Tomáš Gregar

Semantically Enriched Tools for the Knowledge Society: Case of Project Management and Presentation

Working with semantically rich data is one of the stepping stones to the knowledge society. In recent years, gathering, processing, and using semantic data have made a big progress, particularly in the academic environment. However, the advantages of the semantic description remain commonly undiscovered by a “common user”, including people from academia and IT industry that could otherwise profit from capabilities of contemporary semantic systems in the areas of project management and/or technology-enhanced learning. Mostly, the root cause lays in complexity and non-transparency of the mainstream semantic applications. The semantic tool for project management and presentation consists mainly of a module for the semantic annotation of wiki pages integrated into the project management system Trac. It combines the dynamic, easy-of-use nature and applicability of a wiki for project management with the advantages of semantically rich and accurate approach. The system is released as open-source (OS) and is used for management of students’ and research projects at the research lab of the authors.

Semantic Wiki in Environmental Project Management

Advanced management of environmental data requires appropriate metadata and tooling. Moreover, contemporary environmental data is heterogenous, encompassing also data about people, environmentaly-related projects, and documents. Also geographical- and time-related information are vital for any environmental data and should be supported. To satisfy these requirements, “semantic wikis” represent suitable tools but usually requiring knowledge management skills. In this paper, we present a semantic extension to project-management tool Trac, enabling advanced but user-friendly querying in semantic data stored in the system and its visualization. As it builds upon the general concept of RDF-based semantic data, it can be freely extended into other contexts and deployed in various environmental management applications. We also discuss automatic formal visualization of semantic data. Such process significantly lowers the requirements on users in preparing the visualization in domains like environmental studies – and also helps to build Linked Data-aware and better human-readable interfaces of semantic data repositories.