The strategic shift from Unified Modeling Language (UML) to ontologies is a pivotal evolution in the approach to data management, particularly in the context of built asset digital twins. UML has been a standard modeling language used in software engineering to visualize the design of a system. It primarily operates under a ‘closed world assumption’, where any data not explicitly defined in the model is considered false. This approach, while structured, can be restrictive as it limits the ability to integrate new, unknown data into the existing model.
In contrast to UML, ontologies operate under an ‘open world assumption’. This paradigm shift means that unknown data is treated as just that—unknown—rather than false. This approach opens new possibilities for integrating external data, allowing for a more dynamic and flexible data model.
By using ontologies, we enable the integration of diverse data sets, facilitating the connection and interoperability between different domains of knowledge. This is especially beneficial in complex fields like built asset management, where data from various sources needs to be combined and analyzed cohesively.
Ontologies offer a scalable framework that can evolve with emerging data and concepts. This adaptability is crucial in today’s fast-paced digital environment, where new data types and relationships can emerge rapidly. Moreover, ontologies allow for a more nuanced and comprehensive data representation. This richness is crucial in capturing the complex relationships and dependencies in built-in digital twins.
The shift to ontologies provides a more flexible framework for data analysis, offering deeper insights and understanding of the data. It enables us to create more intelligent and responsive models that adapt to new information and changing conditions.
Critically, the use of ontologies is instrumental in developing knowledge graphs, which are a key part of our strategy for managing and leveraging data. These graphs provide a powerful tool for visualizing and interacting with data, uncovering new insights and relationships. The shift enhances our capability to manage complex data systems and aligns with the broader goal of transforming scattered data into strategic assets.
Click here to read the original article published by Eurostep.
Please give your feedback on this article or share a similar story for publishing by clicking here.
