Exploiting Conceptual Modeling for Searching Genomic Metadata: A Quantitative and Qualitative Empirical Study

Providing a common data model for the metadata of several heterogenous genomic data sources is hard, as they do not share any standard or agreed practice for metadata description. Two years ago we managed to discover a subset of common metadata present in most sources and to organize it as a smart genomic conceptual model (GCM); the model has been instrumental to our efforts in the development of a major software pipeline for data integration. More recently, we developed a user-friendly search interface, based on a simplified version of GCM. In this paper, we report our evaluation of the effectiveness of this new user interface. Specifically, we present the results of a compendious empirical study to answer the research question: How much is such a simple interface well-understood by a standard user? The target of this study is a mixed population, composed by biologists, bioinformaticians and computer scientists. The result of our empirical study shows that the users were successful in producing search queries starting from their natural language description, as they did it with good accuracy and small error rate. The study also shows that most users were generally satisfied; it provides indications on how to improve our search system and how to continue our effort in integration of genomic sources. We are consequently adapting the user interface, that will be soon opened to public use.