Strengthening collaborative data analysis and decision making in web communities

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

Abstract: 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.