HisVA: A Visual Analytics System for Studying History

Han, Dongyun; Parsad, Gorakh; Kim, Hwiyeon; Shim, Jaekyom; Kwon, Oh-Sang; Son, Kyung A; Lee, Jooyoung; Cho, Isaac; Ko, Sungahn

doi:10.1109/tvcg.2021.3086414

Cited by 8 publications

(7 citation statements)

References 41 publications

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“…The consistent color encoding across the entire interface allows easy navigation. This ability to explore relationships in the lives of historical figures can be applied in education, as demonstrated by the usage scenarios of the HisVA system [9].…”

Section: Discussionmentioning

confidence: 99%

“…Leskinen et al [17] built visualizations enabling faceted search of the biographical data. Some recent works (e.g., [8,9,11]) visualize biographical data enriched with events in the lifespans of historical figures. However, unlike our approach, these techniques do not explicitly represent the shared events connecting the lives of historical figures in the proposed visualizations.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Visually Connecting Historical Figures Through Event Knowledge Graphs

Latif¹,

Agarwal²,

Gottschalk³

et al. 2021

Preprint

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Figure 1: VisKonnect interface visualizing the result of a query on soccer players: (A) An event timeline shows individual (uni-colored rectangles) and shared (multi-colored rectangles) life events of all historical figures in a user query. (B) An event map provides a geographic perspective of those events. (C) A relationship graph provides an overview of all shared events. (D) Clicking an event brings up a related article from Wikipedia. (E) A chat interface enables typing in a query and generates a short textual answer.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Visually Connecting Historical Figures Through Event Knowledge Graphs

Latif¹,

Agarwal²,

Gottschalk³

et al. 2021

Preprint

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show abstract

“…Event sequences are typically visualized using timelines [GGJ * 21, CvW17,LWD * 16,WGW * 20,CXR17,YM22,HPK * 21], hierarchical visualizations [GGJ * 21, WGGP * 11, WG12, GS14, LWD * 16, JGC * 20, YM22], matrix visualizations [GGJ * 21, YM22], bar chart visualizations [GGJ * 21, MSD * 16], and Sankey flow diagrams [DBZSD20,KPS15,HLI * 15,GGJ * 21,MXC * 19,WMH * 21, YM22, WLS * 21]. Often, case metadata is displayed next to the main visualization serving as a filter [KPS15, GS14, JGC * 20, MXC * 19,WLS * 21].…”

Section: Related Workmentioning

confidence: 99%

FlexEvent: going beyond Case‐Centric Exploration and Analysis of Multivariate Event Sequences

Linden

Wulterkens

Gilst

et al. 2023

Computer Graphics Forum

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In many domains, multivariate event sequence data is collected focused around an entity (the case). Typically, each event has multiple attributes, for example, in healthcare a patient has events such as hospitalization, medication, and surgery. In addition to the multivariate events, also the case (a specific attribute, e.g., patient) has associated multivariate data (e.g., age, gender, weight). Current work typically only visualizes one attribute per event (label) in the event sequences. As a consequence, events can only be explored from a predefined case‐centric perspective. However, to find complex relations from multiple perspectives (e.g., from different case definitions, such as doctor), users also need an event‐ and attribute‐centric perspective. In addition, support is needed to effortlessly switch between and within perspectives. To support such a rich exploration, we present FlexEvent: an exploration and analysis method that enables investigation beyond a fixed case‐centric perspective. Based on an adaptation of existing visualization techniques, such as scatterplots and juxtaposed small multiples, we enable flexible switching between different perspectives to explore the multivariate event sequence data needed to answer multi‐perspective hypotheses. We evaluated FlexEvent with three domain experts in two use cases with sleep disorder and neonatal ICU data that show our method facilitates experts in exploring and analyzing real‐world multivariate sequence data from different perspectives.

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“…The idea of self-guided learning and knowledge acquisition via digital tools in history has been explored in several prior publications. Visual analytics systems like POLIS [14], VAiRoma [2], and HisVA [9] follow the same approach to help people explore historical datasets by providing individual overviews, mostly consisting of traditional and well-known visualization methods like data tables, timelines or map views, and revealing relationships among events that may not be directly apparent. Each of these approaches focuses on a specific topic, but the presented concepts can also be transferred to different datasets.…”

Section: Interactive Exploration Of Historical Data In 2dmentioning

confidence: 99%

“…To assist learners with this process, several digital tools have been proposed that provide curated interactive visualizations like maps, timelines, or graphs. While some tools like Palladio 1 are more tailored to the purpose of presenting finished research results, others like HisVA [9] focus on an active learning process while interacting with the data, which is claimed to be more beneficial than traditional textbook-based learning. However, historical exploration tools to date are mostly based on classic 2D visualizations which are inherently optimized for demonstrating attribute relationships along only one or two spatial dimensions.…”

Section: Introductionmentioning

confidence: 99%

Who Did What When? Discovering Complex Historical Interrelations in Immersive Virtual Reality

Derksen,

Becker,

Elahi

et al. 2023

2023 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)

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Figure 1: We present a tool for exploring historical data in VR using a head-mounted display. Left: The user is placed on a platform representing the main historical fragment (e.g., a person or an event) of their research (here Albert Einstein). Other related fragments are represented as colored labeled spheres and are arranged around the user based on their historical interrelationships. Users can select a sphere to make it the new main fragment, thereby allowing for an immersive exploration of the dataset. Right: For every sphere, a detail window with more information on the corresponding fragment can be opened. An exploration history in the lower field of view shows the order of visited main fragments (here Physics and Erwin Schr ödinger ). If a sphere is marked, a corresponding mark appears on a compass view in the upper field of view (e.g., a blue mark for Albert Einstein). The relation details, here shown for Albert Einstein, Austria-Hungary, and Max Planck, reveal additional details about their historical connections.

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HisVA: A Visual Analytics System for Studying History

Cited by 8 publications

References 41 publications

Visually Connecting Historical Figures Through Event Knowledge Graphs

Visually Connecting Historical Figures Through Event Knowledge Graphs

FlexEvent: going beyond Case‐Centric Exploration and Analysis of Multivariate Event Sequences

Who Did What When? Discovering Complex Historical Interrelations in Immersive Virtual Reality

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