Constraint propagation algorithms for temporal reasoning: a revised report
Readings in qualitative reasoning about physical systems
Artificial Intelligence - Special issue on knowledge representation
Maintaining knowledge about temporal intervals
Communications of the ACM
The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling
The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling
UML Distilled: A Brief Guide to the Standard Object Modeling Language
UML Distilled: A Brief Guide to the Standard Object Modeling Language
Knowledge Representation and Reasoning
Knowledge Representation and Reasoning
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
An approach for fusing data from multiple sources to support construction productivity analyses
An approach for fusing data from multiple sources to support construction productivity analyses
All of Statistics: A Concise Course in Statistical Inference
All of Statistics: A Concise Course in Statistical Inference
Quality assessment of coupled civil engineering applications
Advanced Engineering Informatics
A model for data fusion in civil engineering
EG-ICE'06 Proceedings of the 13th international conference on Intelligent Computing in Engineering and Architecture
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Project management tasks, such as productivity monitoring and cost estimation, require data to be fused from multiple data sources, which are typically spatial and temporal in nature. In order to fuse a pair of spatial and temporal data sources, a number of different types of reasoning mechanisms are needed. This paper presents a taxonomy of spatial and temporal reasoning mechanisms needed to fuse spatial and temporal data sources to support construction productivity monitoring. In addition, the paper also describes two different approaches (i.e., interpolation and nearest neighbor approaches) that can be used to synchronize the temporal and/or spatial data sources. The developed taxonomy has been validated based on representative queries of construction engineers and managers that are identified in previous research studies. The interpolation and nearest neighbor approaches have been validated with real and simulated construction data sources.