The era of digitalization poses high demands on capturing and processing knowledge generated in everyday life in formal models. Ontologies provide common means for formal knowledge capturing and modeling for a universe of discourse. Developing ontologies, however, can be a complex, time-consuming and expensive process which requires a significant amount of resource investments. Different stakeholders, such as ontology engineers, domain experts and ultimate users, are usually involved in the development process; they may be geographically distributed and work independently in isolated environments while typically have to synchronize their contributions. Several methodologies and tools have been created to enable ontology development for a number of different purposes and applications. Albeit designed to cover a range of development aspects, existing approaches lack comprehensive support of the ontology life-cycle, in particular independent work in disparate environments. In this thesis, we tackle the problem of collaborative ontology development in distributed and heterogeneous environments, and present an approach able to holistically assist the development of ontologies in diverse and independent scenarios. First, we define Git4Voc, a lightweight methodology comprising a set of guidelines and practices to be followed by stakeholders while modeling ontologies. We then conceive VoCol, a flexible and integrated development platform to address critical requirements from a technical perspective. . VoCol can be adopted in numerous scenarios and accommodate additional tools in a well-designed and semi-automatic ontology development workflow. The benefits of this flexibility are two-fold: 1) stakeholders do not need to strictly follow a specific methodology; in contrary, they can organize their work in small and incremental development steps; and 2) consumers may provide their feedback, even though they are not directly part of the active development team. We conducted a number of empirical evaluations to assess the effectiveness and efficiency of our holistic approach. The results from the empirical evaluations and concrete applications provide evidence that the methodology and techniques presented in this thesis comply with stakeholders’ needs and effectively support the entire ontology development life-cycle in distributed and heterogeneous environments.
In addition this talk will cover the following topics:
- Enabling Transfer Learning via a Neuro-Symbolic Approach;
- Using Knowledge Graphs for Context-aware Recommender Systems (CARS)
- Using Knowledge Graph Embeddings for Situation Classification
Speaker: Lavdim Halilaj