The PLASMA Framework: Laying the Path to Domain-Specific Semantics in Dataspaces

Alexander Paulus, André Pomp, Tobias Meisen

Abstract: Modern data management is evolving from centralized integration-based solutions to a non-integration-based process of finding, accessing and processing data, as observed within dataspaces. Common reference dataspace architectures assume that sources publish their own domain-specific schema. These schemas, also known as semantic models, can only be partially created automatically and require oversight and refinement by human modellers. Non-expert users, such as mechanical engineers or municipal workers, often have difficulty building models because they are faced with multiple ontologies, classes, and relations, and existing tools are not designed for non-expert users. The PLASMA framework consists of a platform and auxiliary services that focus on providing non-expert users with an accessible way to create and edit semantic models, combining automation approaches and support systems such as a recommendation engine. It also provides data conversion from raw data to RDF. In this paper we highlight the main features, like the modeling interface and the data conversion engine. We discuss how PLASMA as a tool is suitable for building semantic models by non-expert users in the context of dataspaces and show some applications where PLASMA has already been used in data management projects.