size_y_unit"] == "µm"
+        assert pm["physical_size_z_unit"] == "µm"
+
+
+def test_ome_tiff_scale_from_metadata() -> None:
+    """
+    Ensure OME-TIFF physical pixel sizes map to OME-Arrow physical sizes.
+    """
+    tiff_path = Path("tests/data/examplehuman/AS_09125_050116030001_D03f00d2.tif")
+    reader = (
+        OMETiffReader
+        if tiff_path.suffix.lower() in {".ome.tif", ".ome.tiff"}
+        else TiffReader
+    )
+    img = BioImage(image=str(tiff_path), reader=reader)
+    pps = getattr(img, "physical_pixel_sizes", None)
+    assert pps is not None
+
+    expected_x = float(getattr(pps, "X", None) or 1.0)
+    expected_y = float(getattr(pps, "Y", None) or 1.0)
+    expected_z = float(getattr(pps, "Z", None) or 1.0)
+
+    obj = OMEArrow(str(tiff_path))
+    pm = obj.data.as_py()["pixels_meta"]
+
+    assert pm["physical_size_x"] == pytest.approx(expected_x)
+    assert pm["physical_size_y"] == pytest.approx(expected_y)
+    assert pm["physical_size_z"] == pytest.approx(expected_z)