In the last 5 years, the seismological community has experienced an impressive growth in the novel Distributed Acoustic Sensing (DAS) technique, in terms of both the number of experiments and the generated data volume. DAS experiments can generate data at a much finer resolution in space and time, than is seen with standard acquisition techniques. This creates challenges not only for data centres regarding the data management, but also for users that need to access and process this data. The current seismological standards for data and metadata formats, as well as community services specifications, are not capable of handling these datasets in an effective way - not unexpected considering that data volumes and ‘station’ numbers are orders of magnitude larger than typical broad-band experiments.

Within the context of the “Geosphere INfrastructures for QUestions into Integrated REsearch” project (Geo-INQUIRE, https://www.geo-inquire.eu/), we have defined a roadmap to advance towards community standards for some of these aspects. The main objective of improving the FAIRness of these datasets was separated in 3 steps. First, we defined how to archive downsampled versions of the datasets in standard community formats (i.e. miniseed and StationXML). Second, we wanted to support the definition (and foster the adoption) of a new metadata standard for DAS experiments based on the outcome of the DAS Research Coordination Network group (DAS-RCN), an initiative led by US researchers. And finally, we wanted to work on the definition of a data format capable of providing fast processing on the data centre side, as well as being able to provide the data to the user to be processed elsewhere.

We worked with 3 datasets from the Global DAS Month (February 2023), acquired by INGV, ETH and GFZ. These datasets had been published and made available in different non-standard formats. We used these experiments as test cases to later apply this workflow to the datasets generated by the Transnational Access Calls of this project at a variety of Research Infrastructures across Europe (e.g. at Etna, Bedretto, Ligurian, Madeira, Irpinia, and others).

Regarding the data volume and lack of standardisation, we have improved “dastools”, a software package developed at GFZ, to read DAS data in proprietary formats from different manufacturers and convert it to standard miniseed. Downsampling in time and space it provides a reduced version ready to be archived in seismological data centres.

Regarding metadata formats, we included in “dastools” the support for the DAS-RCN proposal, discussed and agreed within the community during the last 3 years. We can generate a first draft version of the metadata based on the information available in the raw data of the experiment. We also added a converter to StationXML (still beta) in order to support each step of the archival of a downsampled version of the DAS data.

We plan to work soon on the definition of a data format for this type of experiment as it is a key part of our project.

In parallel, we’ve just started the development of a Seedlink plugin (real-time transmission) to be deployed and tested at interrogators.

How to cite: Quinteros, J., Currenti, G., Prestifilippo, M., Clinton, J., Edme, P., Wollin, C., Rivet, D., Murphy, S., Schaeffer, J., Pedersen, H., and Strollo, A.: Towards a community standard for DAS metadata: Latest advances within the Geo-INQUIRE project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13131, https://doi.org/10.5194/egusphere-egu24-13131, 2024.

The seismic hazard department and department of the Carpathian region seismicity of the Subbotin Institute of Geophysics of the National Academy of Science of Ukraine, with the support and collaboration of the U.S. Department of Energy, Lawrence Livermore National Laboratory, Michigan State University, and the EarthScope Consortium had done first steps to expand the Ukrainian National Seismic Network (UT) through the installation of permanent broadband seismic stations in the territory of Ukraine.

The main goal of the Seismic Network Expansion and Modernization in Ukraine is to improve regional network coverage by making high-quality data from new stations openly available to the global scientific community in real time. It will strengthen national seismic monitoring and earthquake response capabilities in Ukraine by upgrading and expanding the national networks with high-quality broadband seismometers and strong motion sensors. It will emphasize data quality, real-time data exchange, and network sustainability through training in best practices on station site selection, installation, data management, and network operation.

To maximize the effectiveness of investigating existing and new seismic sites, multiple factors must be considered during the initial selection, preparation, and installation of new seismic stations. One critical component during the site selection process of any seismic network is an assessment of the seismic noise level at potential sites. The capacity of any seismic station to detect earthquakes and record high quality waveforms will be determined by the signal and noise characteristics of the site. Proper site selection is strongly related to the network's region and can be a critical issue. Besides the earth’s natural background noise, there are other noise sources to consider like those related to infrastructure close by (roads, traffic, mining activity, tenants, etc.). The goal of this work is to conduct noise surveys that can be quickly deployed in order to efficiently evaluate potential sites for the installation permanent seismic stations.

An initial noise survey was conducted at two sites: one at an existing site LUBU (near Liubeshka village, Lviv district) and one at a new site SUGL (near Mala Uhol`ka village, Zakarpattia district). We analyzed, and report the data in the form of both time-history examples and standardized Probability Density Function noise plots. Seismic spectral analysis based on the calculation of Power Spectral Density distribution using a Probability Density Function by McNamara approach.

How to cite: Farfuliak, L., Amashukeli, T., Chiang, A., Mackey, K., Haniiev, O., Kuplovskyi, B., Aderhold, K., Burk, D., Prokopyshyn, V., and Petrenko, K.: Initiation of the Seismic Network Expansion and Modernization in Ukraine, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4414, https://doi.org/10.5194/egusphere-egu24-4414, 2024.

Seismic activity in Ukraine varies across regions with notable active zones in the Carpathians and Crimean-Black Sea segments. Southwest Ukraine is affected by the Vrancea seismic zone (Romania) and demands attention, alongside rare but potentially powerful seismic events in the stable Ukrainian shield. Mining and industrial activities also induce ground vibrations (Mw 2.5–4) in otherwise stable areas. Although major destructive earthquakes in Ukraine are infrequent, the cumulative impact of smaller seismic events can shape the geological and geophysical landscape of the region.

An effective seismic network is crucial for safety and research in Ukraine. Yet, the existing seismic network at the Institute of Geophysics of National Academy of Science of Ukraine faces numerous challenges, limiting its capacity to provide accurate seismic information. In addition, the Institute of Geophysics faces a demographic imbalance, with a critical shortage of younger scientists entering the field. This knowledge gap poses implications for the future of scientific research in Ukraine.

In response to these challenges, and considering the Russian invasion, we opted to distribute 28 budget Raspberry Shake Seismographs across schools and universities in Ukraine. Initially, these budget seismometers serve as a short-term solution for seismic data collection. Acknowledging the pros and cons of these stations in contrast to broadband sensors, it's noteworthy that their simplicity in installation, low cost, and near-real-time data transmission make them as a suitable option during the conflict in identifying and characterizing local and regional events.

This initiative also directly supports science teaching from middle to high school in Ukraine. Integrating seismometers into schools cultivates education based on real-time seismic records, familiarizing students with scientific data. The aim is to ignite students’ interest, nurturing a curiosity not only in seismology but also in science as a whole. This goal is accomplished not just through presentations and lessons but also through hands-on involvement, allowing students to take ownership by installing a seismometer and consistently monitoring its output. The analysis of time series seismic signals, regardless of their source – whether earthquakes or artificial noise – forms a fundamental component of any seismology-focused educational program. Currently, such initiatives are lacking in Ukrainian educational institutions.

Raspberry Shake 3D Seismographs have been installed at the Institute of Geophysics in Kyiv, Lviv Polytechnic National University, and Ivan Franko National University of Lviv. Two RS seismometers are at the Mykolaiv Water Hub to support the establishment of the Mykolaiv Innovation Lab in south Ukraine. In November 2023, educational materials for seismology at middle and high school levels in Ukraine were created with the assistance of the GFZ German Research Centre for Geosciences. This approach not only will help students develop practical skills but also provides a starting point for exploring numerical methods and coding at the university level.

How to cite: Amashukeli, T., Malatesta, L., Farfuliak, L., Haniiev, O., Kuplovskyi, B., Prokopyshyn, V., and Petrenko, K.: The prospects of the Ukrainian seismic network:  Introducing a Low-Cost Seismic Network Initiative in Ukraine, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13158, https://doi.org/10.5194/egusphere-egu24-13158, 2024.

The Swedish National Seismic Network (SNSN) currently operates 67 permanent and 13 temporary broadband seismic stations. All stations transmit continuous realtime data to the data centre in Uppsala, and data streams of about 40 stations are automatically forwarded to subscribing institutes in the neighboring countries and to ORFEUS. In addition to the SNSN stations we receive realtime data from about 120 stations located in Norway, Finland, Denmark, Germany, Poland, the Baltic States, and Russia. 

SNSN processes the waveform data of this virtual network of about 200 stations using the SeisComp and Earthworm systems in parallel. Both systems are set up to be very sensitive in order to detect as small events as possible, which also increases the probability of generating spurious events. In order to screen out spurious events we generate a common bulletin which contains events that have been located by both systems independently. Our common bulletin is very reliable (no spurious events during the last 1.5 years), captures events down to about ML = 1 and contains almost all events with ML > 1.5 in Fennoscandia.

All events in the common bulletin are automatically classified by an artificial neural network as earthquakes, blasts or mining-induced events. The classifier has been developed in the framework of a PhD project, and was implemented into the SNSN processing queue during 2023 (Eggertsson et al, "Earthquake or Blast? Classification of Local-Distance Seismic Events in Sweden using Fully-Connected Neural Networks", accepted GJI 2024). It has been thoroughly tested, and, comparing the automatic classification with analyst-reviewed classification, we found a 97% match

Since December 2023, SNSN provides the automatic common bulletin as a simple webpage https://www.snsn.se/combullUTC/ - mainly for the general public and for quick reference. For the seismological community, SNSN has set up an automatic real-time forwarding of complete event parameters for all events with ML >= 2 to the European-Mediterranean Seismological Centre.

How to cite: Roth, M., Eggertsson, G., Schmidt, P., Shomali, H., Oskooi, B., and Lund, B.: The automatic seismic event bulletin of the Swedish National Seismic Network, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12258, https://doi.org/10.5194/egusphere-egu24-12258, 2024.

The Republic of Armenia and the neighboring areas are located in the central part of theArabia-Eurasia collision zone, which is characterized by active seismicity.Over the past decade, the Institute of Geological Sciences (IGS) of NAS RA has developed an advanced and dense seismic network.To develop the local seismic network, the Institute of Geological Sciences in collaboration with the National Taiwan University and Institute of Earth Sciences, Academia Sinica (Taiwan) established 11 seismic stations with broadband seismometers and 6 cGPS (continuous) stations. Data from the existing seismic stations were collected, archived and treated, and main earthquake parameters were determined; the conducted works included catalogue maintenance, recalculation of the main earthquake data, calculation of seismic tomography with the input of recalculated and updated data, and adjustment of the three-dimensional (3D) velocity model for the area of the RA.

Starting from 2017, the Institute of Geological Sciences has participated in two partner ISTC projects: A-2334 Project (Transect) “The Uplift and Seismic Structure of the Greater Caucasus” and KR-2452 Project (SNECCA) “Seismic Network Expansion in the Caucasus and Central Asia” with support from the U.S. Department of Energy.  In the framework of the indicated projects, 32 seismic stations with broadband seismometers were established along with 8 seismic borehole stations with fully broadband seismometers (Real Time) and 8 strong motion sensors. These two projects are implemented through the Seismic Targeted Initiative of the International Science and Technology Center and the Science and Technology Center in Ukraine.The records collected from the eight (8) already operational permanent seismic stations of the indicated network are in real-time mode sent to the International Seismology Center of the IRIS (Incorporated Research Institutions for Seismology). To download and archive the database of seismic stations, a new computer server was acquired under the project, and all required configurations were made to provide for its uninterrupted operation. Seiscomp software set is applied to produce automatic solutions for earthquakes recorded within the region. Adjustments and recalculations of the automatic earthquake solutions are implemented to produce the resulting main earthquake parameters with uncertainties reduced to the rate as low as possible. The collected data from all existing stations are widely used to determine and to re-estimate the main parameters of earthquake occurring in Armenia and in surrounding territories. These data are included in local bulletins and catalogues.For strong motions, the on-going research includes processing of design accelerograms, preparation and analysis of hazard response spectra (RS), selection of the actually recorded (real) acceleration time-history, and spectral matching of the time-history to the hazard response spectrum with application of Seismosoft (Earthquake Engineering Software Solutions, SeismoMatch, SeismoSignal, SeismoSelect, SeismoSpec) software set.All the results obtained from the data seismic stations mentioned above are used for the purposes of scientific research and are summarized in articles.

How to cite: Babayan, G., Sahakyan, E., Babayan, H., Gevorgyan, M., and Sargsyan, L.: Development of the new seismic network of the IGS, Armenia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14842, https://doi.org/10.5194/egusphere-egu24-14842, 2024.

MUDA (geophysical and geochemical MUltiparametric DAtabase) is a new infrastructure of the National Institute of Geophysics and Volcanology (INGV, www.ingv.it) serving geophysical and geochemical multiparametric data, designed and developped in the framework of Dynamic Planet -Working Earth project (https://progetti.ingv.it/it/pian-din).

MUDA is a dynamic and relational database based on MySQL (https://www.mysql.com) with a web interface realised in php (https://www.php.net) using a responsive design technique. The multi-parametric data are stored and organised using a table-structure able of correlating different types of data that allow possible future integration with new type of data acquired through both real-time and off-line transmission vectors.

MUDA collects information from different types of sensors, such as seismometers, accelerometers, hydrogeochemical sensors, sensors for measuring the flux of carbon dioxide on the ground (CO₂), sensors for detecting the concentration of Radon gas and weather stations with the aim of making possible correlations between seismic phenomena and variations in environmental parameters such as the level of groundwater as well as its temperature and electrical conductivity.

MUDA archives and publishes data of multiparametric stations belonging both to permanent (i.e. the National Seismic Network, RSN, https://www.fdsn.org/networks/detail/IV/) or temporary (e.g. PDnet, Massa et al., 2021, https://www.fdsn.org/networks/detail/ZO_2021/) INGV seismic networks, as well as data from a multi-parametric Salse di Nirano Reserve (MO) site in cooperation with the PD PROMUD 2023-2025 (Definition of a multidisciplinary monitoring PROtocol for MUD volcanoes) project and two additional multi-parametric sites installed in the inter-mountain basin of Norcia, as a part of the GEMME 2023-2025 project. Data from Radon stations belong to the INGV-IRON national network (Italian Radon Monitoring Network, https://www.ingv.it/en/monitoring-and-infrastructure/monitoring-networks/ingv-and-its-networks/iron).

MUDA daily publishes multi-parametric data updated to the previous day and offers the chence to view and download dynamic time series for all available data and for different periods, up to a maximum of 30 days. For longer periods, users can request data to muda@ingv.it.

MUDA is now published at http://muda.mi.ingv.it

How to cite: Massa, M., Ferrari, E., Rizzo, A., Lovati, S., and Luzi, L.: MUDA: the dynamic geophysical and geocehmical multiparametric database, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12895, https://doi.org/10.5194/egusphere-egu24-12895, 2024.

Seismic signals coupling to physical (e.g., temperature, pH, Eh, electrical conductivity, flow rate) and geochemical changes in ground and spring waters as well as variations in soil flux regimes (e.g., CO₂, CH₄, radon) represent a valuable tool to better understand the interaction between tectonics and crustal fluids dynamics (e.g., Italiano et al., 2001, 2004; Wang and Manga, 2021; Chiodini et al., 2020; Gori and Barberio, 2022 and references therein). Pre-, co- and post-seismic modifications are markers of the local tectonic stress acting in the crust and are extremely site-specific due to the local geological and lithological features besides being simultaneously influenced by other environmental conditions (e.g., meteorological and climatic). Therefore, local continuous monitoring of all the involved parameters is needed to delineate crustal fluids response to seismicity site by site.
Multiparametric stations have been set up in Italy starting from the end of 2021, placed on the major seismogenic structures, and widely distributed among the Alps, Apennines and Pianura Padana. They are equipped with: (i) sensors installed in water wells measuring water level, temperature, and electrical conductivity; (ii) meteorological sensors measuring atmospheric pressure, temperature, rain, humidity, wind speed and direction; (iii) seismic sensors providing accelerometric and velocimetric datasets; (iv) radon sensors; (v) CO₂ soil flux chamber. 
Data are transmitted in near real-time to an ad hoc developed dynamic relational database (MUDA-geophysical and geochemical MUltiparametric DAtabase) and displayed in a dedicated website (http://muda.mi.ingv.it). The built-in philosophy is to easily compare distinct parameters from the various sensors and possibly recognize cause-effect relationships among them. 
To our knowledge, our new multiparametric network is the first developed in Italy showing all these features.
A statistic approach is also applied to the time-series to investigate intra-annual and inter-annual trends and correlations among different parameters. Alternative methods (e.g., signal decomposition, spike detection) will be presented and discussed. 

References
-Chiodini G., Cardellini C., Di Luccio F., Selva J., Frondini F., Caliro S., Rosiello A., Beddini G., Ventura G., 2020: Correlation between tectonic CO2 Earth degassing and seismicity is revealed by a 10-year record in the Apennines, Italy. Science Advances, https://www.science.org/doi/10.1126/sciadv.abc2938
-Gori F., Barberio M.D., 2022: Hydrogeochemical changes before and during the 2019 Benevento seismic swarm in central-southern Italy. Journal of Hydrology, 604:127250
-Italiano F., Martinelli G., Nuccio P.M., 2001: Anomalies of mantle-derived helium during the 1997 – 1998 seismic swarm of Umbria-Marche, Italy. Geophysical Research Letters, 28(5):839-842
-Italiano F., Martinelli G., Rizzo A., 2004: Geochemical evidence of seismogenic-induced anomalies in the dissolved gases of thermal waters: A case study of Umbria (Central Apennines, Italy) both during and after the 1997–1998 seismic swarm. Geochemistry, Geophysics, Geosystems, 5:11, doi:10.1029/2004GC000720
-Wang C.-Y., Manga M., 2021: Water and Earthquakes. Lecture Notes in Earth System Sciences, Springer Cham, 387 pp., https://doi.org/10.1007/978-3-030-64308-9 

How to cite: Ferrari, E., Massa, M., Rizzo, A. L., Lovati, S., and Di Michele, F.: The Italian multiparametric network for detection and monitoring of earthquake-related crustal fluids alterations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17749, https://doi.org/10.5194/egusphere-egu24-17749, 2024.

Güralp Data Centre (GDC) interface offers ‘one click’ tools to configure instruments to stream data to a central (typically cloud based) server where it is saved in miniSEED in configurable folder structures. This application is particularly important for operators dealing with large volumes of seismic waveform data from regional/national networks.

Additionally, the data can be transmitted to downstream processors such as Earthworm or SeisComP for more advanced seismic monitoring and data analysis. GDC has a simple interface to set up and monitor the operation of the network and is easy to implement into existing systems and networks with minimal configuration as industry standard protocols are employed throughout.

An integrated VPN/Tunnel circumvents Network Address Translations (NATs) present in internet modems and ADSL connections, providing the facility to remotely update digitizer firmware and upload configuration files to multiple units simultaneously.

Long term latency monitoring, network outages and bandwidth usage are captured and displayed in a number of applets that further simplify maintenance of large networks. The GDC dashboard allows network managers to view data integrity over time so that latency performance can be monitored.

Trigger events from instruments can be recorded and displayed on a map as part of a range of features dedicated to EEW implementations. This information is conveyed using the open Common Alert Protocol (CAP). The CAP messages are created by individual station or sub-network triggers and contain important parameters such the on-site recorded PGA, PGV and PGD, providing the lowest possible latency for network early warning.

How to cite: Watkiss, N., Hill, P., Price, E., Foster, C., Clark, A., Restelli, F., and Lindsey, J.: Güralp Data Centre Software for Easy Mass Data Acquisition and Station Metadata Monitoring, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17386, https://doi.org/10.5194/egusphere-egu24-17386, 2024.