Unit 10

Learning Outcomes Achieved

1. Critically analyse development problems and determine appropriate methodologies, tools and techniques to solve them.

What is an Ontology?

It is useful to first define what an ontology is, in relation to UML. Visual representations of ontologies often look similar to UML diagrams, however, they are not the same. Ontologies aim to define all the concepts and relationships between elements of a domain in an integrated way (Gruber, 2008). Ontology diagrams and OWL can be used to explain ontologies in a visual way. UML diagrams are intended for designing concrete systems, and in contrast to ontologies, do not provide detailed domain knowledge such as relationships between concepts (Eric, 2015). In ontologies, additional knowledge can be gained through inference of the relationships between concepts.

Reasons for Using an Ontology

Although the word “ontology” is not directly used, and although the focus was primarily on business structure and functionality, the LEGO group introduced the concept of “process documentation” with the aim of organisational improvement (Bøgebjerg & Rosing, 2016). A challenge which was encountered was that at the company’s high rate of growth, many new employees would arrive while tenured employees would leave, taking their knowledge with them. Because this knowledge wasn’t stored within the company, it was ephemeral and as a result, new hires would misunderstand existing business processes, eventually developing their own interpretations of those processes, leading to disorder. By creating their ontology through documentation, they found that it was much easier to unify teams and pivot business strategies to adapt to ever-changing market conditions.

Feilmayr & Wöß (2016), found that in the tourism industry, using ontologies would make it possible to create technologies that, for lack of a better term, “speak a common language”, and in doing so, the value offering of products could be improved significantly. This would occur because ontologies make it possible to combine extremely detailed/contextual information across services in a meaningful way, allowing richer information to be extracted from existing data, and through formalization, can make more accurate recommendations to users.

Representing the Ontology of Astronauts

The following attachment provides a basic ontology for the IoT astronaut system.

Link to Ontology Files (load index.html or refer to ontology visual.png for a diagram)

Reflection

This exercise allowed me to achieve learning outcome 2, because I learned about the issue of knowledge representation and its effects in the workplace. Knowledge representation is something which cannot be solved with UML, but can be solved with ontologies. I can see ontologies being useful for businesses which end up forming their own terminologies or jargon to describe processes, concepts, or things within that specific domain. Completing this activity made me realize that ontologies are lightweight, and consequently, easy to create once you know the notation. As a result, I’d like to use them to explain/define jargon used at work, as businesses may have multiple terms for various phenomena, which can be a challenge to memorize. On another note, I’ve always wondered if there would be any benefit to creating “workplace dictionaries”, as opposed to having terminology circulate only by word-of-mouth. If time permits, I’d like to research this idea further.

References

Eric. (2015) What is the difference between OWL and UML in the Software Engineering Process. Available from: https://stackoverflow.com/questions/32736474/what-is-the-difference-between-owl-and-uml-in-the-software-engineering-process [Accessed 10 October 2021].

Bøgebjerg, A. & Rosing, M. (2016) LEGO - Transforming the LEGO organization, one process at a time. Leading Practices from the Outperformers. Available from: https://www.researchgate.net/publication/287815467LEGO-_Transforming_the_LEGO_organization_one_process_at_a_time_Leading_Practices_from_the_Outperformers [Accessed 1 November 2021].

Feilmayr, C. & Wöß, W. (2016) An analysis of ontologies and their success factors for application to business. Data & Knowledge Engineering 101: 1-23. DOI: https://doi.org/10.1016/j.datak.2015.11.003

Gruber, T. (2008) Ontology (Definition). Available from: https://tomgruber.org/writing/definition-of-ontology [Accessed 1 November 2021].