Abstract
Since the advent of artificial intelligence, researchers have been trying to create machines that emulate human behaviour. Back in the 1960s however, Licklider (IRE Trans Hum Factors Electron 4-11, 1960) believed that machines and computers were just part of a scale in which computers were on one side and humans on the other (human computation). After almost a decade of active research into human computation and crowdsourcing, this paper presents a survey of crowdsourcing human computation systems, with the focus being on solving micro-tasks and complex tasks. An analysis of the current state of the art is performed from a technical standpoint, which includes a systematized description of the terminologies used by crowdsourcing platforms and the relationships between each term. Furthermore, the similarities between task-oriented crowdsourcing platforms are described and presented in a process diagram according to a proposed classification. Using this analysis as a stepping stone, this paper concludes with a discussion of challenges and possible future research directions.

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.