Over the past 30 years various space-based limb-looking instruments have recorded complementary data on the distribution of ozone in the Earth's atmosphere. The synergistic use of those data records will improve, on the global scale and in the long term, our understanding of interactions between changes in ozone, ultraviolet radiation and climate. Several international efforts were recently launched in this context, like the SPARC/IO3C/IGACO-O3/NDACC Initiative on Past Changes in the Vertical Distribution of Ozone (SI2N), ESA's Climate Change Initiative project on ozone (Ozone_cci), and NASA's Global OZone Chemistry And Related trace gas Data records for the Stratosphere (GOZCARDS). Each ozone vertical profile data record has its particular features determined by the instrument and retrieval characteristics of the measurement system, like e.g. its sampling properties, viewing geometry, spectral range and degradation. Therefore, assessing the mutual consistency and long-term stability of the complementary data records is a prerequisite for the data merging process aimed at by the aforementioned initiatives. In support to the latter, we present such a systematic evaluation of the operational ozone profile data records from the following fourteen limb/occultation profilers: ERBS SAGE-II, UARS HALOE and MLS, SPOT-3 POAM-II and SPOT-4 POAM-III, Odin OSIRIS and SMR, Meteor-3M SAGE-III, Envisat GOMOS, MIPAS and SCIAMACHY, SCISAT-1 ACE-FTS and ACE-MAESTRO, and EOS-Aura MLS. The ground-based networks of ozonesonde and lidar stations affiliated with the Network for the Detection of Atmospheric Composition Change (NDACC) and WMO's Global Atmosphere Watch (GAW) act as a suitable standard transfer of well established quality between the space-based data records. The ground-based transfer enables us to carry out a systematic evaluation of the data quality of each of the fourteen satellite missions using a common comparison methodology. The temporal behavior (long-term drift and annual cycles) of the bias is investigated using robust regression methods. Studies of the vertical and meridian structure of the bias and associated noise yield a threshold altitude below which the satellite data quality degrades rapidly. Our results conclude with a comprehensive overview of the mutual consistency between and the long-term stability of the various limb profilers, and apply directly to the merging activities upon which the different initiatives rely.