Abstract
Recently, several papers reported problems in data exchange using industry foundation classes (IFC). However, most comparisons were made based on a visual check, a manual count, and observation of properties that were selectively chosen. This study proposes a set of metrics for quantifying the similarities and differences between IFC files. The proposed metrics include the similarity rate, the matching rate, the globally unique identifier (GUID) preservation rate, the missing rate, and the addition rate. A long-term goal of this study is to develop a set of metrics for quantifying the information exchange rate between two IFC files. Automated identification of modified information versus newly generated information is an unsolved challenge. The proposed metrics were used in analyzing 88 IFC files generated from different systems to demonstrate the potential use of the proposed metrics.
| Original language | English |
|---|---|
| Pages (from-to) | 172-181 |
| Number of pages | 10 |
| Journal | Journal of Computing in Civil Engineering |
| Volume | 25 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2011 Mar 1 |
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All Science Journal Classification (ASJC) codes
- Civil and Structural Engineering
- Computer Science Applications
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Metrics for quantifying the similarities and differences between IFC files. / Lee, Ghang; Won, Jongsung; Ham, Sungil; Shin, Yuna.
In: Journal of Computing in Civil Engineering, Vol. 25, No. 2, 01.03.2011, p. 172-181.Research output: Contribution to journal › Article
TY - JOUR
T1 - Metrics for quantifying the similarities and differences between IFC files
AU - Lee, Ghang
AU - Won, Jongsung
AU - Ham, Sungil
AU - Shin, Yuna
PY - 2011/3/1
Y1 - 2011/3/1
N2 - Recently, several papers reported problems in data exchange using industry foundation classes (IFC). However, most comparisons were made based on a visual check, a manual count, and observation of properties that were selectively chosen. This study proposes a set of metrics for quantifying the similarities and differences between IFC files. The proposed metrics include the similarity rate, the matching rate, the globally unique identifier (GUID) preservation rate, the missing rate, and the addition rate. A long-term goal of this study is to develop a set of metrics for quantifying the information exchange rate between two IFC files. Automated identification of modified information versus newly generated information is an unsolved challenge. The proposed metrics were used in analyzing 88 IFC files generated from different systems to demonstrate the potential use of the proposed metrics.
AB - Recently, several papers reported problems in data exchange using industry foundation classes (IFC). However, most comparisons were made based on a visual check, a manual count, and observation of properties that were selectively chosen. This study proposes a set of metrics for quantifying the similarities and differences between IFC files. The proposed metrics include the similarity rate, the matching rate, the globally unique identifier (GUID) preservation rate, the missing rate, and the addition rate. A long-term goal of this study is to develop a set of metrics for quantifying the information exchange rate between two IFC files. Automated identification of modified information versus newly generated information is an unsolved challenge. The proposed metrics were used in analyzing 88 IFC files generated from different systems to demonstrate the potential use of the proposed metrics.
UR - http://www.scopus.com/inward/record.url?scp=79952287133&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79952287133&partnerID=8YFLogxK
U2 - 10.1061/(ASCE)CP.1943-5487.0000077
DO - 10.1061/(ASCE)CP.1943-5487.0000077
M3 - Article
VL - 25
SP - 172
EP - 181
JO - Journal of Computing in Civil Engineering
JF - Journal of Computing in Civil Engineering
SN - 0887-3801
IS - 2
ER -