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Visual Analytics in Data-driven Journalism (VALID)


Abstract

Like many other organizations, publishing houses and the news industry are facing tremendous challenges in making sense of the ever-growing amount of information. The goal of this project is to substantially improve Visual Analytics (VA) technologies to support the investigation of complex and heterogeneous data sources in Data-Driven Journalism (DDJ). The emphasis hereby will be on bridging three DDJ gaps we identified: the usage gap (usable systems), the technology gap (dealing with complex heterogeneous data), and the workflow gap (facilitating DDJ in daily newsroom routines) while focusing specifically on (1) time-oriented text and (2) time-oriented network data. To achieve this, a user-centered and problem-driven design and evaluation approach will ensure the practical utility and usability of the intended methods and concepts, which will be bundled and evaluated in form of a research prototype. The collaboration with prestigious Austrian media outlets and the future integration into the business partner’s IT service portfolio will guarantee the sustainable exploitation of results as well as the economic strengthening of the media landscape.

Funding by FFG ICT of the Future

Further details
Type
R&D projects, public funding
Duration
2015 - 2017
Executive
Research Group Visualization and Data Analysis
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Faculty of Computer Science
University of Vienna

Währinger Straße 29
A-1090 Vienna