Cloud-enabaled Multimodal Knowledge Modeling and Acquisition for Education and Learning (KaaS)

Realization of a cloud enabled Knowledge modeling as a Service (KaaS) supports acquiring, managing and sharing knowledge through different types of sources. Cloud computing enables its users to access and edit their data easily without any administration and software development expenses and difficulties. In this paper, an overview and implementation results of the concept called Knowledge Forge is described. The proposed concept of this research is successfully tested and applied in the representation and management of job knowledge (competences) towards the assessment of talent's proficiency. This can also be used for modeling of graduates and students proficiency in order to identify their competence gaps and assign proper learning sources to them in order to improve their competitiveness. The Knowledge Forge can be extended easily to a wide variety of applications in order to enable further knowledge formats and application areas. Thereby, new formats use their own graphical interface and methods, while no changes in the system itself are required. The main goal of this research is to enable skilled workers and knowledge engineers to search for, modify and connect different formats of knowledge(e.g. unstructured knowledge). Neither users nor administrators have to care about the data format, so a search may show better results out of all stored data along with external search results provided by web search engines. The result of this work is a framework for all KaaS purposes. Although its use is limited at the moment it creates a basis for new applications in several areas. Further work can enhance the functionality or simplify the enhancement process to enable even the users to create their own applications.