GrOwEr Detection

GrOwEr takes as input a set of ontologies and identifies the common ontology design patterns (ODP) detected in that set of ontologies.

Cite us:

Contact:

María Poveda-Villalón
Contact email:

Instructions

  1. Create a CSV file (example of csv file) indicating the ontologies for which you want to detect patterns or, if you have the ontologies stored locally, compress the ontologies in a ZIP file (example of zip file) .
  2. In case you do not have the desired ontologies stored locally, the CSV file should have the following format:
    • Each row of the CSV file represents a different ontology.
    • The first column represent the ontology prefix.
    • The second column represent the ontology URI.
    • The first row represents the CSV headers (i.e. the first column of the first row must have the value “Prefix”, and the second column of the first row must have the value “URI”).
  3. In case you have the desired ontologies stored locally, you can create a ZIP file from the folder where the ontologies are located.
  4. Drag and drop your CSV or ZIP file into the service dropping area.
  5. Select the type of the patterns to be detected. In other words, select if the patterns are going to be created from the type of the terms, the name of the terms, or both.
  6. Select if you prefer collections of named classes or individuals to be flattened or not.
  7. Download your web documentation. (example of the output)

Service

Drag and drop your CSV or ZIP file or click to choose your file

Choose a pattern type:

In other words, select if the patterns are going to be created from the type of the terms, the name of the terms, or both.

Choose if you prefer collections to be flattened or not:

In other words, select if you prefer collections of named classes or individuals to be flattened or not.