Open Data and Open Science are broad movements looking beyond Open Access to openly publish and share scientific research immediately. Not only accessibility is addressed at all levels for everyone, without fees, but also reproducibility which gains more attention each year with prominent papers, editorials and blog posts.

Open Data and Open Science not only address publications, but scientific research results in general, including figures, data, models, algorithms, software, tools, notebooks, laboratory designs, recipes, samples and much more.

Furthermore, they relate to the communication, review, and discussion of research results and consider changing needs regarding incentives, quality assessment, metrics, impact, reputation, grants and funding. Thus Open Data and Open Science encompass licensing, policy-making, infrastructures and scientific heritage, while safeguarding the dynamic nature of science and its evolving forms.

Additionally, Reproducible Research is important for science. Journals, researchers and funders drive forward the agenda on many aspects of openness. But still the vast majority of papers analyzing any kind of data is not accompanied by data, code and documentation that let you easily reproduce the calculations that underly the paper.

Computational reproducibility is especially important in the context of big data. Readers of articles must be able to trust the applied methods and computations.

Furthermore, Open Data and Open Science meets the increasing public interest in research results, exemplified by the uptake of Citizen Science, by establishing cooperative platforms for Public Sector Information and governance data, to promote the active engagement of the whole society, including decision-makers, governmental agencies and the general public, and contribute to a true democratisation of knowledge.

Beyond the ethical arguments, Open Data, Reproducible Research, and Open Science also offer an opportunity for young researchers to adapt to a new workflow for performing impacting research and forming unexpected collaborations. Open Data, Reproducible Research, and Open Science can significantly contribute to building a strong research profile, while addressing funder ambitions on stimulating innovation and economic growth through removing all barriers to data and knowledge sharing.

This session is not meant to elaborate abstractly on Open Data, Reproducible Research, and Open Science. Rather, it looks at what is possible nowadays and what is ready for application in geosciences.

The speakers present success stories, failures, best practices, solutions and introduce networks. It is aimed to show how researchers, citizens, funding agencies, governments and other stakeholders can benefit from Open Data, Reproducible Research, and Open Science in various flavors, acknowledging the drawbacks and highlighting the opportunities available for geoscientists.

The session shall open a space to exchange experiences and to present either successful examples or failed efforts. Learning from others and understanding what to adopt and what to change are to help towards own undertakings and new initiatives, so that they become successes.