In this measurement campaign of five water bodies (lakes and reservoirs) several German research groups organised a joint effort to collect a data set for testing, evaluating, and potentially improving the abilities of satellite-based monitoring of water quality in standing waters. The strategy of the campaign is summarised in Figure 1 (documentation "Conceptual design of Inland Water Remote Sensing Validation Campaign 2017") and consists of three independently measured categories of data: (i) satellite-based monitoring, (ii) in situ monitoring, and (iii) bio-optical characterisation. The latter aspect, in particular, was intended in order to go beyond classical comparison of satellite-based and in-situ observations and to enable a more process-oriented and physically-based assessment of the observations made during the satellite overcasts.We concentrated our work on one week in summer 2017 and organised a synoptically measurement campaign on five lakes in Central Germany (Lake Arendsee, Lake Geiseltalsee, Kelbra Reservoir, Rappbode Reservoir, Lake Süßer See, see Tab. 1 in documentation "Main physical and limnological characteristics of the five water bodies from Inland Water Remote Sensing Validation Campaign 2017") based on various field and lab methods. The synoptically approach required the equipment of five sampling teams that are able to work independently from each other. Field- instruments used during the campaign (which required to be available in five sets) had been compared with each other in a separate intercalibration day. All lab-based measurements took place at the central lab of the Helmholtz-Centre for Environmental Research in Magdeburg using methods as outlined in Friese et al. (2014). The five water bodies were intentionally chosen because they reflect a broad range of temperate standing waters with respect to size, depth, trophic state, and the occurrence of cyanobacterial blooms. In addition, also natural and artificial water bodies are reflected by this set of lakes/reservoirs.To our knowledge, this is one of the rare multiple-teams efforts in remote sensing research on water quality making the collection of data in terms of their synoptic evaluation and broad methodological basis particularly useful and valuable.