Abstract
BackgroundThe advancement of science and technologies play an immense role in the way scientific experiments are being conducted. Understanding how experiments are performed and how results are derived has become significantly more complex with the recent explosive growth of heterogeneous research data and methods. Therefore, it is important that the provenance of results is tracked, described, and managed throughout the research lifecycle starting from the beginning of an experiment to its end to ensure reproducibility of results described in publications. However, there is a lack of interoperable representation of end-to-end provenance of scientific experiments that interlinks data, processing steps, and results from an experiment’s computational and non-computational processes.ResultsWe present the “REPRODUCE-ME” data model and ontology to describe the end-to-end provenance of scientific experiments by extending existing standards in the semantic web. The ontology brings together different aspects of the provenance of scientific studies by interlinking non-computational data and steps with computational data and steps to achieve understandability and reproducibility. We explain the important classes and properties of the ontology and how they are mapped to existing ontologies like PROV-O and P-Plan. The ontology is evaluated by answering competency questions over the knowledge base of scientific experiments consisting of computational and non-computational data and steps.ConclusionWe have designed and developed an interoperable way to represent the complete path of a scientific experiment consisting of computational and non-computational steps. We have applied and evaluated our approach to a set of scientific experiments in different subject domains like computational science, biological imaging, and microscopy.
Highlights
Scientific experiments play a key role in new inventions and in extending the world’s knowledge
Results we present our main results for the understandability, reproducibility, and reuse of scientific experiments using a provenance-based semantic approach
In this article, we presented the REPRODUCE-ME Data Model and the ontology to describe the provenance of scientific experiments
Summary
Scientific experiments play a key role in new inventions and in extending the world’s knowledge. There is a lack of interoperable representation of end-to-end provenance of scientific experiments that interlinks data, processing steps, and results from an experiment’s computational and non-computational processes. The prerequisite to designing and developing an end-toend provenance representation of scientific experiments arises from the requirements collected from interviews we conducted with scientists working in the Collaborative Research Center (CRC) ReceptorLight [13], as well as from a workshop conducted to foster reproducible science [14]. We conducted a survey addressed to researchers from different disciplines to understand scientific experiments and research practices for reproducibility [6]. The detailed insights from these meetings and the survey helped us to understand the different scientific practices followed in their experiments and the importance of reproducibility when working in a collaborative environment as described in [13]. It is important to describe non-computational steps in sufficient detail for their reproducibility [1]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
