Recent advancement of technologies such as sensor networking, cloud computing and data mining have significantly increased the availability of scientific and business data. Due to this sheer vast- ness automated quality control is a required to ensure that the information collected is beneficial for its intended application. Most data representation and collection systems neglect data quality information, which is an integral part of the data itself. Organizations must take data quality issues into consideration in their planning and operational process. This can be achieved by incorporating data quality evaluation into the data collection and representation process. This project uses the Goal Question Metric approach (GQM) which is a very popular software development paradigm, to evaluate data quality. This project incorporates the GQM technique into data collection process and leverages the multidimensional nature of data to evaluate data quality. This is achieved by means of a service that is built with Representational state transfer (REST) architecture, a test client consumes this service for the purpose of data representation which provides a structured form of the results with an overall data quality score of the system in consideration.