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Very large amounts of geospatial data are daily generated by many observation processes in different application domains. The amount of produced data is increasing due to the advances in the use of modern automatic sensing devices and also in the facilities available to promote crowdsourcing data collection initiatives. Spatial observation data includes both data of conventional entities and also samplings over multi-dimensional spaces. Existing observation data management solutions lack declarative specification of spatio-temporal analytics. On the other hand, current data management technologies miss observation data semantics and fail to integrate the management of entities and samplings in a single data modeling solution. The present paper presents the design of a framework that enables spatio-temporal declarative analysis over large warehouses of observation data. It integrates the management of entities and samplings within a simple data model based on the well known mathematical concept of function. Observation data semantics are incorporated into the model with appropriate metadata structures.

IntroductionSex-dependent differences of infective endocarditis (IE) have been reported. Women suffer from IE less frequently than men and tend to present more severe manifestations. Our objective was to analyse the sex-based differences of IE in the clinical presentation, treatment, and prognosis.Material and methodsWe analysed the sex differences in the clinical presentation, modality of treatment and prognosis of IE in a national-level multicentric cohort between 2008 and 2018. All data were prospectively recorded by the GAMES cohort (Spanish Collaboration on Endocarditis).ResultsA total of 3451 patients were included, of whom 1105 were women (32.0%). Women were older than men (mean age, 68.4 vs 64.5). The most frequently affected valves were the aortic valve in men (50.6%) and mitral valve in women (48.7%). Staphylococcus aureus aetiology was more frequent in women (30.1% vs 23.1%; p<0.001).Surgery was performed in 38.3% of women and 50% of men. After propensity score (PS) matching for age and estimated surgical risk (European System for Cardiac Operative Risk Evaluation II (EuroSCORE II)), the analysis of the matched cohorts revealed that women were less likely to undergo surgery (OR 0.74; 95% CI 0.59 to 0.91; p=0.05).The observed overall in-hospital mortality was 32.8% in women and 25.7% in men (OR for the mortality of female sex 1.41; 95% CI 1.21 to 1.65; p<0.001). This statistical difference was not modified after adjusting for all possible confounders.ConclusionsFemale sex was an independent factor related to mortality after adjusting for confounders. In addition, women were less frequently referred for surgical treatment.