The intersection of visualization and the humanities (VIS*H) is marked by a tension between chasing analytical "insight" and interpretive "meaning." The effectiveness of visualization techniques hinges on established evaluation frameworks that assess both analytical utility and communicative efficacy, creating a potential mismatch with the non-positivist, interpretive aims of humanities scholarship. To examine how this tension manifests in practice, we systematically surveyed 171 VIS*H design studies to analyze their evaluation workflows and rigor according to standard practice. Our findings reveal recurring flaws, such as an over-reliance on monomethod approaches, and show that higher-quality evaluations emerge from workflows that effectively triangulate diverse evidence. From these findings, we derive recommendations to refine quality and validation criteria for humanities visualizations, and juxtapose them to ongoing critical debates in the field, ultimately arguing for a paradigm shift that can reconcile the advantages of established validation techniques with the interpretive depth required for humanistic inquiry.

In digital humanities (DH) and cultural heritage (CH), visualization-based storytelling (VBS) has become an important approach for structuring, interpreting, and communicating cultural data and research results. The specific characteristics of these domains – historically oriented data, high levels of semantic ambiguity and uncertainty, interpretive rather than purely analytical goals, and deep expertise in narrative theory and practice – create both distinct requirements for VBS design and distinct opportunities that existing frameworks and tools only partially address. Yet the body of work that has emerged in response to these requirements remains scattered across disciplines and venues, with no systematic account of current practice and no consolidated view of open challenges.Against this backdrop, we survey DH and CH work on story designs and VBS tools to identify trends and recurring patterns, promising practices, and open challenges. We contribute by (1) synthesizing storytelling design spaces into a framework tailored to VBS in DH and CH, (2) mapping existing approaches to generate a field-level picture of practices and gaps, and (3) highlighting future areas of concern and inquiry for VBS in relation to domain-specific epistemic questions. Overall, this survey seeks to consolidate an emerging community of practice and offer a shared analytical foundation for future research and design.

Visualizing big and complex multivariate data is challenging. To address this challenge, we propose flexible visual analytics (FVA) with the aim to mitigate visual complexity and interaction complexity challenges in visual analytics, while maintaining the strengths of multiple perspectives on the studied data. At the heart of our proposed approach are transitions that fluidly transform data between user-relevant views to offer various perspectives and insights into the data. While smooth display transitions have been already proposed, there has not yet been an interdisciplinary discussion to systematically conceptualize and formalize these ideas. As a call to further action, we argue that future research is necessary to develop a conceptual framework for flexible visual analytics. We discuss preliminary ideas for prioritizing multi-aspect visual representations and multi-aspect transitions between them, and consider the display user for whom such depictions are produced and made available for visual analytics. With this contribution we aim to further facilitate visual analytics on complex data sets for varying data exploration tasks and purposes based on different user characteristics and data use contexts.

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.

Cultural heritage exhibitions commonly have to arrange a high amount of diverse artefacts and associated information in architecturally complex facilities. This constellation issues challenges to both: exhibition designers who have to find ways to deal with spatial restrictions and visitors who often experience cognitive overload and museum fatigue due to the high amount of information available. Against this background, the article is focusing on the question, how information visualization can serve as advance organizer, to make the organizing principles of cultural heritage exhibitions (like common topics, themes, geographical or temporal origin) transparent to the visitors. For this purpose, we extend the visualization method of time geography to an interactive visualization framework of time topography, which can support the interactive exploration of conceptual and physical cultural heritage exhibition spaces in parallel.

Visual analytics emphasizes the interplay between visualization, analytical procedures performed by computers and human perceptual and cognitive activities. Human reasoning is an important element in this context. There are several theories in psychology and HCI explaining open-ended and exploratory reasoning. Five of these theories (sensemaking theories, gestalt theories, distributed cognition, graph comprehension theories and skill-rule-knowledge models) are described in this paper. We discuss their relevance for visual analytics. In order to do this more systematically, we developed a schema of categories relevant for visual analytics research and evaluation. All these theories have strengths but also weaknesses in explaining interaction with visual analytics systems. A possibility to overcome the weaknesses would be to combine two or more of these theories.

Many real-world problems involve time-oriented data. Time data is different from other kinds of data--explicitly harnessing the structures of time in visualizations can guide and support users’ visual analysis processes. State-of-the-art visualizations hardly take advantage of the structures of time to aid users in understanding and exploring the data. To bring more flexibility to the analysis process, we have developed interactive visual methods incorporating the structures of time within a pixel-based visualization called GROOVE (granular overview overlay). GROOVE uses different techniques to visualize time-oriented data by overlaying several time granularities in one visualization and provides interactive operators, which utilize the structures of time in different ways to capture and explore time-oriented data.