Observational data are essential for analyzing past and current environmental trends and for providing appropriate initial, boundary and validation conditions for numerical models used in the environmental sciences (climate, hydrology, cryosphere, biosphere, etc.), but very often access to such data needs to overcome a number of, from the sparseness of data to institutional barriers (confidentiality, cost, etc.). Such barriers impede in many instances the successful outcomes of research programs addressing themes such as climate change, water, or biodiversity protection. In January 2011, a workshop was organized in Riederalp, Switzerland, sponsored by the ‘‘ACQWA'' project (www.acqwa.ch), a large integrating project under the 7th R&D framework programme of the EU (FP7). Over 25 EU projects focusing on water resources and water management were represented. Institutional and financial obstacles to data access for use in modeling exercises were identified, and gaps in scientific knowledge that contribute to uncertainty were highlighted. The workshop served to identify a number of sectors where gaps in data represent barriers to successful research outcomes, and have suggested ways and means of alleviating some of these difficulties.