Data Visualization Competition Introduction

The Data Visualization Competition is an important part of the China Visualization and Visual Analytics Conference. The competition invites researchers, developers, students, and enthusiasts to use their most effective visualization and Visual Analytics techniques/tools to accomplish data analysis as well as visualization tasks. The competition aims to evaluate the effectiveness, novelty, and artistry of their techniques and tools in solving complex problems, and promote the development and advancement of research and applications related to visualization and Visual Analytics in China.

Data Visualization Competition Content

The Data Visualization Competition offers two tracks, of which the participants can choose the corresponding topic to compete. Each track has its own judges.

Track 1: Data Visualization Challenge

I: Data Visual Analytics and Humanities & Creativity Competition

Peking Opera (Jingju), as an important representative of traditional Chinese performing arts, integrates multiple elements including literature, performance, music, fine arts, and historical culture, carrying rich character development, narrative structures, and cultural expressions. A large number of Peking Opera scripts not only record the evolution process of classical stage art but also reflect social concepts, value systems, and aesthetic characteristics across different historical periods. With the advancement of digital preservation efforts, the scale and completeness of Peking Opera script text data continue to improve, providing new opportunities for computational analysis and visualization research of traditional opera.

This task is based on a Peking Opera script dataset and encourages participants to combine natural language processing, complex network analysis, temporal analysis, and visualization methods to conduct systematic analysis and visual exploration of Peking Opera scripts from multiple perspectives including character relationships, thematic expression, narrative structure, and version evolution. Participants should not only focus on the textual structure and artistic features within individual scripts but also conduct cross-script, cross-source, and cross-genre comparative analysis to uncover potential structural patterns, cultural connections, and evolutionary trends among Peking Opera scripts.

The competition dataset includes Peking Opera data across different sources and genres. Additionally, participants may incorporate historical documents, performance materials, opera audio/video recordings, role type (hangdang) knowledge, or other open data to enhance analysis depth and research value. The competition encourages participants, while ensuring data accuracy, to integrate artificial intelligence and innovative visualization methods, promoting Peking Opera data research from traditional text interpretation toward data-driven humanities and intelligent analysis paradigms, and providing new possibilities for the digital preservation, academic research, and international dissemination of outstanding traditional Chinese culture.

Participants may choose one of the following tasks to complete.

Task One: 「Opera Rhyme, Myriad Phenomena」 Peking Opera Visual Analytics Competition

• Based on characters' gender, age, identity, personality descriptions, and performance cues (singing, recitation, acting, combat) in the scripts, infer the unlabeled role types (hangdang) of characters (such as Sheng, Dan, Jing, Chou and their subcategories), and analyze typical correspondence patterns between character features and role type classifications. Further, combined with the script creation period or historical background, use data analysis and visualization methods to explore the changing patterns of character-role type correspondence across different periods (recommended text: no more than 800 words; images: no more than 5).
• Identify interaction relationships among major characters in the scripts, construct character relationship networks, and analyze the structural characteristics of character relationship networks in different types of plays (historical plays, family plays, court case plays, etc.) (recommended text: no more than 800 words; images: no more than 5).
• Extract core themes from the scripts, analyze the thematic composition and combination patterns of different scripts. Through cross-script comparison, summarize the commonalities and differences in thematic expression, and explore whether there are representative thematic combination patterns and their characteristics (recommended text: no more than 800 words; images: no more than 5).
• Based on performance form markers and script content, conduct systematic analysis of the narrative structure of scripts, identify key stages in plot development, and characterize plot fluctuations and pacing changes. Further compare differences in narrative structure among different scripts, and summarize typical narrative patterns and their structural characteristics (recommended text: no more than 800 words; images: no more than 5).
• Building upon the above analyses, comprehensively analyze the association mechanisms and differential characteristics among character relationships, thematic structure, and narrative structure. For example, explore how specific character relationships carry and drive thematic expression, how thematic structure influences narrative strategies and plot organization, and how different narrative approaches reshape the presentation and evolution of character relationships. By constructing an interactive visual analytics system, explore whether there are typical association patterns, co-evolutionary laws, or stable structural characteristics among character relationships, thematic expression, and narrative approaches (recommended text: no more than 800 words; images: no more than 5).

Task Two: 「Opera Rhyme, Millennia of Heritage」 Peking Opera Visualization Creativity Competition

With the theme "Digital Heritage and Intelligent Expression of Peking Opera Culture," this task invites participants to conduct relevant analysis and creative design based on the Peking Opera script text dataset provided by the competition or self-selected extended datasets, and to complete their works within the specified timeframe.

Provided Data: For detailed information, please refer to Track 1-I Data.

II: Scientific Visualization Challenge

Exploring the formation of large-scale cosmic structures is a core topic in modern astrophysics. Nyx is a parallel adaptive mesh refinement (AMR) cosmological simulation code developed based on the AMReX framework. The Nyx cosmological simulation program uses compressible hydrodynamics and dark matter N-body simulation as its core to simulate cosmic evolution processes, with a focus on studying the intergalactic medium and Lyman-alpha forest phenomena. Unlike programs that explicitly track active galactic nucleus particles, Nyx employs adaptive mesh refinement technology to accurately solve Eulerian fluid dynamics processes in high-density regions while computing self-gravity. The low-density gas produced by its simulations fills the vast voids between galaxies and serves as the primary observational means for understanding dark energy, dark matter, and the thermal history of the universe.

In the Nyx dataset, the data for each timestep is stored in files using little-endian byte order and float32 format. The data is stored in column-major order, i.e., the z-axis data is stored first, followed by the y-axis data, and finally the x-axis data. Please complete the following tasks based on the provided Nyx dataset.

• Employ volume data rendering techniques, and design appropriate transfer functions and lighting effects to demonstrate the changes in density information during cosmic evolution (recommended text: no more than 800 words; images: no more than 5).
• Based on visualization image results, summarize the evolutionary characteristics of cosmic density, elucidate the core laws of cosmic structure formation and intergalactic medium evolution, and explain the application value of visualization technology in cosmological data analysis (recommended text: no more than 800 words; images: no more than 5).
• Cosmic Density Temporal Statistical Feature Analysis: In the early universe, matter distribution was relatively uniform, with density values highly concentrated around the mean. Under the continuous gravitational influence of dark matter over 100 evolution time steps, cosmic matter continuously aggregates and collapses, showing a significant "clumping" characteristic overall, with the fluctuation amplitude of density values continuously increasing, gradually forming a polarized distribution of extreme low-density cosmic voids and extreme high-density structure peaks. Independently calculate the gas density data for each time step, construct logarithmic density histograms, and quantitatively track the evolutionary shift patterns of the global density distribution over time (recommended text: no more than 800 words; images: no more than 5).
• Phase Space Interactive Brushing Visual Analytics: Build a linked interactive visual analytics dashboard to implement phase space-based filtering and analysis functions. Support users in custom box-selection of specific density intervals in statistical histograms, such as filtering the top 1% highest density interval. The system should be able to link in real-time with the 3D spatial view, quickly render physical cell data matching the density threshold, visually verify the correspondence between high-density tail data in histograms and the dense structures of cosmic web nodes, and achieve bidirectional associative analysis between statistical features and spatial physical structures (recommended text: no more than 800 words; images: no more than 5).

Provided Data: For detailed information, please refer to Track 1-II Data.

Note: The dataset for this track is designated. Please do not use self-selected datasets.

Track 2: Art Visualization Competition

The Art Visualization Competition is an important component of the China Visualization and Visual Analytics Conference, together with the Visual Analytics Challenge constituting the conference's Data Visualization Competition. It aims to promote exchange and cooperation in art visualization creation and research in China, and to advance talent cultivation. The Art Visualization Competition specifies a theme scope and invites domestic and international university students studying art, design, and visualization to use their most proficient expressive techniques to complete art visualization creations within a specified period. The competition sets up a series of awards to be presented to outstanding and innovative works.

The competition places no restrictions on expressive techniques, aiming to encourage students to maximize their imagination and creative freedom. Art visualization works must be based on real data, and original data excerpts should be provided as evaluation references. The evaluation criterion is whether the participating team can effectively express a data-based artistic idea, viewpoint, or concept through visual or auditory forms.

Submitted visualization works may contain AI-generated content. The use of new intelligent and digital technologies to explore and promote new methods in visualization creation processes and presentation forms is encouraged. However, please note that authors must clearly label and explain AI-generated content. The review committee will evaluate the relevance of generated content to the theme and whether it violates laws, ethics, and public order.

Annual Theme: Digital Intelligence in the Forest City, Green Rhyme Visualized

The theme for this year's art project is "Digital Intelligence in the Forest City, Green Rhyme Visualized." In an era of synergistic development between the digital economy and ecological civilization, the fusion of art and technology has become a new key to unlocking urban charm. The two complement each other, giving cold data warmth and making ecological textures visible and perceptible. Against this backdrop, data serves as both the core driving force of the "China Data Valley" and a vivid annotation of the forest city's ecology. Through visualization art techniques, Guiyang's computing power data and ecological data can be transformed into visual works that combine technological sophistication with natural beauty, showcasing the symbiotic beauty of "green content" and "innovation content."

As the "China Data Valley," Guiyang is a key hub in the "East Data West Computing" initiative, with intelligent computing accounting for over 98%. Massive data converges and flows here. At the same time, it is also a "Forest City" enveloped in greenery, where karst landforms and forest vegetation complement each other, and ecological civilization construction has achieved remarkable results. It is an excellent vehicle for showcasing the integration of digital intelligence technology and ecological nature. Guiyang's ecological foundation and digital strength vividly interpret the theme "Digital Intelligence in the Forest City, Green Rhyme Visualized." Its dual positioning as a digital economy innovation base in Southwest China and a national ecological leisure tourism destination makes it a frontier position for promoting the deep integration of visualization art, digital technology, and ecological civilization. At the same time, as the core city of the Central Guizhou Economic Zone, Guiyang carries the important mission of ecological innovation and green development in the digital age. Our goal is to rely on Guiyang's unique advantages to create a platform combining digital intelligence, ecological aesthetics, and creative art, and through co-creation, showcase the infinite possibilities of the symbiosis between ecology and technology in the digital age.

The 2026 13th China Visualization and Visual Analytics Conference Art Project (ChinaVISAP'26) Student Competition is now recruiting students currently enrolled in universities nationwide (both undergraduates and graduate students are eligible). This competition sincerely invites all students who love visualization art and design and are full of creativity to actively participate, showcasing the youthful perspective and diverse exploration in the visualization field. This student competition closely follows the annual theme "Digital Intelligence in the Forest City, Green Rhyme Visualized," requiring participating students to independently select relevant datasets within this theme scope for art visualization creation. The competition places no restrictions on creative expressive techniques, encouraging students to fully utilize their imagination and creativity, boldly break through and freely create, presenting their understanding and interpretation of "Digital Intelligence in the Forest City, Green Rhyme Visualized" through diverse visualization forms, and showcasing contemporary students' enthusiasm for exploration and wonderful creativity in the visualization field.

Works in this track will be reviewed by a panel of domestic art visualization experts. The evaluation principle is whether the participating team can effectively express a data-based artistic idea, viewpoint, or concept through visual, auditory, and other art forms.

Participation Guidelines

Registration Information

Faculty, students, and researchers from national universities (including vocational colleges) and research institutes, developers and designers from enterprises and institutions, as well as visualization and visual analytics enthusiasts and artists are welcome to participate in the competition. Participants must register as teams.

• Track 1: Each team may have no more than 6 participants, plus 1-2 advisors;
• Track 2: Each team may have no more than 4 participants, plus 1-2 advisors.

Team naming convention: "Institution-Team Leader Name" or "Enthusiast Team-Team Leader Name." For example: "Tianjin University-Zhang San," "Enthusiast Team-Li Si." The first-ranked participant in each team is the team leader, responsible for communication matters. For non-research institute or enterprise institution names, please fill in "Enthusiast Team" (Enthusiast Team indicates that participants have formed a team in their personal capacity).

Registration Method

• The competition adopts online registration. Registration portal: https://s99x45wjic.jiandaoyun.com/f/6a0ae5b7d2ebb735eedc664d.
• Registration information includes: Contact Email, Team Name, Participants (Team Leader, Members, Advisors), Phone Number, Email, Institution (School/College, etc.), Title (Degree/Year, etc.).
• Award certificates will be printed according to the registration order, with students listed first, followed by advisors.
• One Email can only register one team. The team number is unique and bound to the contact Email.
• If you forget your number, you can query it on the submission page using the registered Email. Please be sure to remember your contact Email.

Work Submission Method

Competition works must be submitted online. Please click the submission portal link to submit your work. Avoid submitting during peak hours near the deadline.

Submission portals:

Track 1 work submission link: https://s99x45wjic.jiandaoyun.com/f/6a0ae5b7d2ebb735eedc664e

Track 2 work submission link: https://s99x45wjic.jiandaoyun.com/f/6a0ae5b7d2ebb735eedc6642

• Submission information includes: Team number, competition track and theme, work title, work abstract (100 words), and work submission content.
• To update your work, please resubmit using the same team number. The last submission under the same team number and team name will be considered final. The work title will be based on the last submission and work description document.
• It is recommended to refer to previous outstanding works. For details, please see "Review of Past Challenge Outstanding Works." You may also refer to selected works from the IEEE VAST Challenge organized by the IEEE VIS Conference. The work repository can be found at: http://cs.umd.edu/hcil/varepository/benchmarks.php.

Work Submission Material Requirements

Track 1

1. Work Description Document: Track 1 requires participants to use the recommended template provided by the organizers to introduce their work in an illustrated manner, submitted in Word or PDF format.
2. Video: Track 1 requires participants to produce a video with narration, explaining their visual analytics process. Total video length should not exceed 5 minutes, 1 video only, limited to MP4 format, and video size must be strictly controlled within 50MB.
3. Representative Work Image: Please provide 1 high-definition version, limited to JPG format. For multiple images, please stitch them together. Image size should not exceed 20MB.

Track 2

1. Work Interpretation (for review):
   • 1 file, limited to PDF format, < 10MB.
   • Necessary creative interpretation or explanation of the work, including original data description, work screenshots, and interpretation.
2. Work File (for review):
   • Work video or explanatory video. Please provide an online link.
   • 1 representative work image, limited to *.jpg / *.png format, single image < 20MB.
3. High-Definition Work File Download Link (for exhibition):
   • Includes all high-definition work files and work interpretation.
   • Baidu Netdisk is recommended. Ensure the link remains valid during the review period.
   • Video format works limited to *.mp4 / *.mov / *.avi types, < 50MB.
   • Image format works limited to *.jpg / *.png types, single image < 20MB.
   • Only electronic versions need to be submitted; no mailing is required.

Judging Rules

All entries will be submitted to both visual analysis experts, domain experts, and visualization-related artists for comprehensive evaluation. The evaluation will focus on evaluating the thematic orientation and application value of the entries, as well as the effectiveness, novelty and artistry of the entries in terms of interaction design, degree of data utilization, social benefits, analytical ideas and methods, etc.

Entries submitted by all eligible teams by the event deadline will be judged. The competition organizers will not evaluate any entries submitted after the deadline, and the organizers will not be held responsible for any damage, missing entries, or delayed submissions due to computer, Internet, or mobile network failures.

Awards

The chairman of the competition committee will select a number of exciting entries in proportion to the results of expert evaluation. At the ChinaVis 2026 conference, award certificates will be presented to all winning teams, and some of the winning teams will be invited to make on-site presentations at the competition session of the conference.

Important Time Points

China Standard Time 23:59, (UTC+8).

• Deadline for online registration: June 7, 2026.
• Deadline for submission of entries:
  • Track 1 (Data Visualization Challenge): June 20, 2026.
  • Track 2 (Art Visualization): June 10, 2026.
• Announcement date for judging results: July 02, 2026.

Documentation Templates and Dataset Download

1. Track 1-I: Data Visual Analytics and Humanities & Creativity Competition
   • Work document answer template: Download
   • Data download link: Download
2. Track 1-II: Scientific Visualization Challenge
   • Work document answer template: Download
   • Data download link: Download
3. Track 2: Art Visualization Competition
   • Self-provided datasets, with original data excerpts provided as evaluation references.

Others

1. Entries must not violate relevant national laws and regulations, and must not infringe on any third party intellectual property rights or other rights. If the work gives rise to intellectual property objections and disputes, the responsibility shall be borne by the participant.
2. Participants may use open source or commercial data analysis and visualization software, such as DataV, Tableau, R and Excel, etc. Participants are encouraged to use software development tools to design and implement their own visual analysis solutions or artistic visualization works. Common visualization development tools include D3, ECharts, AntV, and Processing, etc. Participants are requested to clearly state the development tools used and the open-source or commercial software used in the documentation of the work.
3. The winning team must have at least one person registered with ChinaVis 2026.
4. Winning teams are required to make their entries into posters and participate in the poster session of ChinaVis 2026, with specific requirements referring to the poster session.
5. The intellectual property rights of the entries belong to the participants. The organizers of the conference have the right to use the entries, work-related materials, and team information for promotional materials, authorized media releases, official website browsing and downloading, exhibitions (including roving exhibitions), and other activities.
6. Names and order of participants cannot be changed after the entries have been submitted.

Organizing Committee Of The Visualization Competition

Zhang Huijie, Northeast Normal University

Xu Jin, Hangzhou Normal University

Chen Jing, Nanjing University

Zhang Junjie, Hong Kong University of Science and Technology (Guangzhou)

Han Jun, Hong Kong University of Science and Technology

Previous Challenges Review

• 2025 Data Visual Analytics Challenge
• 2024 Data Visual Analytics Challenge
• 2023 Data Visual Analytics Challenge
• 2022 Data Visual Analytics Challenge
• 2021 Data Visual Analytics Challenge
• 2020 Data Visual Analytics Challenge
• 2019 Data Visual Analytics Challenge
• 2018 Data Visual Analytics Challenge

For more information, please visit the historical website: http://chinavis.org/history.html