Ontology-based end-user visual query formulation: Why, what, who, how, and which?

Value creation in an organisation is a time-sensitive and data-intensive process, yet it is often delayed and bounded by the reliance on IT experts extracting data for domain experts. Hence, there is a need for providing people who are not professional developers with the flexibility to pose relatively complex and ad hoc queries in an easy and intuitive way. In this respect, visual methods for query formulation undertake the challenge of making querying independent of users’ technical skills and the knowledge of the underlying textual query language and the structure of data. An ontology is more promising than the logical schema of the underlying data for guiding users in formulating queries, since it provides a richer vocabulary closer to the users’ understanding. However, on the one hand, today the most of world’s enterprise data reside in relational databases rather than triple stores, and on the other, visual query formulation has become more compelling due to ever-increasing data size and complexity—known as Big Data. This article presents and argues for ontology-based visual query formulation for end-users; discusses its feasibility in terms of ontology-based data access, which virtualises legacy relational databases as RDF, and the dimensions of Big Data; presents key conceptual aspects and dimensions, challenges, and requirements; and reviews, categorises, and discusses notable approaches and systems

Collaborative Social Structures and Task Modelling Integration

Abstract. Interdisciplinary work groups have proved to be one of the best practices (in terms of efficiency) in modern organizations. Large applications have many different users who can play different roles with responsibilities and rights depending on such roles. There are so many roles, groups, relationships among them, tasks, and collaborations, that it is very difficult to develop an application without gathering all this information in a proper way. This paper describes a modelling approach supported by a graphical notation, which makes the representation of such information easier to analyse and manage. The goal is to provide a complete and integrated approach to model collaborative interactive systems.

Evaluating the DIPORSI Framework: DIstributed Processing Of Remotely Sensed Imagery

The recent advances in remote sensing are contributing to improve emerging applications like geographical information systems