Known Unknowns: Representing Uncertainty in Historical Time

Kräutli, Florian; Davis, Stephen Boyd

doi:10.14236/ewic/eva2013.16

Cited by 9 publications

(11 citation statements)

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“…Given this growing number of visualization interfaces to cultural collections, it is noteworthy how a few of them take the sometimes-substantial amounts of data uncertainty into account and make them explicit [8]. If we find such work, it mainly focuses on one single data dimension: the temporal dimension of object information (e.g., [26,27]). While this focus on time seems to correlate with the factual relevance of this dimension in cultural heritage and history domains [28], it is obviously not the only dimension where uncertainties exist and where their representation could help to make the factual state of cultural information and knowledge more transparent.…”

Section: Related Workmentioning

confidence: 99%

“…Time has been argued to be the primary data dimension for cultural heritage collections, which could be productively combined with every other analytical perspective [28]. Yet, "especially when dealing with historic time, dates are often unknown or uncertain" ( [26], p. 62). As such, information on temporal origins of cultural objects can (1) lack accuracy or be imprecise, which can result from different temporal granularities and estimates (days, years, centuries, epochs) or from some level of probability assigned ("about", "approx.…”

Section: Temporal Uncertaintymentioning

confidence: 99%

“…", "circa"). Furthermore, temporal information can be (2) ambivalent (e.g., it is often unclear whether the recorded date refers to the production, use, or sale of an object [26]) or (3) contested, due to assessments from different experts or age determination methods. (4) Finally, temporal information can be completely absent or missing for a given object.…”

Section: Temporal Uncertaintymentioning

confidence: 99%

“…Options for visualization: As for the large (second) class of imprecise time information, it is often challenging to quantify or formalize the corresponding entries so that they can also be visualized [26]-without losing any information. To visualize uncertain temporal data, Kräutli proposed to keep the temporal granularity as entered in the database (not try to transfer years to days, which might result in an accumulation of objects on the 1st of January) and to calculate a probability value for the uncertainties.…”

Section: Temporal Uncertaintymentioning

confidence: 99%

“…To visualize uncertain temporal data, Kräutli proposed to keep the temporal granularity as entered in the database (not try to transfer years to days, which might result in an accumulation of objects on the 1st of January) and to calculate a probability value for the uncertainties. Such probabilities can be either visualized by all available standard techniques to modify glyphs (see Figure 4, top row), or-in cases where linear axes are used for the encoding of time-with linear extensions in combination with uncertainty indicators, such as opacity, dashed lines, or wavelength (see Figure 4, center row) [26,29].…”

Section: Temporal Uncertaintymentioning

confidence: 99%

See 4 more Smart Citations

Exhibiting Uncertainty: Visualizing Data Quality Indicators for Cultural Collections

2019

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Uncertainty is a standard condition under which large parts of art-historical and curatorial knowledge creation and communication are operating. In contrast to standard levels of data quality in non-historical research domains, historical object and knowledge collections contain substantial amounts of uncertain, ambiguous, contested, or plainly missing data. Visualization approaches and interfaces to cultural collections have started to represent data quality and uncertainty metrics, yet all existing work is limited to representations for isolated metadata dimensions only. With this article, we advocate for a more systematic, synoptic and self-conscious approach to uncertainty visualization for cultural collections. We introduce omnipresent types of data uncertainty and discuss reasons for their frequent omission by interfaces for galleries, libraries, archives and museums. On this basis we argue for a coordinated counter strategy for uncertainty visualization in this field, which will also raise the efforts going into complex interface design and conceptualization. Building on the PolyCube framework for collection visualization, we showcase how multiple uncertainty representation techniques can be assessed and coordinated in a multi-perspective environment. As for an outlook, we reflect on both the strengths and limitations of making the actual wealth of data quality questions transparent with regard to different target and user groups.

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Section: Related Workmentioning

confidence: 99%

Section: Temporal Uncertaintymentioning

confidence: 99%

Section: Temporal Uncertaintymentioning

confidence: 99%

Section: Temporal Uncertaintymentioning

confidence: 99%

Section: Temporal Uncertaintymentioning

confidence: 99%

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Exhibiting Uncertainty: Visualizing Data Quality Indicators for Cultural Collections

2019

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Can I believe what I see? Data visualization and trust in the humanities

Davis

Vane

Kräutli

2021

Interdisciplinary Science Reviews

Self Cite

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Questions of trust are increasingly important in relation to data and its use. The authors focus on humanities data and its visualization, through analysis of their own recent projects with museums, archives and libraries internationally. Their account connects the specifics of hands-on digital humanities work to larger epistemological questions. They discuss the sources of potential mistrust, and examine how different expectations and assumptions emerge depending on the use and user of the data; they offer a simple schema through which the implications may be traced. It is argued that vital issues of trust can be engaged with through design, which, rather than being conceived as a cosmetic finish, is seen as contributing insights and questions that affect the whole process. The article concludes with recommendations intended to be useful in both theory and practice.

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Communicating Uncertainty in Digital Humanities Visualization Research

Panagiotidou

Lamqaddam

Poblome

et al. 2022

IEEE Trans. Visual. Comput. Graphics

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Due to their historical nature, humanistic data encompass multiple sources of uncertainty. While humanists are accustomed to handling such uncertainty with their established methods, they are cautious of visualizations that appear overly objective and fail to communicate this uncertainty. To design more trustworthy visualizations for humanistic research, therefore, a deeper understanding of its relation to uncertainty is needed. We systematically reviewed 126 publications from digital humanities literature that use visualization as part of their research process, and examined how uncertainty was handled and represented in their visualizations. Crossing these dimensions with the visualization type and use, we identified that uncertainty originated from multiple steps in the research process from the source artifacts to their datafication. We also noted how besides known uncertainty coping strategies, such as excluding data and evaluating its effects, humanists also embraced uncertainty as a separate dimension important to retain. By mapping how the visualizations encoded uncertainty, we identified four approaches that varied in terms of explicitness and customization. This work contributes with two empirical taxonomies of uncertainty and it's corresponding coping strategies, as well as with the foundation of a research agenda for uncertainty visualization in the digital humanities. Our findings further the synergy among humanists and visualization researchers, and ultimately contribute to the development of more trustworthy, uncertainty-aware visualizations.

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Known Unknowns: Representing Uncertainty in Historical Time

Cited by 9 publications

References 0 publications

Exhibiting Uncertainty: Visualizing Data Quality Indicators for Cultural Collections

Exhibiting Uncertainty: Visualizing Data Quality Indicators for Cultural Collections

Can I believe what I see? Data visualization and trust in the humanities

Communicating Uncertainty in Digital Humanities Visualization Research

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