crowd: A Tool for Conceptual Modelling assisted by Automated Reasoning

Abstract

There is an increment on the complexity of the information systems derived from new paradigms, for example Semantic Web, Big Data, e-government, etc. which require high quality solutions to tackle complex problems such as information integration. This quality is widely determined by the conceptual level. In this work, we present crowd as a novel tool for designing both conceptual models and ontologies based on visual representations with assistance of logic-based reasoning services. The challenge and the intention behind this work is to define graphicallogical methodologies as effective solutions for the description of interest domains at conceptual level. We detail the tool and demonstrate the usage of an initial prototype with some simple examples. Moreover, we identify limitations and potential issues about modelling and propose some partial solutions to tackle them. Currently, we are working to release the first beta version of crowd.