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Data-driven environmental sustainability should consider not just getting more data, but smarter representation of data. Today's research data handling and publication processes are still largely decoupled. Static datasets are published somewhere, referenced from papers, sometimes updated and then out of sync with the publication. Involving non-researchers in such a data representation is not trivial due to a lack of attractiveness, but would be important to benefit from a larger pool of domain knowledge, and would contribute to make science more attractive overall.

In our work at the Service Prototyping Lab at Zurich University of Applied Sciences, we have gathered some experience with building collaborative dashboards including annotations of interesting data positions, hyperlinking updated data from publications, and conditional formulation of findings to co-evolve with continuously updated data. This short talk aims to inspire raising the barrier for research data handling for future projects to help that the current problem - not enough data about the environment - does not contribute to the next problem - too much data.