Semantic Modeling of Bridge Deterioration Knowledge for Supporting Big Bridge Data Analytics

Kaijian Liu, Nora El-Gohary

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A big size of bridge data is being constantly generated - from a variety of distributed sources and in heterogeneous formats - in the form of national bridge inventory (NBI) data, national bridge elements (NBE) data, bridge inspection and maintenance reports, traffic data, etc. Big bridge data analytics open unprecedented opportunities to leverage this large amount of data for improved bridge deterioration prediction and understanding, and enhanced maintenance decision making. In this paper, the authors propose a big bridge data analytics framework that consists of: (1) semantic data/information extraction and integration, (2) semantic data/information analysis and mining, and (3) semantic data/information retrieval and visualization. The big size of the data, in addition to it being scattered and heterogeneity of meaning and format, adds to the challenge of data integration and analysis. As such, at the cornerstone of this framework is an ontology of bridge deterioration knowledge, which aims to facilitate the semantic integration and analysis of the data based on content and domain-specific meaning, and to bridge the terminology gap across different sources. This paper focuses on providing an overview of the framework for big bridge data analytics and presenting the proposed bridge deterioration ontology as the first step towards implementing this framework.

Original languageEnglish (US)
Title of host publicationConstruction Research Congress 2016
Subtitle of host publicationOld and New Construction Technologies Converge in Historic San Juan - Proceedings of the 2016 Construction Research Congress, CRC 2016
EditorsJose L. Perdomo-Rivera, Carla Lopez del Puerto, Antonio Gonzalez-Quevedo, Francisco Maldonado-Fortunet, Omar I. Molina-Bas
PublisherAmerican Society of Civil Engineers (ASCE)
Pages930-939
Number of pages10
ISBN (Electronic)9780784479827
DOIs
StatePublished - Jan 1 2016
EventConstruction Research Congress 2016: Old and New Construction Technologies Converge in Historic San Juan, CRC 2016 - San Juan, Puerto Rico
Duration: May 31 2016Jun 2 2016

Publication series

NameConstruction Research Congress 2016: Old and New Construction Technologies Converge in Historic San Juan - Proceedings of the 2016 Construction Research Congress, CRC 2016

Other

OtherConstruction Research Congress 2016: Old and New Construction Technologies Converge in Historic San Juan, CRC 2016
CountryPuerto Rico
CitySan Juan
Period5/31/166/2/16

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction

Fingerprint Dive into the research topics of 'Semantic Modeling of Bridge Deterioration Knowledge for Supporting Big Bridge Data Analytics'. Together they form a unique fingerprint.

  • Cite this

    Liu, K., & El-Gohary, N. (2016). Semantic Modeling of Bridge Deterioration Knowledge for Supporting Big Bridge Data Analytics. In J. L. Perdomo-Rivera, C. Lopez del Puerto, A. Gonzalez-Quevedo, F. Maldonado-Fortunet, & O. I. Molina-Bas (Eds.), Construction Research Congress 2016: Old and New Construction Technologies Converge in Historic San Juan - Proceedings of the 2016 Construction Research Congress, CRC 2016 (pp. 930-939). (Construction Research Congress 2016: Old and New Construction Technologies Converge in Historic San Juan - Proceedings of the 2016 Construction Research Congress, CRC 2016). American Society of Civil Engineers (ASCE). https://doi.org/10.1061/9780784479827.094