The Data Visualization Competition offers three tracks, of which the participants can choose the corresponding topic to compete.
Each track has its own judges.
Track 1:Visual Analytics Challenge
Ⅰ「Data Analysis Inspires Wisdom」Time-Series Multivariate Education Data Visual Analytics Challenge
NorthClass is a well-known higher education training institution that offers over 100 courses covering various academic disciplines such as literature, science, engineering, medicine, economics, and management, attracting approximately 300,000 registered learners. The institution establishes a flexible and convenient learning environment by providing excellent instructional services. In order to adapt to the development trend of the digital age and enhance its market competitiveness in the field of technology, the institution has planned and launched a programming course. Learners are required to complete specified
programming tasks during the learning period, with multiple attempts and submissions allowed to ensure full mastery and application of the knowledge learned. After the completion of the course, the organization gathers learners' temporal learning data to assess whether the quality of instruction meets the predetermined standards and requirements. To optimize teaching resources and improve teaching quality, the institution aims to establish a dedicated Smart Education Development and Innovation Group that will explore how to empower education with next-generation artificial intelligence technology, in order to better cultivate innovative talents who are suited to the development needs of the new era. Visualization and Visual Analytics harness the power of high-bandwidth visual perception channels to transform complex temporal learning behavior data into comprehensible graphical representations. These techniques not only diagnose and analyze learners' knowledge mastery levels but also dynamically monitor the evolving trends in their learning behaviors. Additionally, they effectively identify and dissect potential factors that contribute to learning difficulties. If you were a member of the Smart Education Development and Innovation Group, please design and implement a Visual Analytics solution to help the institution intuitively perceive the learning status of learners and provide feasible suggestions for adjusting teaching strategies and course designs. Please complete the following tasks:
- Analyze the log records of learners' question-answering behaviors, quantitatively assess the degree of knowledge mastery based on multi-dimensional attributes such as answer scores and answer status, and identify weak links in their knowledge system. (It is recommended that participants answer this question with no more than 800 words and no more than 5 pictures)
- Mine personalized learning behavior patterns based on learners' characteristics, and design and present learners' profiles from various perspectives, including peak answering hours, preferred question types, correct answering rates, etc. (It is recommended that participants answer this question with no more than 800 words and 5 pictures)
- Different learning modes directly impact learners' ability to absorb, integrate, and apply knowledge. Efficient learning modes can enhance deep understanding and long-term memory retention of knowledge. Please model the potential relationship between learning modes and knowledge acquisition, present the results in the form of a graph, and provide a brief analysis. (It is recommended that participants answer this question with no more than 800 words and 5 pictures)
- The difficulty level of questions should align with the learner's level of knowledge. When a learner possesses a high level of knowledge but achieves a low percentage of correct answers, it indicates that the question's difficulty exceeds their ability. Please utilize Visual Analytics to identify these inappropriate questions. (It is recommended that participants answer this question with no more than 800 words and no more than 5 pictures)
- Based on the outcomes of the aforementioned analysis, it is crucial to offer valuable recommendations for topic designers and course managers to optimize question bank content settings and enhance the quality of teaching and learning. Please briefly explain the rationale behind these suggestions. (It is recommended that participants answer this question with no more than 800 words and 3 pictures)
Optional Data set : For detailed information, please refer to Track 1 Data Description.
Note：The dataset for this track is designated, please do not use self-selected datasets.
Ⅱ「Insight into Recruitment Data」Multivariate Recruitment Data Visual Analytics Challenge
DataInsight is a leading data analytics consulting firm focused on providing data-based insights and decision support to organisations. The company offers a wide range of services, including market trend analysis, consumer behaviour research, human resource optimisation and many other areas. In order to adapt to the needs of the big data era and enhance its professional service capabilities in the field of data science, DataInsight has planned and launched a new data service offering, which aims to help companies gain a deeper understanding of the dynamics of the recruitment market and optimise their talent acquisition and human resource management strategies. To this end, DataInsight has collected recruitment market data, a dataset containing 400,000 detailed job announcements covering diverse job types and industry categories and a wide range of administrative divisions. dataInsight plans to set up a specialised team to analyse the recruitment dynamics of the market, and leverage advanced data analytics and visualisation technologies to conduct in-depth analysis of this data to uncover market trends and assist in HR optimisation. If you are a member of this team, please design and implement a Visual Analytics solution to help the
organisation visualise and understand industry and geographical developments, and provide actionable recommendations for talent acquisition and job search decisions. Please complete the following tasks:
- Analyze job postings and quantitatively assess the degree of job differentiation based on multidimensional attributes such as industry category, salary, and experience requirements. (It is recommended that participants answer this question with no more than 800 words and no more than 5 pictures)
- Integrating the key features of the job, design and present the job portrait from multiple angles, such as critical skills, preferred city, salary package, and so on. (It is recommended that participants answer this question with no more than 800 words and no more than 5 pictures)
- Different positions offer varying remuneration packages. Model the potential relationship between remuneration packages and positions, industries, geographies, etc. Identify remuneration patterns and potential pay differentials, present the results in a graph, and provide a brief analysis. (It is recommended that participants answer this question with no more than 800 words and no more than 5 pictures)
- Mining and summarizing geographic recruitment activity portraits, designing and presenting geographic characteristics of recruitment activities from multiple perspectives, such as preferred positions and industry categories, and identifying geographies with similar recruitment characteristics. (It is recommended that participants answer this question with no more than 800 words and no more than 5 pictures)
- Taking into account the results of the above analyses, is it possible to summarise the dynamics of the industry and identify emerging positions that are in urgent need of talent, and briefly explain the reasons. (It is recommended that participants answer this question with no more than 500 words and no more than 3 pictures)
Optional Data set : For detailed information, please refer to Track 1 Data Description.
Note：The dataset for this track is designated, please do not use self-selected datasets.
Track 2:「Mutual Learning between Data and Wisdom」Digital Humanities Visualization Creative Competition
"Exchanges and mutual understanding among civilisations is an important driving force for the progress of human civilisation and the peaceful development of the world." Over the past thousands of years, China and the world's civilisations have been engaged in extensive and in-depth exchanges, and have been integrated into different civilisations, which have been condensed into the material and spiritual wealth of each civilisation in tangible or intangible ways, and have jointly drawn a great picture of the world's civilisations. The Humanities Visualisation Creative Competition of ‘Digital Intelligence and Mutual Appreciation - Chinese and Foreign Civilisations Learning from Each Other’ is based on the theme of ‘Mutual Appreciation of Civilisations’, and invites participants to develop relevant work based on the sample dataset provided by the competition or a dataset of their own choosing. Participants are invited to work on the sample datasets or self-selected datasets provided by the competition, and complete the relevant creative works within the specified time.
The sample dataset of the competition includes part of the open data from seven museums: the Victoria and Albert Museum (V&A) in the UK, Le Louvre in France, The Metropolitan Museum of Art (The MET) in the US, Kyoto National Museum (Kyohaku) in Japan, National Palace Museum in Taipei, National Museum of Australia, and Shosoin in Japan, totalling 4,312 data (4,321 images). Taipei National Palace Museum, National Museum of Australia, and Shosoin in Japan, totalling 4,312 data items (4,321 images, one item of collection data may correspond to more than one image). Half of the data contain a ‘China’ field, indicating that the collection has a Chinese origin or description. Due to the different field formats of different museums, the metadata field names of all the collections in the sample dataset have been preprocessed, and the information in the six fields of Classification, Material, Technique, Metadata, Collection Name, and Description has been translated into Chinese and English (DeepL), EN for English and ZN for Chinese, so please check the accuracy of the translation when using the data.
In addition, please note that the data provided this time was downloaded through the Museum's Open Data API, and the data was partially reconstructed, cleaned and translated by human beings. If participants wish to use this dataset, it is recommended that they download more raw data from the Museum's official website through the Open Data Interface for analysis and processing.
Optional Data set : For detailed information, please refer to Track 1 Data Description.
Track 3: Art Visualization Competition
The Art Visualization Competition is an important part of the China Visualization and Visual Analysis Conference. Together with the China VISAP'24 Art Exhibition and a series of artist talks, it forms the 2024 China VIS Art Program. The aim of this competition is to promote talent cultivation, to stimulate conversation and collaboration within the artistic visualization community. It invites submissions that investigate topics related to the VISAP's theme from college students in art, design and visualization, encourages students to use their best techniques to represent the findings in their research within the prescribed time limit. The Competition sets a series of awards for excellent and novel submissions.
There is no restriction regarding the techniques being used. The competition aims to encourage students to maximize their imagination and creativity. Artistic visualization works need to base on real data. Submission of original data samples is required as a reference for evaluation. The criterion for the selection of the works is whether the team can effectively present a data-based artistic idea, viewpoint, or concept through visual or auditory forms.
We welcome you as artists to collaborate with artificial intelligence as an innovative co-composer to generate new knowledge in data visualization and processes. However, please be aware that the committee will carefully evaluate whether this usage is fair and appropriate within the boundaries of relevance, ethics, and intention. Please mark any work that is AI generated as being so.
Annual Theme: Data Intelligence Hong Kong, Co-creation in Visualization
The theme for the China VISAP'24 is 'Data Intelligence Hong Kong, Co-creation in Visualization.' In this rapidly changing era, art and technology are no longer isolated fields but complementary and mutually reinforcing, jointly nurturing new ideas and ways of perception. Against this backdrop, data transforms into a source of vitality, with artistic visualization techniques turning dry data into vibrant visual works.
Hong Kong, as an international metropolis in Asia, is renowned for its unique cultural diversity and technological innovation, making it an ideal venue to showcase the fusion of art and technology. The diversity and innovative spirit of Hong Kong are a perfect embodiment of the theme 'Data Intelligence Hong Kong, Co-creation in Visualization,' and its position at the intersection of global finance, technology, and culture make it a vanguard in promoting the integration of visual art and technology. Concurrently, with the development of the
Guangdong-Hong Kong-Macao Greater Bay Area, Hong Kong, as an integral part of the region, carries a significant mission for innovation and development in the digital age. Our goal is to leverage Hong Kong's unique advantages to create a platform that combines digital intelligence and creative art, showcasing the limitless possibilities of the digital era through co-creation.
China VISAP'24 calls upon artists, designers, researchers, faculty and students from universities, and professionals from all fields to create and submit artistic design works related to the theme 'Data Intelligence Hong Kong, Co-creation in Visualization,' showcasing multi-dimensional exploration and splendor in the field of visualization. This track requires authors to select relevant datasets within the theme of 'Data Intelligence Hong Kong, Co-creation in Visualization' for artistic visualization creation. There are no restrictions on the methods of expression, with the aim of encouraging students to maximize their imagination and free creativity, and to encourage the creation and submission of artistic design works related to multidimensional visualization, showcasing multi-dimensional exploration and splendor in the field.
The works for this track will be reviewed by a domestic expert panel on artistic visualization. The evaluation criteria are whether the participating teams can effectively express artistic ideas, viewpoints, or concepts based on self-selected data through visual, auditory, and other artistic forms.