Linked Data Tools

Semantic Web technologies have immense potential to transform the Internet into a distributed reasoning machine that will not only execute extremely precise searches, but will also have the ability to analyze the data it finds to create new knowledge. This paper examines the state of Semantic Web (also known as Linked Data) tools and infrastructure to determine whether semantic technologies are sufficiently mature for non–expert use, and to identify some of the obstacles to global Linked Data implementation.

Linked Data Tools

Semantic Web technologies have immense potential to transform the Internet into a distributed reasoning machine that will not only execute extremely precise searches, but will also have the ability to analyze the data it finds to create new knowledge. This paper examines the state of Semantic Web (also known as Linked Data) tools and infrastructure to determine whether semantic technologies are sufficiently mature for non–expert use, and to identify some of the obstacles to global Linked Data implementation.

A rule-based argumentation framework for distributed contextual reasoning in dynamic environments

In this study, we tackled the problem of distributed reasoning in environments in which agents may have incomplete and inconsistent knowledge. Conflicts between agents are resolved through defeasible argumentation-based semantics with a preference function. Support for dynamic environments, where agents constantly enter and leave the system, was achieved by means of rules whose premises can be held by arbitrary agents. Moreover, we presented a formalism that enables agents to share information about their current situation or focus when issuing queries to other agents. This is necessary in environments where agents have a partial view of the world and must be able to cooperate with one another to reach conclusions. Hence, we presented the formalization of a multi-agent system and the argument construction and semantics that define its reasoning approach. Using example scenarios, we demonstrated that our system enables the modeling of a broader range of scenarios than related work.