The purpose of this dataset is to characterize the types of multiparameter data generated by instrumental networks for monitoring seismic-volcanic phenomena. The dataframe includes indicators that facilitate the detection and classification of files when gaps occur during the transmission of information to various acquisition systems. This allows the identification of patterns of files related to missing data, enabling their subsequent recovery at the source to improve the accuracy and availability of information in monitoring and interpretation centers. The results highlight a generalizable framework for correlating source and target files. This approach covers various acquisition systems and source files, with the aim of improving data continuity in remote instrumental networks, laying the foundation for a gap recovery model applicable to various formats and monitoring networks. It also considers the relevance of the files to be recovered and the volume of data in relation to the capacity of the available transmission media.