Marco Massa, Andrea Luca Rizzo, Davide Scafidi, Elisa Ferrari, Sara Lovati, Lucia Luzi, the MUDA working group
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MUDA: dynamic geophysical and geochemical MUltiparametric DAtabase
Abstract. In this paper, the new dynamic geophysical and geochemical MUltiparametric DAtabase (MUDA) is presented. MUDA is a new infrastructure of the National Institute of Geophysics and Volcanology (INGV), published on-line in December 2023, with the aim of archiving and disseminating multiparametric data collected by multidisciplinary monitoring networks. MUDA is a MySQL relational database with a web interface developed in php, aimed at investigating in quasi real time possible correlations between seismic phenomena and variations in endogenous and environmental parameters. At present, MUDA collects data from different types of sensors such as hydrogeochemical probes for physical-chemical parameters in waters, meteorological stations, detectors of air Radon concentration, diffusive flux of carbon dioxide (CO2) and seismometers belonging both to the National Seismic Network of INGV and to temporary networks installed in the framework of multidisciplinary research projects. MUDA daily publishes data updated to the previous day and offers the chance to view and download multiparametric time series selected for different time periods. The resultant dataset provides broad perspectives in the framework of future high frequency and continuous multiparametric monitorings as a starting point to identify possible seismic precursors for short-term earthquake forecasting. MUDA is now quoted with the Digital Object Identifier https://doi.org/10.13127/muda (Massa et al., 2023).
Earth System Science DataGEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
18.00
自引率
5.30%
发文量
231
审稿时长
35 weeks
期刊介绍:
Earth System Science Data (ESSD) is an international, interdisciplinary journal that publishes articles on original research data in order to promote the reuse of high-quality data in the field of Earth system sciences. The journal welcomes submissions of original data or data collections that meet the required quality standards and have the potential to contribute to the goals of the journal. It includes sections dedicated to regular-length articles, brief communications (such as updates to existing data sets), commentaries, review articles, and special issues. ESSD is abstracted and indexed in several databases, including Science Citation Index Expanded, Current Contents/PCE, Scopus, ADS, CLOCKSS, CNKI, DOAJ, EBSCO, Gale/Cengage, GoOA (CAS), and Google Scholar, among others.