Browse Theses

We present BIODQ, a model for estimating and managing the quality of biological data in genomics repositories. BIODQ uses our new Quality Estimation Model (QEM) which has been implemented as part of the Quality Management Architecture (QMA). The QEM consists of a set of quality dimensions and their quantitative measures. The QMA combines a series of software components that provide support for the integration of the QEM with existing biological repositories. We describe a research study conducted among biologists, which provides insights into the process of quality assessment in the biological context, and is the basis of our evaluation. The evaluation results show that the QEM dimensions and estimations are biologically-relevant and useful for discriminating high quality from low quality data. Additionally, the evaluation performed on a subset of the National Center for Biotechnology Information’s databases validates the benefits of QMA as a quality-aware interface to genomics repositories. We expect BIODQ to benefit biologists and other users of genomics repositories by providing them with accurate information about the quality of the information that is returned as part of their queries.