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diff --git a/docs/build/lift-data-from-tabular-data-such-as-csv-xslx-or-database-tables/index.md b/docs/build/lift-data-from-tabular-data-such-as-csv-xslx-or-database-tables/index.md
index 5f40a2fda..2daf1c9f6 100644
--- a/docs/build/lift-data-from-tabular-data-such-as-csv-xslx-or-database-tables/index.md
+++ b/docs/build/lift-data-from-tabular-data-such-as-csv-xslx-or-database-tables/index.md
@@ -27,12 +27,12 @@ This beginner-level tutorial shows how you can build a Knowledge Graph based on
The documentation consists of the following steps, which are described in detail below:
1. Registration of the target vocabulary
-2. Uploading of the data (file)/Connect to JDBC endpoint
-3. (Re-)View your data table
-4. Creation of a (target) graph
-5. Creation of the transformation rules
-6. Evaluation of the results of the transformation rules
-7. Execution of the transformation to populate the target graph
+2. Uploading of the data (file)
+3. Creating the Transformation
+4. Configure Mapping
+5. Evaluate a Transformation
+6. Build the Knowledge Graph
+
## Sample Material
@@ -72,20 +72,21 @@ The vocabulary contains the classes and properties needed to map the data into t
1. In Corporate Memory, click Vocabularies under **EXPLORE** in the navigation on the left side of the page.
- { class="bordered" width="30%" }
+ { class="bordered" width="50%" }
2. Click **Register new vocabulary** on the top right.
- { class="bordered" }
+ { class="bordered" width="50%" }
3. Define a **Name**, a **Graph URI** and a **Description** of the vocabulary. _In this example we will use:_
- - Name: _**Product Vocabulary**_
- - Graph URI: _**http://ld.company.org/prod-vocab/**_
- - Description: _**Example vocabulary modeled to describe relations between products and services.**_
- - Vocabulary File: Browse in your filesystem for the **[products_vocabulary.nt](products_vocabulary.nt)** file and select it to be uploaded.
+ - Label: `Product Vocabulary`
+ - Graph URI: `http://ld.company.org/prod-vocab/`
+ - Description: `Example vocabulary modeled to describe relations between products and services.`
+ - Upload File: Browse in your filesystem for the **[products_vocabulary.nt](products_vocabulary.nt)** file and select it to be uploaded.
+
+ { class="bordered" width="50%" }
- { class="bordered" width="50%" }
=== "cmemc"
@@ -95,35 +96,50 @@ The vocabulary contains the classes and properties needed to map the data into t
---
-## 2 Upload the data file / Connect to the JDBC endpoint
+## 2 Uploading of the data (file)
+
+1. In Corporate Memory, click **:fontawesome-regular-folder: Projects** under **BUILD** in the navigation on the left side of the page.
+
+ { class="bordered" width="50%" }
-=== "CSV + XLSX"
+2. Click **Create :octicons-plus-circle-24:** at the top right of the page.
- 1. In Corporate Memory, click Projects under **BUILD** in the navigation on the left side of the page.
+3. In the **Create new item** window, select **Project** and click **Add**. The Create new item of type Project window appears.
- { class="bordered" width="30%" }
+4. Fill in the required details such as Title and Description. Alternatively, import the existing project by clicking **Import Project File** and selecting the file from your system.
- 2. Click **Create** at the top of the page.
+5. Click **Create**. Your project is created.
+
+
+---
- 3. In **Create new item** window, select **Project** and click **Add**. The Create new item of type Project window appears.
+=== "Workflow view"
- 4. Fill in the required details such as Title and Description. Alternatively, import the existing project by clicking **Import Project File** and selecting the file from your system.
+ 1. Within your project, click on **Create workflow**.
- 5. Click **Create**. Your project is created.
+ { class="bordered" width="50%" }
- 6. Within your project, click **Create** or **Create item**.
+ 2. Fill out a label and click **Create**.
- 7. In the **Create new item** dialog, select **CSV**.
+ { class="bordered" width="50%" }
- { class="bordered" }
+ 3. Drag and drop the **[services.csv](services.csv) sample file** on the grid.
- 8. Fill out a label and upload the **[services.csv](services.csv) sample file**.
+ 4. Optionally change the Label, then click on **Create**.
- { class="bordered" }
+ { class="bordered" width="50%" }
- 9. Click **Create**.** Leave all other parameters at their default values.
+ 5. Create a second **dataset** by drag & drop it on the grid using [products.xlsx](products.xlsx) file.
- 10. Create a second **dataset**. Choose **Excel** and upload the [products.xlsx](products.xlsx) file.
+=== "cmemc"
+
+ ``` shell-session
+ $ cmemc project create tutorial-csv
+
+ $ cmemc dataset create --project tutorial-csv services.csv
+
+ $ cmemc dataset create --project tutorial-csv products.xlsx
+ ```
=== "JDBC"
@@ -131,7 +147,7 @@ The vocabulary contains the classes and properties needed to map the data into t
1. In the project, Click **Create** and select the **JDBC endpoint** type.
- { class="bordered" }
+ { class="bordered" width="50%" }
2. Define a **Label** for the dataset, specify the **JDBC Driver connection URL**, the **table** name and the **user** and **password** to connect to the database. _In this example we will use:_
@@ -141,7 +157,7 @@ The vocabulary contains the classes and properties needed to map the data into t
- username: _**root**_
- password: _**\*\*\*\***_
- { class="bordered" }
+ { class="bordered" width="50%" }
The general form of the JDBC connection string is:
@@ -168,142 +184,128 @@ The vocabulary contains the classes and properties needed to map the data into t
Instead of selecting a table you can also specify a custom SQL query in the _source query_ field.
-=== "cmemc"
-
- ``` shell-session
- $ cmemc project create tutorial-csv
-
- $ cmemc dataset create --project tutorial-csv services.csv
+---
- $ cmemc dataset create --project tutorial-csv products.xlsx
- ```
+## 3 Creating the Transformation
----
+The transformation defines how an input dataset (e.g. CSV) will be transformed into an output dataset (e.g. Knowledge Graph).
-## 3 (Re-)View your Data Table
+1. Click on the right dot and select **Connect to the newly created Transformation**.
-To validate that the input data is correct, you can preview the data table in Corporate Memory.
+ { class="bordered" width="50%" }
-1. On the dataset page, press the **Load preview** button
+2. Fill out the **Label** with _**Lift Service Database**_.
- { class="bordered" }
+ { class="bordered" width="50%" }
-2. Once the preview is loaded, you can view a couple of rows to check that your data is accessible.
- { class="bordered" }
+3. Scroll down to **Target vocabularies** and choose **Products vocabulary**.
-3. Optionally, you can click **start profiling** and explore statistics about the dataset.
+ { class="bordered" width="50%" }
- { class="bordered" }
+4. Click on **Create**.
---
-## 4 Create a Knowledge Graph
+## 4 Configure Mapping
-1. Click Create at the top of the page.
+1. Click on the 3 Dots from the previous created Transormation an choose **Mapping Editor**.
-2. In Create new item window, select Knowledge Graph and click Add.
+2. Click **Mapping** in the main area to expand its menu.
- { class="bordered" }
+3. Click **Edit** to create a base mapping.
-3. The Create new item of type Knowledge Graph window appears.
+ { class="bordered" width="50%" }
-4. Define a **Label** for the Knowledge Graph and provide a **graph** uri. Leave all the other parameters at the default values. _In this example we will use:_
+4. Define the **Target entity type** from the vocabulary, the **URI pattern** and a **label** for the mapping. _In this example we will use:_
- - Label: _**Service Knowledge Graph**_
- - Graph: _****_
+ - Target entity type: _**Service**_
+ - URI pattern:
-5. Click **Create**.
+ - Click **Create custom pattern**
+ - Insert `http://ld.company.org/prod-inst/{ServiceID}`, where `http://ld.company.org/prod-inst/` is a common prefix for the instances in this use case, and `{ServiceID}` is a placeholder that will resolve to the column of that name.
----
+ - An optional Label: `Service`
-## 5 Create a Transformation
+ { class="bordered" width="50%" }
-The transformation defines how an input dataset (e.g. CSV) will be transformed into an output dataset (e.g. Knowledge Graph).
+5. Click **Save**
-1. Click **Create** in your project.
+_Example RDF triple in our Knowledge Graph based on the mapping definition:_
-2. On the **Create New Item** window, select **Transform** and click **Add** to create a new transformation.
+``` text
+
+```
-3. Fill out the the details leaving the **target vocabularies** field at its default value **all installed vocabularies,** which will enable us to create a transformation to the previously installed products vocabulary. _In this example we will use:_
+6. Evaluate your mapping by clicking the Expand :material-greater-than: button in the **Examples of target data** property to see at most three generated base URIs.
- - Name: _**Lift Service Database**_
- - _In the section **INPUT TASK** in the field **Dataset**, select the previously created dataset: **Services** (Input Dataset)._
- - _Select the previously created dataset as the Output Dataset: **Service Knowledge Graph**_
+ { class="bordered" width="50%" }
-4. In the main area you will find the **Mapping editor**.
+ We have now created the Service entities in the Knowledge Graph. As a next step, we will add the name of the Service entity.
- { class="bordered" }
+7. Press the circular **Blue + button** on the lower right and select **Add value mapping**.
-5. Click **Mapping** in the main area to expand its menu.
+ { class="bordered" width="50%" }
- { class="bordered" }
+8. Define the **Target property**, the **Data type**, the **Value path** (column name) and a **Label** for your value mapping. _In this example we will use:_
-6. Click **Edit** to create a base mapping.
+ - Target Property: **_name_**
+ - Data type: _**String**_
+ - Value path: _**ServiceName**_ (which corresponds to the column of that name)
+ - An optional Label: _**service name**_
- { class="bordered" }
+ { class="bordered" width="50%" }
-7. Define the **Target entity type** from the vocabulary, the **URI pattern** and a **label** for the mapping. _In this example we will use:_
+9. Click **Save**.
- - Target entity type: _**Service**_
- - URI pattern:
+---
- - Click **Create custom pattern**
- - Insert _****_
- - where __ is a common prefix for the instances in this use case,
- - and _{ServiceID}_ is a placeholder that will resolve to the column of that name
+## 5 Evaluate a Transformation
- - _An optional Label: **Service**_
+Go the **Transform evaluation** tab of your transformation to view a list of generated entities. By clicking one of the generated entities, more details are provided.
- { class="bordered" }
+{ class="bordered" width="50%" }
-8. Click **Save** _Example RDF triple in our Knowledge Graph based on the mapping definition:_
- ```nt
-
- ```
+---
-9. Evaluate your mapping by clicking the Expand  button in the **Examples of target data** property to see at most three generated base URIs.
+## 6 Build the Knowledge Graph
- { class="bordered" }
+1. Switch back to the **Workflow view**.
- We have now created the Service entities in the Knowledge Graph. As a next step, we will add the name of the Service entity.
+2. Select the red dot on the right side and click **Connect to the newly created Knowledge graph**.
-10. Press the circular **Blue + button** on the lower right and select **Add value mapping**.
+ { class="bordered" width="50%" }
- { class="bordered" }
+3. Define a **Label** for the Knowledge Graph and provide a **graph** uri. Leave all the other parameters at the default values. _In this example we will use:_
-11. Define the **Target property**, the **Data type**, the **Value path** (column name) and a **Label** for your value mapping. _In this example we will use:_
+ - Label: `Service Knowledge Graph`
+ - Graph: `http://ld.company.org/prod-instances/`
- - Target Property: **_name_**
- - Data type: _**StringValueType**_
- - Value path: _**ServiceName**_ (which corresponds to the column of that name)
- - An optional Label: _**service name**_
+ { class="bordered" width="50%" }
- { class="bordered" }
+4. Click **Create**.
-12. Click **Save.**
+5. Press the :material-play: button and click on **Save and run workflow**.
----
+6. Validate the results by selecting **Workflow report** In this example, 9x Service triples were created in our Knowledge Graph based on the mapping.
-## 6 Evaluate a Transformation
+ { class="bordered" width="50%" }
-Go the **Transform evaluation** tab of your transformation to view a list of generated entities. By clicking one of the generated entities, more details are provided.
-{ class="bordered" }
+7. Click Knowledge Graph under **Explore** in the navigation on the left side of the page.
----
+ { class="bordered" width="50%" }
-## 7 Build the Knowledge Graph
+8. Optionally, you can click on the Settings Icon and add more columns to the viw.
-1. Go into the mapping and visit the **Transform execution** tab.
+ { class="bordered" width="50%" }
- { class="bordered" }
+9. Here you can add `name` for example.
-2. Press the  button and validate the results. In this example, 9x Service triples were created in our Knowledge Graph based on the mapping.
+ { class="bordered" width="50%" }
- { class="bordered" }
+10. Finally you can use the Explore **Knowledge Graphs** module to (re-)view of the created Knowledge Graph: `http://ld.company.org/prod-instances/`
-3. Finally you can use the Explore **Knowledge Graphs** module to (re-)view of the created Knowledge Graph:
+ { class="bordered" width="50%" }
- { class="bordered" }
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