PROVIDEDH - PROgressive Visual DEcision-Making in Digital Humanities

The PROVIDEDH project (PROgressive VIsual DEcision-Making in Digital Humanities) aims to provide visual interactive tools that convey the degree of uncertainty of the datasets and computational models used behind, designed to progressively adapt the visualizations to incorporate the new, more complete or more accurate data. It aims to give DH scholars a space to explore and assess the completeness and evolution of the involved research objects, the degree of uncertainty that the models applied to the data incorporate, and to share their perspectives and insights to other stakeholders of society. PROVIDEDH revolves around two key scientific questions: 1. Is it possible to assess the degree of uncertainty that a particular DH dataset incorporates, tracking such degree during the evolution of the dataset and how it is affected when different computational models are applied to it? 2. Is it possible to convey this evolution of uncertainty by means of interactive multimodal interfaces that progressively adapt to the moment in which they are used and permit the users to make decisions accordingly? The methods used include state-of-the-art computational methods in computer science and data visualisation, together with Open Innovation, Design Thinking and Citizen Science approaches. With this cross-disciplinary approach we aim at fostering ecosystem centric networks, contributing to the sustainability and accuracy of the data as well as reproducibility of workflows. The novelity of the proposed project lies in its interdisciplinary approach combining state of the art methods in computer science and visualisation methods on the one hand, and Open Innovation approaches, methods in Design thinking and the involvement of Citizen Science from the Digital Humanities perspectives on the other. This cross-disciplinary approach to data treatment, dissemination and access makes results more sustainable, provides better and wider-reaching access as well more accurate data.