Tutorial

1. Input file

   First, we have a table in CSV format.
   

2. Upload file

   We go to Morph-OME website and upload the file. We can either upload a local file or enter the url of a remote one.
   

3. Select the ontology

   We can select one or more ontologies to be used for the auto-completion function in the next page
   

4. Select smart suggestion source

   We select the knowledge graph to help us in selecting the classes and properties in the next page. We can select None if we don't want to use the smart suggestion feature. Then we click on Open With Editor to annotate the columns.
   

5. Select the subject column

   We select the subject column, which contains the labels of the main entities in the input data. Here, the subject column is name. As we selected the DBpedia knowledge graph for the smart suggestion, the class of the subject column and the equivalent properties of the columns will be suggested.
   

6. Select the class

   If the suggested class of the subject column is correct, we can leave it as is. If we like to change it, we can type the correct class and editor will suggest the class.
   

7. Select properties

   If we selected the smart suggestion options, the system would try to predict the equivalent properties to the different columns (which is the case here). In this example, the system didn't predict the height, so we type the first few letters and the auto-complete function help us select the correct property.
   

8. Select Output

   We can choose to download the results as a mapping file in RML or R2RML format. We can also choose to generate the RDF of our data with a SPARQL endpoint. To do so, we choose the option Online KG
   

9. Generate KG

   We generate the knowledge graph and allow querying the data using SPARQL.
   

10. Find it again

    We can go to the page My Knowledge Graph, and access previously generated Knowledge Graphs.