Automated generation of customized field data collection templates to support information needs of cost estimators

Semiha Kiziltas, Burcu Akinci

Research output: Contribution to journalArticle

Abstract

While estimating activity production rates, cost estimators rely on historical production rates. To have realistic and useful cost estimates based on historical production rates, such production rate data should be augmented with historical contextual information that depict conditions under which activity production rates were achieved in past projects. This information is needed in determining which production rate to use among alternates for a similar activity existing in a new bid. Estimators need contextual information especially when they are unfamiliar with the work being estimated. Hence, such information items need to be identified, collected, and stored for estimators' use in new projects. This paper details a construction-method specific and an extensible approach that is developed for enabling cost estimators to define contextual information items that need to be collected on job sites and stored as part of project histories. Based on this approach, the writers implemented a prototype system, called as ContextGen, and performed user-tests with estimators with different experience levels. Results showed that the developed approach captures method-specific information needs of estimators and is extensible to incorporate new contextual information items that can have different data representations. The developed approach is also precise in retrieving contextual information items specific to a construction method from a set of predefined contextual information items available in a library.

Original languageEnglish (US)
Pages (from-to)129-139
Number of pages11
JournalJournal of Computing in Civil Engineering
Volume24
Issue number2
DOIs
StatePublished - 2010

Keywords

  • Automated information retrieval
  • Automation
  • Classifications
  • Construction costs
  • Cost estimating
  • Customized data collection
  • Data collection
  • Faceted classification
  • History
  • Information management
  • Precision and recall
  • Project history
  • Project management

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Computer Science Applications

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