Abstract
Desktop video editing plays an important role in the digital video market, and cooperative applications are important for organizations. Cooperative video editing tools can be an interesting solution for large broadcasters or for remote reporting, and such commercial products are lacking. This paper describes a cooperative video editing tool, Coview, which uses Web services to provide the cooperative functionalities. For this purpose, an overview is given of the basic issues of Web Services and Computer Supported Cooperative Work. Then, the Web Services-based cooperative infrastructure and the Coview prototype is described. Finally, some experimental results and concluding remarks are presented.

Abstract
Distributed systems emerged in the last decade as a more efficient way of sharing networked resources, allowing cooperating processes to be executed in remote computers with possibly distinct architectures and operating systems. This paper presents the motivations that may lead to the usage of distributed architectures in the support of telecommunications services, particularly multimedia services. It also gives an overview of one distributed architecture, ANSA, which was used to implement a prototype of a distributed multimedia service, briefly described.

Abstract
Solid research depends on systematic, verifiable and repeatable scientometric analysis. However, scientometric analysis is difficult in the current research landscape characterized by the increasing number of publications per year, intersections between research domains, and the diversity of stakeholders involved in research projects. To address this problem, we propose SciCrowd, a hybrid human-AI mixed-initiative system, which supports the collaboration between Artificial Intelligence services and crowdsourcing services. This work discusses the design and evaluation of SciCrowd. The evaluation is focused on attitudes, concerns and intentions towards use. This study contributes a nuanced understanding of the interplay between algorithmic and human tasks in the process of conducting scientometric analysis.

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Abstract
With the widespread availability and pervasiveness of artificial intelligence (AI) in many application areas across the globe, the role of crowdsourcing has seen an upsurge in terms of importance for scaling up data-driven algorithms in rapid cycles through a relatively low-cost distributed workforce or even on a volunteer basis. However, there is a lack of systematic and empirical examination of the interplay among the processes and activities combining crowd-machine hybrid interaction. To uncover the enduring aspects characterizing the human-centered AI design space when involving ensembles of crowds and algorithms and their symbiotic relations and requirements, a Computer-Supported Cooperative Work (CSCW) lens strongly rooted in the taxonomic tradition of conceptual scheme development is taken with the aim of aggregating and characterizing some of the main component entities in the burgeoning domain of hybrid crowd-AI centered systems. The goal of this article is thus to propose a theoretically grounded and empirically validated analytical framework for the study of crowd-machine interaction and its environment. Based on a scoping review and several cross-sectional analyses of research studies comprising hybrid forms of human interaction with AI systems and applications at a crowd scale, the available literature was distilled and incorporated into a unifying framework comprised of taxonomic units distributed across integration dimensions that range from the original time and space axes in which every collaborative activity take place to the main attributes that constitute a hybrid intelligence architecture. The upshot is that when turning to the challenges that are inherent in tasks requiring massive participation, novel properties can be obtained for a set of potential scenarios that go beyond the single experience of a human interacting with the technology to comprise a vast set of massive machine-crowd interactions.