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The digitization of legacy infrastructure constitutes an important component of smart cities. While most cities worldwide possess digital maps of their transportation infrastructure, few have accurate digital information on their electric, natural gas, telecom, water, wastewater, and district heating and cooling systems. Digitizing data on legacy infrastructure systems comes with several challenges such as missing data, data conversion issues, data inconsistency, differences in the data format, spatio-temporal resolutions, structure, semantics and syntax, difficulty in providing controlled access to the datasets, and so on. Therefore, we introduce GUIDES, a new data conversion and management framework for urban infrastructure systems, which is comprised of big data analytics, efficient data management techniques, semantic web technologies, methods to ensure information security, and tools that aid visual analytics. The proposed framework facilitates: (i) mapping of urban infrastructure systems; (ii) integration of heterogeneous geospatial data; (iii) a secured way of storing, analyzing and querying data while preserving the semantics; (iv) qualitative and quantitative analysis over several spatio-temporal resolutions; and (v) visualization of static (e.g., land use) and dynamic (e.g., road traffic) information.
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Designing a Data Commons for Urban Big Data
Infrastructure systems and smart buildings are rapidly joining the Internet of Things and evolving into advanced cyber-physical systems. As a result, massive amounts of data that characterize the structure and function of urban areas in minute detail are being generated. However, these data are often fragmented and managed by a variety of public agencies and private corporations. As a result, they are not readily available to the urban research community. This paper lays out a strategy to develop a data commons that would collect, curate and distribute Urban Big Data to support re-search on infrastructure systems and how they interact with the human populations they support.
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- Award ID(s):
- 1652999
- PAR ID:
- 10056073
- Date Published:
- Journal Name:
- Computers in Urban Planning and Urban Management (CUPUM), University of South Australia, Adelaide, Australia
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
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