Cited By
View all- Balsebre PYao DCong GHai Z(2022)Geospatial Entity ResolutionProceedings of the ACM Web Conference 202210.1145/3485447.3512026(3061-3070)Online publication date: 25-Apr-2022
Ontology-based Instance Matching for Geospatial Urban Data Integration
Article No.: 8, Pages 1 - 8
Abstract
To run a smart city, data is collected from disparate sources such as IoT devices, social media, private and public organizations, and government agencies. In the US, the City of Chicago has been a pioneer in the collection of data and in the development of a framework, called OpenGrid, to curate and analyze the collected data. OpenGrid is a geospatial situational awareness platform that allows policy makers, service providers, and the general public to explore city data and to perform advanced data analytics to enable planning of services, prediction of events and patterns, and identification of incidents across the city. This paper presents the instance matching module of GIVA, a Geospatial data Integration, Visualization, and Analytics platform, as applied to the integration of information related to businesses, which is spread across several datasets. In particular, we describe the integration of two datasets, Business Licenses and Food Inspections, so as to enable predictive analytics to determine which food establishments the city should inspect first. The paper describes semantic web-based instance matching mechanisms to compare the Business Names and Address fields.
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Index Terms
- Ontology-based Instance Matching for Geospatial Urban Data Integration
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November 2017
118 pages
ISBN:9781450354950
DOI:10.1145/3152178
Copyright © 2017 Owner/Author.
This work is licensed under a Creative Commons Attribution International 4.0 License.
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Published: 07 November 2017
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- National Science Foundation
- Bloomberg Philanthropies
- Bill and Melinda Gates Foundation
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SIGSPATIAL'17: 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
November 7 - 10, 2017
CA, Redondo Beach, USA
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View all- Balsebre PYao DCong GHai Z(2022)Geospatial Entity ResolutionProceedings of the ACM Web Conference 202210.1145/3485447.3512026(3061-3070)Online publication date: 25-Apr-2022
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