NO.165 Leveraging Multidisciplinary Expertise for Visual Computing of Urban Mobility Data
September 7 - 10, 2020 (Check-in: September 6, 2020 )
- Ye Zhao
- Kent State University, USA
- Xinyue Ye
- New Jersey Institute of Technology, USA
- Feng Zhen
- Nanjing University, CHINA
Description of the Meeting
Advanced sensing technologies and computing infrastructures are producing massive human and vehicle mobility data in urban spaces at an unprecedented scale and speed. In particular, with the prevalent GPS, Wi-Fi, Cellular, and RFID devices, human population mobility information is accurately recorded as the moving paths of taxis, fleets, public transits, and mobile phones. Thus, human dynamics patterns and trends are modelled in the urban mobility data and can be discovered through data-centric computing. The big data collected can be utilized by domain experts in multiple fields including urban design and planning, transportation, geography, environment, criminology, economy, and more, to optimize urban systems, improve human life quality and environment, and amend city operations.
Researchers in the fields of geography, transportation, urban study, business, environment, and many social sciences have presented a variety of technologies of managing, mining, and analyzing knowledge from the mobility data and utilizing them in a variety of real world applications. On the other hand, many visualization techniques and visual analytics tools are developed, aimed to allow users conduct iterative, evolving information foraging and sense making using visual computing capabilities and their domain knowledge.
Nonetheless, there exists a big gap between the domain experts and the visualization experts to leverage the emerging urban mobility datasets in interdisciplinary projects and applications. The knowledge of each other and collaboration between the two research groups is surprisingly little. Many domain experts do not recognize the capability and potential that visual analytics tools can help in their research topics and applications. Meanwhile, visualization researchers often suffer from the dearth of knowledge about real domain tasks and requirements to design pertinent techniques and systems. This fact indeed greatly impedes the anticipated data utilization and contribution to our society.
In the proposed meeting, we plan to integrate a variety of domain and visual computing experts in the workshop. We establish a wide scope by inviting scholars from the following domains: computer science, information science, information engineering, sociology, geography, urban planning, architecture, information technology, transportation, cartography, public policy, public health, business and marketing. Please see the attached excel list for details. Domain experts can provide data and driving problems, typical solutions, and domain technologies. Meanwhile, visualization experts can contribute to better data utilization with inspiring data computing methods, as well as visual interfaces and functions. Bringing such liaison together is of utmost importance for the success of such problem-driven endeavors, necessitating not only expertise in both domains but also a good communication and a shared understanding between both groups.
The workshop will focus on discussion of interdisciplinary topics to address the following problems:
- What research topics construct the body of knowledge of current visual computing of urban mobility data research? and in your opinion, how will the research evolve into the future?
- What accomplishments have urban visual analytics as a research area achieved and what is your vision of its future development?
- What is your ongoing research or industrial projects that represent the new use of visual computing of urban mobility data or contribute to the development of urban visual analytics?
- Which networks, or organizations, or science communities should we engage more to enhance the domain-specific applications of urban visual analytics research?
- What will be the role of urban visual analytics research in the research landscape of urban computing, or more generally computational social science in the coming 5-10 years?
- What are the current gaps in urban visual analytics education in academia? How could we innovate current education curriculum to foster next generation workforce in urban visual analytics?
- How Open Data and Open Source Software relate to urban visual analytics?
- What is your advice for promoting multidisciplinary collaboration for visual computing of urban mobility data?
- What are the funding opportunities (academia or industry) of conducting visual computing of urban mobility data?
Moreover, the workship will discuss the following research-oriented topics including:
- Domain research tasks and problem complexity: Identify domain problems on utilizing the urban mobility data where visualization tools and visual analytics techniques can potentially provide solutions. Discuss the complexity of urban problems and categorize the problems with potential research directions.
- Data processing, uncertainty, privacy and management: discuss data issues related to urban mobility data, including privacy, human subjects, regulation. Present facts about data inaccuracy and errors, which lead to uncertainty which need to be addressed in related research and applications. Identify data management issues related to these problems.
- Mental model of users and visualization design space: study and match the mental model of the domain users with visual computing models and designs. Discuss how to capture the user requirements. Discuss current visualization design space and methods, possibly leading to a new mode of visual design for the urban mobility data.
- Common language for understanding and effective translation among domains: discuss about the possibility and potential to establish common ontology/language to integrate experts from multiple domains. Find the translation issues in urban computing, mining, visualization and related urban domains.
- Design validation and method evaluation: discuss issues on valid the computational methods and visualization tools; find how domain experts can more actively and easily attend the design and implementation of useful visual analytical tools. Design and propose evaluation ethods, rules and meaningful policies.
We expect the workshop outcomes of the integrated research groups will include:
- Collaboration and teamwork in multiple fields of research leading to better utilization of the urban mobility data.
- One or multiple direction papers which propose new and important interdisciplinary research topics, challenges, and tasks of the urban data.