The Datacentric Translator tool is your entry point into the modern datacentric, model-driven, low-code world of information management. Effectively, it allows you to create computable metadata for your datasets. It generates RDF for the model and the data as well as XML and/or JSON data if desired.

The open source tool Kunteksto allows you to transition existing datasets into the Datacentric, sharable model eco-system. However, it does not allow you to reuse components across data models.

The Translator is the next step towards being datacentric and provides analysis and the creation of reusable eXtended Datatypes of existing datasets so that you are truely bringing existing data into the Datacentric Universe. This provides for fine-grained model definitions that give enterprises a flexible, modular approach to becoming operationally datacentric. See What is Datacentric?

The Process

  • The basic process is to first define a Data Model Definition and import a CSV file.
  • Next select the DMD and select Process CSV from the menu.
  • This creates an eXtended Datatype for each column in the CSV.
  • You now need to edit each of the eXtended Datatypes so that the information is as complete as possible.
  • Once the eXtended Datatypes are complete, go back to the DMD, select it and then ‘Generate a Data Model’.
  • Now these eXtended Datatypes are avaialble for you to use as you begin the model-backed approach to your inforamtion management.


Module 1:

This tutorial introduces you to importing and annotating a small demo dataset.

Module 2:

This tutorial introduces you to importing and annotating a commonly seen data science dataset. This demonstrate further the approach to injecting knowledge into your models.

Module 3:

This tutorial introduces you to advanced data model desing based on previously generated eXtended Datatypes.