REPRODUCE-ME: Ontology-Based Data Access for Reproducibility of Microscopy Experiments

Abstract

It has always been the aim of every scientist to make their work reproducible so that the scientific community can verify and trust the experiment results. With more complex in vivo and in vitro studies, achieving reproducibility has become more challenging over the last decades. In this work, we focus on integrative data management for reproducibility aspects related to execution environment conservation taking into account the use case of microscopy experiments. We use Semantic Web technologies to describe the experiment and its execution environment. We have developed an ontology, REPRODUCE-ME (Reproduce Microscopy Experiments) by extending the existing vocabulary PROV-O. Scientists can use this ontology to make semantic queries related to reproducibility of experiments on the microscopic data. To ensure efficient execution of these queries, we rely on ontology-based data access to source data stored in a relational DBMS.