Digital data, software and samples are key inputs that underpin research and ultimately scholarly publications, and there are increasing expectations from policy makers and funders that they will be Open and FAIR (Findable, Accessible, Interoperable, Reusable). Open, accessible, high-quality data, software and samples are critical to ensure the integrity of published research and to facilitate reuse of these inputs in future scientific efforts. In Europe, adherence to the INSPIRE directive becomes gradually more enforced by national legislations, affecting also the data lifecycle in Earth and Environmental Sciences.

These issues and challenges get addressed at an increasing pace today, with journals changing their policies towards openness of data, samples and software connected to publications, and national, European and global initiatives and institutions developing more and more services around Open and FAIR data, covering curation, distribution and processing. Yet, researchers, as producers as well as users of data, products, and software, continue to struggle with the requirements and conditions they encounter in this rapidly evolving environment.

This session will showcase the range of practices with respect to the FAIR and Open paradigms in research infrastructures and research data repositories. It will also look at how research infrastructures and repositories assess FAIRness, the development and role of general standards, and the consequences for data publication and the integration of data, software and samples into the scholarly publication process.

In that sense, this session also supports tackling the existing and upcoming challenges in the evolution of an integrated, Open and FAIR research ecosystem.

Earth science research has become increasingly collaborative through shared code and shared platforms. Researchers work together on data, software and algorithms to answer cutting-edge research questions. Teams also share these data and software with other collaborators to refine and improve these products. As data volumes continue to grow, researchers will need new platforms to both enable analysis at scale and to support the sharing of data and software.

Software is critical to the success of science. Creating and using Free and Open Source Software (FOSS) fosters contributions from the scientific community, creates a peer-reviewed and consensus-oriented environment, and promotes the sustainability of science infrastructures.

This session will look at how Free and Open Source Software (FOSS) and cloud-based architecture solutions support information sharing, scientific collaboration, scientific reproducibility and solutions that enable large-scale data analytics.

Significant investments are made globally in laboratory analytical research in the Earth and space sciences to extract new scientific insights from Earth and planetary materials. Expensive laboratory infrastructure and advanced instrumentation generates data at an ever increasing level of precision, resolution, and volume. Any data generated at any scale needs to be efficiently managed and losslessly transferred from instruments in “Private” domains to a “Collaboration” domains, where researchers can analyze and share these data as well as the analytical tools. Ultimately, the data need to be transferred to the “Public” domain, complete with all relevant information about the analytical process and uncertainty, and cross-references to originating samples and publications. Many solutions today are bespoke and inefficient, lacking, for example, unique identification of samples, instruments, and data sets needed to trace the analytical history of the data.

This session seeks contributions about new developments to achieve FAIR, scalable and sustainable access to analytical data from any laboratory instrument and domain at any scale (from an individual instrument in a geochemical lab to data measured with synchrotrons), and any stage from the initial collection of the sample through to the publication of the final data, including the use of persistent identifiers to uniquely identify samples, instruments, researchers, grants, data, etc. Papers are welcome on systems that transfer data/metadata directly from instruments to “collaborative storage areas” that facilitate sharing and processing of geochemical data, as well as systems that transfer data used in publications to relevant repositories that ensure long term persistence of data and enhanced reproducibility of geochemical research.