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The challenging problem of formal verification of SMIL (Synchronized Multimedia Integration Language Specification) documents is considered in this paper, where we propose a hybrid formal method that automatically detects and corrects the temporal and spatial conflicts. The proposed solution is based on a related work that uses Hoare logic for temporal conflict detection in SMIL documents. The use of Hoare logic is borrowed by that solution but with many improvements and extensions. New rules are added to enable modeling of more SMIL elements. We also deal with spatial conflicts and propose a spatio-temporal inconsistencies verification algorithm, called Spatio-temporal Inconsistencies Verification Algorithm (SIVA), that checks the spatial incoherence of SMIL documents. The disjunctive constraints of Marriott are used to correct the spatial inconsistencies. Furthermore, we propose a new tool that helps the author to validate the temporal and spatial constraints in SMIL documents. If any temporal or spatial conflicts are detected, the system returns a help message to report the error and help the author to correct the conflict. Finally, our contribution has been compared with two recent related works, and the results show that the proposed solution allow to check more attributes.

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Coronaviruses have been around for years, they are a large family of viruses that can create a variety of anomaly in humans and even in animals, the first symptoms are summed up by a simple cold with fever but it can spread to very serious respiratory problems. This disease has caused a global crisis on all levels; it's a very big challenge that we have lived it since the Second World War. The challenging problem of COVID-19 data science is considered in this paper, where we propose a new data warhouse, that best meets the needs of scientists. The proposed data warhouse as of February 24, 2020, is based on heterogeneous data provided by Our World in Data GitHub and Kaggle database, which are collected daily from Our World in Data COVID-19. Furthermore, this data warehouse is used to feed dashboards in real time that helps the decision-makers to strengthening of the coronavirus screening network, track the spread of the virus before and after vaccination around the world to fight against this dangerous disease.