In these strange and uncertain COVID 19 times, it is key to invest in data demand and data use for iterative evidence-based decision making and ensuring accuracy in reporting and designing impactful interventions to local, regional and global challenges aimed addressing Agenda 2030 for Sustainable Development.
Using data iteratively and systematically for evidenced-based decision-making is key. Whereas sharing is important, it is key to advocate for the use of the data lest it is rendered not useful and all of the efforts invested in collecting, collating, curating, and making meaning out of this data are wasted.
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?
How to facilitate the development and implementation of open tools and standards for managing and exchanging water data?
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
Whether it flooding, drought or environmental pollution, we cannot mitigate or respond to disasters without data. However, prediction models, mobile apps and web services for policy support can only be used if sufficient data are freely available. Those data are usually collected by governments, funded by taxpayers. Taxpayers should therefore be entitled to access these data, provided they do not infringe the privacy and safety of citizens.I wrote a blog about this for Open Data Day 2019 and I'm curious about your opinions and experiences.