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Dive into the research topics where Spyros Christodoulou is active.

Publication


Featured researches published by Spyros Christodoulou.


International Journal of Web-based Learning and Teaching Technologies | 2009

Tackling Cognitively-Complex Collaboration with CoPe_it!

Nikos I. Karacapilidis; Manolis Tzagarakis; Nikos Karousos; George Gkotsis; Vassilis Kallistros; Spyros Christodoulou; Christos Mettouris

CoPe_it! is an innovative Web-based tool that complies with collaborative practices to provide members of communities with the appropriate means to manage individual and collective knowledge during a sense-making and/or decision-making session. In this article, we demonstrate its applicability in tackling cognitively-complex collaboration settings, which are characterized by big volumes of interrelated data obtained from diverse sources and knowledge expressed by diverse participants. We focus on issues related to the representation of such settings and propose an approach to make it easier for participants to follow the evolution of collaboration, comprehend it in its entirety, and meaningfully aggregate data to resolve the issue under consideration.


PLOS ONE | 2014

Collaborative Mining and Interpretation of Large-Scale Data for Biomedical Research Insights

Georgia Tsiliki; Nikos I. Karacapilidis; Spyros Christodoulou; Manolis Tzagarakis

Biomedical research becomes increasingly interdisciplinary and collaborative in nature. Researchers need to efficiently and effectively collaborate and make decisions by meaningfully assembling, mining and analyzing available large-scale volumes of complex multi-faceted data residing in different sources. In line with related research directives revealing that, in spite of the recent advances in data mining and computational analysis, humans can easily detect patterns which computer algorithms may have difficulty in finding, this paper reports on the practical use of an innovative web-based collaboration support platform in a biomedical research context. Arguing that dealing with data-intensive and cognitively complex settings is not a technical problem alone, the proposed platform adopts a hybrid approach that builds on the synergy between machine and human intelligence to facilitate the underlying sense-making and decision making processes. User experience shows that the platform enables more informed and quicker decisions, by displaying the aggregated information according to their needs, while also exploiting the associated human intelligence.


international world wide web conferences | 2014

Strengthening collaborative data analysis and decision making in web communities

Nikos I. Karacapilidis; Spyros Christodoulou; Manolis Tzagarakis; Georgia Tsiliki; Costas P. Pappis

Generally speaking, modern research becomes increasingly interdisciplinary and collaborative in nature. Researchers need to collaborate and make decisions by meaningfully assembling, mining and analyzing available large-scale volumes of complex multi-faceted data residing in different sources. At the same time, they need to efficiently and effectively exploit services available over the Web. Arguing that dealing with data-intensive and cognitively complex settings is not a technical problem alone, this paper presents a novel collaboration support platform for Web communities. The proposed solution adopts a hybrid approach that builds on the synergy between machine and human intelligence to facilitate the underlying sense-making and decision making processes. User experience shows that the platform enables stakeholders to make better, more informed and quicker decisions. The functionalities of the proposed platform are described through a real-world case from a biomedical research community.


Archive | 2014

The Dicode Collaboration and Decision Making Support Services

Manolis Tzagarakis; Nikos I. Karacapilidis; Spyros Christodoulou; Fan Yang-Turner; Lydia Lau

As broadly admitted, supporting collaboration and decision making in today’s knowledge intensive environment is far from being easy. This is because collaboration settings are often associated with ever-increasing amounts of multiple types of data, obtained from diverse sources that often have a low signal-to-noise ratio for addressing the problem at hand. Towards addressing such concerns, we have developed a series of innovative collaboration and decision making services in the context of the Dicode project. The adopted approach facilitates and augments sense-making and decision making by incrementally formalizing the collaboration context.


Archive | 2011

Building on the Synergy of Machine and Human Reasoning to Tackle Data-Intensive Collaboration and Decision Making

Nikos I. Karacapilidis; Stefan Rüping; Manolis Tzagarakis; Axel Poigné; Spyros Christodoulou

This paper reports on a hybrid approach aiming to facilitate and augment collaboration and decision making in data-intensive and cognitively-complex settings. The proposed approach exploits and builds on the most prominent high-performance computing paradigms and large data processing technologies to meaningfully search, analyze and aggregate data existing in diverse, extremely large and rapidly evolving sources. It can be viewed as an innovative workbench incorporating and orchestrating a set of interoperable services that reduce the data-intensiveness and complexity overload at critical decision points to a manageable level, thus permitting stakeholders to be more productive and concentrate on creative activities.


Archive | 2014

Data Intensiveness and Cognitive Complexity in Contemporary Collaboration and Decision Making Settings

Spyros Christodoulou; Nikos I. Karacapilidis; Manolis Tzagarakis; Vania Dimitrova; Guillermo de la Calle

This chapter reviews the state-of-the-art on collaboration and decision making support in contemporary settings. Related issues concerning integration technologies are also discussed. The methodologies, tools and approaches discussed in the chapter are considered with respect to the information overload and cognitive complexity dimensions. The chapter aims to provide useful insights concerning the exploitation and advancement of existing collaboration and decision making support technologies.


Archive | 2014

Collaboration and Decision Making in Data-Intensive and Cognitively-Complex Settings: Lessons Learned from the Dicode Project

Spyros Christodoulou; Manolis Tzagarakis; Nikos I. Karacapilidis; Fan Yang-Turner; Lydia Lau; Vania Dimitrova

This chapter reports on practical lessons learned during the development of innovative collaboration and decision making support services in the context of the Dicode project. These lessons concern: (i) the methodology followed and process carried out for the development of the abovementioned Dicode services (ii) the facilitation and enhancement of collaboration and decision making in data intensive and/or cognitively complex settings, and (iii) related technological and integration issues. Detailed evaluation reports, interviews and discussions within the development teams, as well as analysis of the use of the developed services by end-users through the associated log files, provided valuable feedback for the formulation and compilation of these lessons. By sharing insights gained in the context of the Dicode project, this chapter aims to help people engaged in developing similar services.


Archive | 2016

Exploiting Alternative Knowledge Visualizations and Reasoning Mechanisms to Enhance Collaborative Decision Making

Spyros Christodoulou; Nikos I. Karacapilidis; Manolis Tzagarakis

Collaborative decision making in today’s knowledge intensive and multi-disciplinary environments is a challenging task. The diversity of these environments and the associated plurality of decision makers’ perceptions of the issue under consideration require the exploitation of a variety of meaningful knowledge visualizations and reasoning mechanisms to effectively support the overall stakeholders’ collaboration towards making a decision. This chapter reports on an innovative approach that offers a number of interrelated visualizations of the knowledge exchanged and shared during a collaborative decision making process. These visualizations incorporate suitable reasoning mechanisms that exploit human and machine understandable knowledge to facilitate the underlying what-if analysis and aid stakeholders towards reaching consensus and, ultimately, making a collective decision.


computer-based medical systems | 2012

On a meaningful integration of web services in data-intensive biomedical environments: The DICODE approach

Guillermo de la Calle; Miguel García-Remesal; Manolis Tzagarakis; Spyros Christodoulou; Georgia Tsiliki; Nikos I. Karacapilidis

This paper reports on an innovative approach that aims to reduce information management costs in dataintensive and cognitively-complex biomedical environments. Recognizing the importance of prominent high-performance computing paradigms and large data processing technologies as well as collaboration support systems to remedy data-intensive issues, it adopts a hybrid approach by building on the synergy of these technologies. The proposed approach provides innovative Web-based workbenches that integrate and orchestrate a set of interoperable services that reduce the data-intensiveness and complexity overload at critical decision points to a manageable level, thus permitting stakeholders to be more productive and concentrate on creative activities.


2011 10th International Workshop on Biomedical Engineering | 2011

Facilitating scientific collaboration in data-intensive biomedical settings

Nikos I. Karacapilidis; Manolis Tzagarakis; Spyros Christodoulou; Georgia Tsiliki

This paper reports on a Web 2.0 tool that aims to facilitate collaboration in data-intensive biomedical settings. The proposed tool can be viewed as an innovative workbench incorporating and orchestrating a set of interoperable services that reduce the data-intensiveness and complexity overload at critical decision points to a manageable level, thus permitting stakeholders to be more productive and concentrate on creative activities. Through a particular collaboration scenario, we explore various possibilities and challenges of managing biomedical collaboration with the use of the proposed tool.

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Nikos Karousos

Hellenic Open University

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Dora Nousia

Research Academic Computer Technology Institute

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