Many geoscientific fields experienced a remarkable expansion of capabilities during the last decades due to the increase in computational capacity, new data collection techniques and the availability of high quality data through the internet. This boost of possibilities and data can no longer be handled by specialised software and makes utilisation of many (predominantly commercial) programmes time consuming, expensive, non-transparent, prone to conversion errors and results in a frustratingly steep learning curve. One easy and free solution that bypasses these shortcomings is R. It is no surprise that the number of users increases exponentially. The number of contributed packages (collections of specialised functions) rises in a similar way, which increasingly complicates keeping track with new developments or identifying the most suitable package when starting with a new scientific method.

The goal of this session is to provide a platform for a rich discussion among researchers that have travelled the track sketched above or – even better – that were just about to realise this. We are delighted to offer you a stage to present how you continued your track. We welcome contributions about how R helped you bridging different scientific fields: remote sensing data handling, spatial models, time series analysis and numeric modelling of ecologic, atmospheric/climatic, hydrologic, pedologic, topographic, geodynamic and further data.

We welcome state of the art approaches using R. Presentations of packages and scripts with a geoscientific background, of inherent problems you experienced using R, benchmarks and improvements, conceptual ideas, innovative approaches to data handling, analysis tools and visualisation will make essential contributions.

We decisively invite everybody who does not feel offended by this text to join especially the poster session to enrich our discussion about solutions and pitfalls, about marvellous presentations and painful meanders on the way to a solution.