Advanced data acquisition (DAQ) technologies, such as smart tags, laser scanners and embedded sensors promise to collect accurate, complete, and timely field data, which is essential to increase the control of construction projects. However, since different DAQ technologies have different capabilities, which are meant to collect different types of data that come with different data processing requirements, construction professionals end up making ad-hoc decisions on which technologies to use in order to capture the required field data. To enable the capture of construction field data in a formal way via mapping required field data to applicable DAQ tools, we identified an initial set of representation requirements for modeling DAQ tools. Based on these requirements, we evaluated and compared relevant sensor ontologies. The limitations and capabilities of relevant sensor ontologies are described in this paper. This evaluation revealed that for the mapping process, there is no single ontology that can be used in its original form to represent DAQ tools. Hence, a representation schema, which builds on various aspects of existing ontologies, has been developed.