OGC Standards – Driving Reproducibility of Scientific Workflows
Synopsis: Reproducibility is a current hot topic in science, international initiatives such as GEOSS (Global Earth Observation System of Systems), or production environments like the Copernicus Climate Data Service or other public administration data distribution platforms. Recently, the US National Science Foundation published a consensus study report on Reproducibility and Replicability in Science. In all cases, a once produced result needs to be reproducible at a later stage independently of new incoming, updated, or obsolete data, revised software libraries, or renovated data access protocols. Defined workflows shall operate despite changes in the underlying infrastructure. At the same time, the scientific understanding of our environment increases and results in adapted models and algorithms, data and service governance models change, and legal, commercial or scientific constraints and requirements evolve.
The FAIR principles, a set of guiding principles to make data Findable, Accessible, Interoperable, and Reusable, has gained momentum since their publication in 2016. Reusability in FAIR is closely related to reproducibility, as results in data-intensive science and their following relevance to society are often the result of knowledge discovery from appropriate scientific data, associated algorithms, and applied workflows. It is the combination of reusable data and re-applicable algorithms and processing workflows that form solid wisdom.
The Open Geospatial Consortium is the worldwide leading standardization body for geospatial data and services. OGC uses the FAIR principles as part of its mission to use location to connect people, communities, technology, and decision making for the greater good. The OGC Innovation Program is exploring in several research and development initiatives as well as Standard Program working groups how to enhance reproducibility through enhanced data representation, discovery, and access models. This session will highlight the latest achievements in this context, demonstrate how open standards boost interoperability and reproducibility using a series of Web APIs that provide stable state-of-the-art interfaces to data, services, and applications; cloud-based deployment and execution models for arbitrary applications that process (Big) data at their physical location; or metadata and discovery models that include data, services, and applications.
The session is open to all authors.