After decades of digitization, large cultural heritage collections have emerged on the web, which contain massive stocks of content from galleries, libraries, archives, and museums. This increase in digital cultural heritage data promises new modes of analysis and increased levels of access for academic scholars and casual users alike. Going beyond the standard representations of search-centric and grid-based interfaces, a multitude of approaches has recently started to enable visual access to cultural collections, and to explore them as complex and comprehensive information spaces by the means of interactive visualizations. In contrast to conventional web interfaces, we witness a widening spectrum of innovative visualization types specially designed for rich collections from the cultural heritage sector. This new class of information visualizations gives rise to a notable diversity of interaction and representation techniques while lending currency and urgency to a discussion about principles such as serendipity, generosity, and criticality in connection with visualization design. With this survey, we review information visualization approaches to digital cultural heritage collections and reflect on the state of the art in techniques and design choices. We contextualize our survey with humanist perspectives on the field and point out opportunities for future research.
Recent research supports that a person’s self-reported explicit attitude is not necessarily consistent with their implicit attitude. However, in sustainability research, implicit cognitive measures are still at their early stages, and consider primarily singular aspects of sustainability. Here, we pose that the degree of congruence of individuals’ implicit and explicit attitudes represents the foundation of any organization’s sustainability culture. Although many organizations assert that sustainable development represents an important dimension of their vision and strategy, in reality, sustainable development often translates simply into explicit self-presentation and reputation. Traditional methods such as surveys lack information on implicit measures and—since they collect data based solely on the explicit knowledge of the respondents, which may be biased by social desirability and impression management—can therefore not determine the degree of congruence between explicit and implicit attitudes. We implemented a browser-based application of the Implicit Association Test (IAT) regarding sustainability as a reaction time-based cognitive measure supported by an interactive and activating process that was completed by 114 executives. Additionally, a questionnaire-based survey was conducted among them to investigate their explicit attitudes. We calculated Pearson correlation coefficients and conducted repeated measures MANOVA and principle component analysis. Our data analysis demonstrated low congruence between explicit and implicit sustainability orientations (Pearson’s r ranging from − 0.10 to 0.31). Potential explanations for our findings relate to the effects of impression management and individuals’ lack of cognitive processing of their own sustainability orientation. In sum, exploring the potential incongruence between explicit and implicit sustainability orientations helps narrow an important knowledge gap and provides a basis for rethinking the impact of internal and external learning processes within and between organizational systems, society, and science.
Various studies have indicated that unaccompanied minor refugees (UMRs) have a higher risk of suffering from mental health problems than do accompanied minor refugees and general population norm. However, only a few studies provide data on UMRs regarding post-migration risk factors, their interrelations, and their influence on mental health. In this study, system models of post-migration risk factors for mental health and their interactions were developed in the case of Austria. In three consecutive interactive workshops with scientists and practitioners, fuzzy-logic cognitive mapping techniques were used to integrate the experts’ knowledge. The resulting final system model consists of 11 risk factors (e.g., social contacts in the host country, housing situation, or professional health care services). The model provides a deeper insight into the complexity of interrelated direct, indirect, and reciprocal relations, as well as self-reinforcing triads. This systemic approach provides a sound basis for further investigations, taking into account the inherent complex multifactorial dependencies in this topic.
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