Urban Computational Paradigms with Shareable Data, Models, Tools, and Frameworks
Type: Virtual Paper
Day: 2/26/2022
Start Time: 3:40 PM
End Time: 5:00 PM
Theme:
Sponsor Group(s):
Geographic Information Science and Systems Specialty Group
, Cyberinfrastructure Specialty Group
, Spatial Analysis and Modeling Specialty Group
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Organizer(s):
Xiao Huang
, Xinyue Ye
, Zhenlong Li
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Chairs(s):
Xiao Huang, University of Arkansas
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Description:
Although the Big Data Era provides countless opportunities with the emerging of innovative data sources, it also poses new challenges, among which reproducibility and replicability (R & R) are facing a growing awareness. The extensive usage of urban monitoring big data, such as satellite imagery, location-based services, street views, to list a few, uniquely emphasizes the importance of R & R in Urban Science from the intertwining perspectives of location privacy, geospatial data quality, computing scalability, geoinformation shareability, and conclusion generalizability. To support reproducible computational studies, Choi et al. (2021) identified three thrusts: 1) open sharing of data and models online; 2) encapsulating computational models through containers and self-documented tutorials; 3) developing Application Programming Interfaces (APIs) for programmatic control of complex computational models. In addition, other venues exist where R & R can be promoted, such as the development of visualization frameworks, data-sharing portals, and integrated cyberinfrastructures. In response to the R & R challenges in Urban Science and the growing open-sourcing trend in academia, this session encourages the submission of abstracts that focus on tackling urban issues and problems by designing shareable data/products, developing analytical tools, launching online data visualization portals, constructing integrated cyberinfrastructures, and so on. Submitted abstracts could cover but are not limited to the following themes:
• Shareable urban monitoring data and products that benefit urban science communities.
• Online visualization, analytical, and data-sharing platforms that promote and facilitate data- and knowledge-sharing for both academia and the public.
• Development of reusable and interoperable analytical tools, packages, models, and data-accessing portals/APIs that advance urban sciences.
• Applied urban studies using designed data products, models, tools, and platforms.
• Research agenda and visions related to reproducibility and replicability in urban science.
• Urban monitoring and analytics using sharable data and platforms
Presentation(s), if applicable
Evelyn Ravuri, Saginaw Valley State University; Measuring Gentrification in Three U.S. Cities Using Google Street View |
Yujie Hu, University of Florida; Modeling and analysis of excess commuting with trip chains |
Na Jiang, University At Buffalo; Exploring Urban Shrinkage via Computational Approaches: A Case Study of Detroit |
Yoohoon Kim, ; A study on urban network in Seoul Metropolitan Area |
Non-Presenting Participants Agenda
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Urban Computational Paradigms with Shareable Data, Models, Tools, and Frameworks
Description
Virtual Paper
Contact the Primary Organizer
Xiao Huang - xiao.huang2@emory.edu