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Automated parsing, and ontological & machine learning-powered semantic similarity modelling, of the Digital, Data and Technology (DDaT) profession capability framework website.
Jillur Quddus • Founder & Chief Data Scientist • 30th September 2023
We are delighted to announce the public release of our DDaT ontology - an ontological model of the Digital, Data and Technology (DDaT) profession.
Our DDaT ontology contains public sector information sourced from the Digital, Data and Technology (DDaT) profession capability framework which is maintained by the Central Digital and Data Office (CDDO) and publicly-available under the Open Government License v3.0. This framework defines the DDaT disciplines (e.g. architecture), branches (e.g. technical architecture) and roles (e.g. Principal Technical Architect) found in government, and the skills (e.g. strategy) associated with them.
The initial goal of our DDaT ontological model is to enable a complementary means to visualise, search and explore the existing DDaT capability framework (rather than focusing on rigourous semantic structure). This includes an effective means to identify and visualise common skills and responsibilities shared between different roles across different disciplines. Over time, we hope to extend the ontology to include typical artefacts created by DDaT professionals (e.g. data catalogues, user personas etc.), and common digital services & systems (e.g. common data model, common data platform, website, API etc.). Our ultimate goal is to develop an ontology that defines and describes the full range of contemporary disciplines, roles, skills, artefacts, services and systems that make up the DDaT profession across all relevant global industries in both the private and public sector.
There are numerous ways to access our DDaT ontology, depending on your needs.
Visualisation
You can visualise the current publicly-released version of our DDaT ontology via our OntoSpark web application. To do so, please visit https://app.ontospark.com?ontologyid=ddat.
OWL RDF/XML
You can access both current and historic publicly-released versions of our DDaT ontology in OWL RDF/XML format via a public GitHub repository found at https://github.com/hyperlearningai/ddat-ontology.
WebProtégé
WebProtégé is a free, open-source ontology editor and development environment. To access the public (view-only) WebProtégé project containing our DDaT ontology, please visit https://webprotege.stanford.edu/#projects/a86cf6a3-c6f1-4dc8-a8db-b8be17e39736/edit/Classes (WebProtégé account required).
In order to generate an ontology model of the existing DDaT capability framework, we developed a Python application that automatically parses the DDaT capability framework website using open-source web automation libraries, and then creates the ontology as an OWL RDF/XML file. As part of our DDaT ontology release, we have also made the source code for this Python application open-source via a public GitHub repository found at https://github.com/hyperlearningai/ddat-ontology-modeller. Instructions for configuring and running this Python application may be found in the repository's README.md file.
If you have any questions regarding our DDaT ontology, or would like to contribute towards its iterative development, then please don't hesitate to get in touch!
DDaT Ontology Visualisation DDaT Ontology OWL File DDaT Parser & Modeller App
A fun and interactive introduction to both the Python programming language and basic computing concepts using programmable robots.
An introductory course to the Python 3 programming language, with a curriculum aligned to the Certified Associate in Python Programming (PCAP) examination syllabus (PCAP-31-02).
Automated parsing, and ontological & machine learning-powered semantic similarity modelling, of the Digital, Data and Technology (DDaT) profession capability framework website.