Abstract
In a world overwhelmed by constant data creation and manipulation, where privacy is becoming a real concern, topics like data usage control, accountability, provenance, protected sharing of resources and trustworthiness of knowledge sources are becoming main topics of discussion among communities of interest. In this paper enhancements are proposed for an existing framework that tackles some of the afore mentioned issues namely data provenance, usage control and accountability. Such proposals consist of providing means for publishing resources in a private manner hereby making websites behave like meshes of hyperlinked resources from different domains, not only for resources publicly published but also for the ones protected by access policies. © 2014, Society, Privacy and the Semantic Web Policy and Technology.

Abstract
In agent mediated electronic commerce the diversity of the involved actors can lead to diff erent conceptualizations of their needs and capabilities giving rise to semantic incompatibilities that might hamper negotiations and the fulfilling of satisfactory transactions. In order to provide help in the conversation among diff erent agents, these systems should provide ontology services, more specifically, ontology matching services. However, given the natural ambiguity of the ontology matching process, raising the possibility of multiple alignments between the same pair of ontologies, it is necessary to choose the one that best meets the interests of both agents. On the other hand, agents may possess diff erent interests, therefore the ontology alignment may also become the object of further negotiation. In this context, the application and exploitation of relationships captured in social networks can result in the establishment of more accurate adequacy relations of ontology alignments to agents, as well as the improvement of the negotiations' efficiency and, consequently, the users' satisfaction with the electronic commerce system. In this paper we present the AEMOS system which follows an ontology-based information integration approach, exploiting the ontology matching paradigm, improved by the application and exploitation of the relationships captured in the social networks. Copyright © 2014, Australian Computer Society Inc.

Abstract
With the growing popularity of micro-task crowdsourcing platforms, new workflow-based micro-task crowdsourcing approaches are starting to emerge. Such workflows occur in legal, political and conflict resolution domains as well, presenting new challenges, namely in micro-task specification and human-machine interaction, which result mostly from the flow of unstructured data. Domain ontologies provide the structure and semantics required to describe the data flowing throughout the workflow in a way understandable to both humans and machines. This paper presents a method for the construction of micro-task workflows from legal domain ontologies. The method is currently being employed in the context of the UMCourt project in order to formulate information retrieval and conflict resolution workflows.

Abstract
Computational systems operating in open, dynamic and decentralized environments are required to share data with previously unknown computational systems. Due to this ill specification and emergent operation the systems are required to share the data's respective schemas and semantics so that the systems can correctly manipulate, understand and reason upon the shared data. The schemas and semantics are typically provided by ontologies using specific semantics provided by the ontology language. Because computational systems adopt different ontologies to describe their domain of discourse, a consistent and compatible communication relies on the ability to reconcile (in run-time) the vocabulary used in their ontologies. Since each computational system might have its own perspective about what are the best correspondences between the adopted ontologies, conflicts can arise. To address such conflicts, computational systems may engage in any kind of negotiation process that is able to lead them to a common and acceptable agreement. This paper proposes an argumentation-based approach where the computational entities describe their own arguments according to a commonly agreed argumentation meta-model. In order to support autonomy and conceptual differences, the community argumentation model can be individually extended yet maintaining computational effectiveness. Based on the formal specification, a software development framework is proposed.

Abstract
With the growing popularity of micro-task crowdsourcing platforms, a renewed interest in the resolution of complex tasks that require the cooperation of human and machine participants has emerged. This interest has led to workflow approaches that present new challenges at different dimensions of the human-machine computation process, namely in micro-task specification and human-computer interaction due to the unstructured nature of micro-tasks in terms of domain representation. In this sense, a semi-automatic generation environment for human-computer micro-task workflows from domain ontologies is proposed. The structure and semantics of the domain ontology provides a common ground for understanding and enhances human-computer cooperation.

Abstract
Nowadays, there are many technologies that support location systems involving intrusive and nonintrusive equipment and also varying in terms of precision, range, and cost. However, the developers some time neglect the noise introduced by these systems, which prevents these systems from reaching their full potential. Focused on this problem, in this research work a comparison study between three different filters was performed in order to reduce the noise introduced by a location system based on RFID UWB technology with an associated error of approximately 18 cm. To achieve this goal, a set of experiments was devised and executed using a miniature train moving at constant velocity in a scenario with two distinct shapes-linear and oval. Also, this train was equipped with a varying number of active tags. The obtained results proved that the Kalman Filter achieved better results when compared to the other two filters. Also, this filter increases the performance of the location system by 15% and 12% for the linear and oval paths respectively, when using one tag. For a multiple tags and oval shape similar results were obtained (11-13% of improvement).