diff --git a/docs/notebooks/demo_sarxarray.ipynb b/docs/notebooks/demo_sarxarray.ipynb
index f81dd59..cf0ceac 100644
--- a/docs/notebooks/demo_sarxarray.ipynb
+++ b/docs/notebooks/demo_sarxarray.ipynb
@@ -188,6 +188,16 @@
     "print(stack)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The loaded `stack` variable is an `xarray.Dataset` object, which contains three data variables: `complex`, `amplitude`, and `phase`. The three variables are read as Dask arrays, which is not loaded into memory until you explicitly call methods like `compute()` or `persist()`. There are two advantages of using Dask arrays:\n",
+    "\n",
+    "- This allows you to work with larger-than-memory datasets.\n",
+    "- It allows easy parallelization of computations, since Dask arrays are chunked by default."
+   ]
+  },
   {
    "attachments": {},
    "cell_type": "markdown",
diff --git a/paper/paper.md b/paper/paper.md
index 29921fe..af08eaf 100644
--- a/paper/paper.md
+++ b/paper/paper.md
@@ -31,7 +31,7 @@ bibliography: paper.bib
 
 ## Summary
 
-Satellite-based Synthetic Aperture Radar (SAR) provides invaluable data for Earth Observation. The Interferometric SAR (InSAR) technique [@hanssen01], which utilizes a stack of SAR images in Single Look Complex (SLC) format, plays a significant role in various surface motion monitoring applications, e.g. civil-infrastructure stability [@chang2014detection; @chang2017railway; @ozer2018applicability], and hydrocarbons extraction [@fokker2016application; @ZHANG2022102847]. To facilitate advanced data processing for InSAR communities, we developed `SARXarray`, a Xarray extension for handling co-registered SLC SAR stacks. 
+Satellite-based Synthetic Aperture Radar (SAR) provides invaluable data for Earth Observation. The Interferometric SAR (InSAR) technique [@hanssen01], which utilizes a stack of SAR images in Single Look Complex (SLC) format, plays a significant role in various surface motion monitoring applications, e.g. civil-infrastructure stability [@chang2014detection; @chang2017railway; @ozer2018applicability], and hydrocarbon extraction [@fokker2016application; @ZHANG2022102847]. To facilitate advanced data processing for InSAR communities, we developed `SARXarray`, a Xarray extension for handling co-registered SLC SAR stacks. 
 
 ## Statement of Need
 
@@ -39,7 +39,7 @@ Satellite-based SAR generates data stacks with long temporal coverage, wide spat
 
 To facilitate efficient processing of SLC SAR stacks and minimize code customization, we developed `SARXarray`. 
 
-`SARXarray` leverages two well-established Python libraries `Xarray` and `Dask` from the [Pangeo community](https://www.pangeo.io/). It utilizes Xarray’s support on labeled multi-dimensional datasets to stress the space-time character of an SLC SAR stack. `Dask` is used to perform lazy evaluation of operations and block-wise computations. SARXarray can be integrated into existing Python workflows of InSAR processing and deployed on a variety of computational infrastructures. 
+`SARXarray` leverages two well-established Python libraries `Xarray` and `Dask` from the [Pangeo community](https://www.pangeo.io/). It utilizes Xarray’s support on labeled multi-dimensional datasets to stress the space-time character of an SLC SAR stack. `Dask` is used to perform lazy evaluation of operations and block-wise computations. SARXarray can be integrated into existing Python workflows of InSAR processing and deployed on a variety of compute infrastructures. 
 
 ## State of the field
 
@@ -54,7 +54,7 @@ A similar open-source library [`xarray-sentinel`](https://github.com/bopen/xarra
 
 The software has three main components: 
 
-- an I/O module that lazily loads binary SLCs and related metadata
+- an I/O module that lazily loads/writes binary SLCs and related metadata
 - a Stack accessor that provides basic SAR-specific operations (amplitude/phase extraction and Mean-Reflection-Map generation)
 - a utility module that provides functions for multi-Looking and coherence calculation. 
 
diff --git a/pyproject.toml b/pyproject.toml
index 20b6abc..60a3a30 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -16,7 +16,8 @@ dependencies = [
 ]
 description = "Xarray extension for Synthetic Aperture Radar (SAR) data"
 readme = "README.md"
-license = {file = "LICENSE"}
+license = "Apache-2.0"
+license-files = ["LICENSE"]
 authors = [
     {name = "Ou Ku", email = "o.ku@esciencecenter.nl"},
     {name = "Fakhereh Sarah Alidoost"},
@@ -29,7 +30,6 @@ keywords = ["radar", "sar", "insar", "earth observation", "distributed computing
 classifiers=[
     'Development Status :: 3 - Alpha',
     'Intended Audience :: Developers',
-    'License :: OSI Approved :: Apache Software License',
     'Natural Language :: English',
     'Programming Language :: Python :: 3.10',
     'Programming Language :: Python :: 3.11',