Ontologies

Learn about the ontology basics and some principles used in DTXS standard.

As per Wikipedia, ontology is the study of being. It is the branch of philosophy that investigates the nature of existence, the features all entities have in common, and how they are divided into basic categories of being.

Then, a digital twin is set of adaptive models that emulate the behaviour of a physical system in a virtual system getting real time data to update itself along its life cycle

It might sound strange to include philosophy into exact science like software development or structured data transfer. However, as per the nature of the digital twins and the variety of the data it can work with, the conceptualization of this data becomes very important and is the first step to build standards. This is where ontology helps.

The problem

The trick is how to use the ontologies to create a strict definition of APIs for transferring digital twin data between various endpoints (software tools, digital technologies, etc.).

The solution

This DTXS standard is tackling this problem by appling the ontology-based data integration, using the multiple ontologies approach, citing from Wikipedia:

Multiple ontologies, each modeling an individual data source, are used in combination for integration. Though, this approach is more flexible than the single ontology approach, it requires creation of mappings between the multiple ontologies.

For some more information, see also following articles:

From ontology classes to the API classes

Data integration based on multiple ontologies

The approach used in DTXS to combine multiple technologies is illustrated in the diagram below. In this figure, we can see standalone ontologies from different domains (e.g., nuclear decommissioning, robotics and IFC/BIM modelling). These ontologies define set of uniquely identified classes using URIs, typical for the domain of that ontogy.

  |-----------------|       |-----------------|       |-----------------|
  | Nuclear         |       | IEEE            |       | IFC             |
  | Decommissioning |       | Robotics        |       | BuildingSmart   |
  | Ontology        |       | Ontology        |       | Ontology        |
  |-----------------|       |-----------------|       |-----------------|
          |                         |                         |
          v                         v                         v
  |---------------------------------------------------------------------|
  | "Merger" ontology - providing links between classes and properties  |
  | of "input ontologies".                                              |
  |---------------------------------------------------------------------|

Figure 1: Diagram illustrating the merging process of standalone ontologies.

These classes then can have their own set of properties. The list and structure of these properties can be unlimited and thus hard to compare and merge.

Merging

Let's have the following:

Input ontologies - set of ontologies that we want to merge together
Merger ontology - an ontology providing a merging layer to create the resulting merged ontology
Output ontology - ontology created by merging the input ontologies using the merger ontology

The basis of merging is comparison - one needs to identify the commons and differencies between the classes and properties of the input ontologies.

List of ontologies

Following ontologies have been integrated into DTXS so far: