## 3 Methodology  
Figure 1 presents an implemented process of the proposed ontology-based information retrieval method for bridge inspection, which comprises the following steps:  
1. Ontology construction: This step aims to construct a bridge inspection-relevant ontology. Firstly, existing ontologies and relational data related to bridge inspection are collected. Then, reusing these ontologies will be taken into consideration when the seven-step method [33] is adopted to build the Blontology. Meanwhile, the automatic mapping technology is applied to improve the seven-step method in order to accelerate the construction of the Blontology. After that, the Blontology can be established. Section 4 will describe the construction process of the Blontology in detail.
2. Data conversion: This step aims to transform the Blontology from the Web Ontology Language (OWL) file to Resource Description Framework (RDF) data stored in the TDB database (an RDF triple stores). The Blontology derived from the first step is saved as an OWL file, and, in practice, the OWL file should be translated to RDF data to improve the readability. Apache Jena Fuseki (a SPARQL server) is deployed for the implementation of data conversion. After the OWL file is manually uploaded to the Fuseki server, the Fuseki server can automate the execution of the data conversion and then save the transformed data in the TDB database. This step is a simple manual process and thus will not be described again in the following sections.
3. System development: This step aims to develop the bridge inspection prototype system to realize the semantic retrieval from the Blontology-based knowledge base. SPARQL query is used to retrieve bridge inspection information from the TDB database according to user input data. The prototype system should provide a nice man-machine interaction environment for executing the SPARQL queries and presenting the query results. The prototype system is not only a realization of the proposed IR method but can also be used to validate the effectiveness of the proposed IR method for bridge inspection. The development process of the prototype system will be discussed in Section 5.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Ontology**} & \multicolumn{2}{c}{**The Classes and Relations of the Blontology**} & \multirow{2}{*}{**Ontology**} \\ \cline{2-3} \cline{5-5}  & **Classes** & & **Relations** & **Ontology** \\ \cline{2-3} \cline{5-5}  & **C1–C4 1** & **R1–R3 2** & **R4–R9 3 \\ \hline BridgeOnto [27] & XX & XX & O & manual \\ CBRPMO [10] & O & O & O & manual \\ BSHM ontology [11] & XX & XXX & O & manual \\ BROT [13] & XX & XX & O & semi-automatic \\ BrMontology [12] & XX & O & O & manual \\ IPD-Onto [28] & O & O & O & manual \\ IC-PRO-Onto [29] & O & O & O & manual \\ Context Ontology [30] & X & O & O & not mentioned \\ IPD-Onto [31] & O & O & O & not mentioned \\ HiOnto [32] & X & X & O & not mentioned \\ \hline \hline \end{tabular}  
* C1–C4 denote “Bridge”, “BridgePortion”, “BridgeComponent”, “BridgeElement”, respectively. 2 R1–R9 denote “isPortionOf”, “isComponentOf”, “isElementOf”, “onTheEastOf”, “onTheSouthOf”, “isOn”, “onTheWestOf”, “onTheNorthOf”, “isUnder”, respectively. 3 O = not covered; X = rarely covered; XX = moderately covered; XXX = covered.  
\end{table}
Table 1: Review of existing ontologies in bridge engineering.