Designing Data Interchange Services for Learning Components

Abstract: The paper proposes design principles for data representation in cloud data interchange services among various information systems, with applications on e-learning systems. These principles contribute to detailing and improving standards in the process of retaining learning objects in repositories and facilitate discovering digital content used for teaching, learning, or training among various information systems. Equivalence algorithms and canonical representation are used in order to ensure the uniform representation in the cloud database. The solution we describe, proposed to be provided within cloud architectures, brings important advantages in e-learning systems communication and educational institutions cooperation, since different institutions use different e-learning systems and do not have automatic means of exchanging information. The advances in representing learning objects contributes to facilitating the exchange of these resources among different stakeholders.

Keywords: learning components, learning objects, equivalence and simplification algorithms, data interchange, cloud services, database representation, pattern matching, software design.