Due to new technologies, improved infrastructures but also enormously driven by the SDGs the amount of data increases day by day.Does every water scientist or expert in national authorities have to be a computer or data scientist in the future?Certainly not, specific knowledge and experience in the different sectors of water research will be equally important in the future, too. However, such skills will become more and more important and the concept and implications of FAIR data principles have to be implemented in teaching world-wide.How does this influence the higher education but also the capacity development?

Better coordination between bilateral, multilateral and private sector investments in water data and tools could provide synergies and reduce unnecessary spending.An example in the water sector are the long-operting data centres federated within the GTN-H that offer a long-term commitment to global (mostly) in-situ water observations (some of them since decades). Their data are widely used by scientific communities. Of course there are many more examples, in particular from space agencies and space-borne observations.- Can external funding for monitoring and capacity building help to encourage beneficiaries to share data with the data centres and the global community to address local and global problems? - Are there best practice examples of how this is a long-term benefit of external funding from which nations benefit?- What are good ways to monitor the impact of observational networks, databases or data sets for decision-making and capacity development? 

Facilitating the development and implementation of open tools and standards for managing and exchanging water data within and between organizations at sub-national, national and international levels could support water management and policy making at various levels.Please share your experience about, e.g.- (un) successful implementation of international standards for data transfer (e.g. OGC WaterML-2. netcdf-CF), or the FAIR Data principles, GEO Data Sharing and Management Principles- good practice examples of shared tools- How to enhance skills development and availability of shared data