Abstract Graph Database Management Systems brought data model abstractions closer to
how humans are used to handle knowledge–ie, driven by inferences across complex …

In this paper, we present a novel framework for enriching time series data in smart cities by
supplementing it with information from external sources via semantic data enrichment. Our …

One key driver of the Linked Data paradigm is the ability to lift data graphs from legacy
systems by employing various adapters and RDFizers (eg, D2RQ for relational databases …

Traditionally, venues that are publishing Knowledge Management research have been
separating concerns between two viewpoints that rarely converge into holistic approaches …

Our study reports a comparative analysis of natural language interactions with BPMN
models, specifically contrasting semantic graphs generated from diagrams by the RDF …

This chapter provides an overview on the current state of the ComVantage modeling method
implementation. The method addresses the domain of product-service systems that must run …

Abstract The Internet of Things (IoT) must address not only the data-level communication
across networks of sensors and cyber-physical systems, but also the machine-readable …

Software engineering benefitted from modeling standards (eg UML, BPMN), but Agile
Software Project Management tends to marginalize most forms of documentation including …

Advocating a convergence between generative AI and BPMN-based process analysis, this
study reports on experiments with multi-modal business process representations. By …

Abstract Model-driven engineering (MDE) traditionally relied on a generic notion of “model
transformation” to bridge design with software implementation, or the so-called “design-time” …