Overview and State-of-the-Art of Uncertainty Visualization

How Data Workers Cope with Uncertainty

“…Visualization tools were used by nine participants to support different tasks, e.g. P2 used Jigsaw [24] do nothing (P7) C: annotate to prevent data usage of erroneous records (P7) M: filter uncertain data; M: delete model that generates errors; A: improve acquisition source and tools; A: acquire data from multiple sources; R: group discussions^M: manual correction; C: set task constraints (P1, 3,5,6,7,8,11,12) Imprecision (8 participants) do nothing (P5) C: model uncertainty ; C: annotate data quality, confidence or possible range; R: compare to literature^C: set quality threshold (P1,2,9,12)…”

“…M: filter imprecise data; M: enrich with better quality data^A: improve acquisition^R: human expertise; M: aggregate data; R: prevent error propagation (P1, 3,7,9,11,12) Noise (4 participants) f P: plot data with uncertainty (P9) R: discuss with experts to identify noise^M: remove noise; C: compute threshold level^M: remove noise (P4,6,9,11) Table 3. Data uncertainty coping strategies by high level goals: Ignore, Understand and Minimise (Exploit is not shown as it only applies to missing data & imprecision).…”

“…When high level tasks are used, few authors justify their choice [19]. Recent reviews [19,18,3] on the exploration of uncertain data show an existing, large body of work that focuses on communication [17,12], collaboration [35,8] and user evaluations [4,34]. These reviews also highlight the need to focus on enabling reasoning and sense-making under uncertainty [25].…”

The reconstruction of drawn architecture

“…There is a wide range of definitions with reference to the various fields of knowledge and different approaches, some less generic than others, concerning both the uncertainty and the ways of representing it. There is, not surprisingly, a copious literature on this topic, including surveys of the problem [Edwards and Nelson, 2001;Otto et al, 2010;Bonneau et al, 2014;Masuch and Strothotte, 1998;Thomson et al, 2005;Brodlie et al, 2012;Pang et al, 1997;Pang and Furman, 1994;Boukhelifa and Duke, 2009]. …”

“…When uncertainty is due to a lack of knowledge, which means knowledge that in principle could be known, but in practice is not, we refer to the type of uncertainty called epistemic: it is subjective; it is uncertain due to errors that practically cannot be controlled and can be described by non-probabilistic modeling. [Bonneau et al, 2014] The reconstruction process, using a given set of documentary sources, requires a procedural pipeline based on a semantic system, able to define a set of preparatory and operational phasescomplementary between them-in order to investigate the sources and, when missing any information, the related or integrative references [Apollonio et al, 2013;Münster et al, 2016;PfarrHarfst, 2016].…”