Update README for standalone-datacatalog

standalone-datacatalog/README.md

@@ -1,3 +1,41 @@
 # The `standalone-datacatalog` Kedro starter
 
-For more information, see the [Kedro documentation about this starter](https://docs.kedro.org/en/stable/notebooks_and_ipython/kedro_as_a_data_registry.html).
+This starter, formerly known as `mini-kedro`, sets up a lightweight Kedro project that uses the Kedro [Data Catalog](https://docs.kedro.org/en/stable/data/index.html) as a registry for data without using any of the other features of Kedro.
+
+The starter comprises a minimal setup to use the traditional [Iris dataset](https://www.kaggle.com/uciml/iris).
+
+## Usage
+
+To create a new project based on this starter:
+
+```bash
+kedro new --starter=standalone-datacatalog
+```
+
+You can call the project any name you choose. When created, the project contains the following:
+
+* A `conf` directory, which contains an example `DataCatalog` configuration (`catalog.yml`):
+
+ ```yaml
+# conf/base/catalog.yml
+example_dataset_1:
+  type: pandas.CSVDataset
+  filepath: folder/filepath.csv
+
+example_dataset_2:
+  type: spark.SparkDataset
+  filepath: s3a://your_bucket/data/01_raw/example_dataset_2*
+  credentials: dev_s3
+  file_format: csv
+  save_args:
+    if_exists: replace
+```
+
+* A `data` directory, which contains an example dataset identical to the one used by the [`pandas-iris`](https://github.com/kedro-org/kedro-starters/tree/main/pandas-iris) starter
+
+* An example Jupyter notebook, which shows how to instantiate the `DataCatalog` and interact with the example dataset:
+
+```python
+df = catalog.load("example_dataset_1")
+df_2 = catalog.save("example_dataset_2")
+```