Der Datensatz "Intensivkapazitäten und COVID-19-Intensivbettenbelegung in Deutschland" des Robert Koch-Instituts dokumentiert die tägliche intensivmedizinische Versorgungslage seit der COVID-19-Pandemie. Basierend auf Meldungen aller intensivbettenführenden Krankenhäuser in Deutschland erfasst das DIVI-Intensivregister Echtzeitdaten zu belegten und freien Intensivbetten. Die Erhebung differenziert nach Altersgruppen, Regionen und Versorgungsstufen. COVID-19-Fälle auf Intensivstationen werden gesondert ausgewiesen. Die Daten stehen aggregiert auf Bundes-, Landes- und Kreisebene zur Verfügung. Damit bildet der Datensatz eine Grundlage für die Überwachung von Kapazitäten, die Koordination von Behandlungskapazitäten und politische Entscheidungsprozesse während der Pandemie und darüber hinaus.
Burgardt, Sabrina · Feß, Julian · Guthmann, Alexander · et al.
1 files · 43 MB · zip
Data sets as plotted in the preprint "Quantum-enabled active matter at the atomic scale" are uploaded. The zip file "data" contains a folder for each figure in the preprint (named after the figure). Each folder contains the data for all graphs in the respective figure.
Cell characterisation and aging data for a 280 Ah prismatic LFP cell. This data is for the 'LIC' cell from EU Horizon Project: TEMPEST. The following data is included: (1) Capacity tests and HPPC tests at 15, 20, 25, 30, and 35 °C (capacity_hppc_entropy.zip). (2) Entropy coefficient measurements at 0.1, 0.3, 0.5, 0.7, and 0.9 SoC (capacity_hppc_entropy.zip). (3) Aging data for 700 cycles including the raw cycling data and reference performance tests (aging.zip).
Kárpi, Marcell · Szalai, Sándor · Baracza, Mátyás Krisztián
1 files · 1.1 MB · zip
Geoelectric raw data, measured with an Iris Syscal Pro Switch 72, in the park of the University of Miskolc. The data are in .bin format, which can be opened and managed by the free software Prosys II: (Dowload link: https://www.iris-instruments.com/download.html). The used geoelectric arrays are the Wenner-alpha, dipole-dipole, and a quasi-null array G112. In the years we did measurement, precipitation data is also attached. Lithology is given in a table.
40 RGB PNG frames of ERA5 vertically integrated water-vapour transport (IVT) magnitude over the North Pacific, 6-hourly from 2 to 11 February 2017, derived from the public ARCO-ERA5 archive (IVT = sqrt(u^2 + v^2)). Each frame renders an atmospheric river as a bright filament on a dark background and is named NPacific_IVT_0000.png ... NPacific_IVT_0039.png. This is the Earth-observation dataset for the Galaxy Training Network tutorial 'Object tracking using CellProfiler' (https://gxy.io/GTN:T00516), used to demonstrate that a CellProfiler nucleus-tracking pipeline can be reused to detect and track atmospheric rivers. Preprocessing notebooks, full Galaxy run provenance, and the software archive: https://github.com/annefou/fiesta-galaxy-cellprofiler-eo (DOI 10.5281/zenodo.20811614). Part of the OSCARS-FIESTA project.
Der Datensatz "Daten der Notaufnahmesurveillance" wird durch das Robert Koch-Institut und das AKTIN-Notaufnahmeregister bei Krankenhausaufnahmen bereitgestellt. Der Datensatz beinhaltet aggregierte Routinedaten aus deutschen Notaufnahmen zur syndromischen Überwachung von akuten Erkrankungen. Dazu zählen grippeähnliche Erkrankungen (ILI), Coronavirus-Erkrankungen (COVID-19), akute respiratorische Erkrankungen (ARE), gastrointestinale Infektionen (GI) und schwere akute respiratorische Infektionen (SARI). Dabei wird der relative Anteil dieser Erkrankungen an der Gesamtzahl der Notaufnahmevorstellungen sowie die berechneten Erwartungswerte und Prädiktionsintervalle ausgewiesen. Die Daten sind nach Notaufnahmetypen und Altersgruppen aggregiert. Damit bietet der Datensatz eine wertvolle Ressource für die Forschung im Bereich der Notfallmedizin und der Überwachung akuter Gesundheitsereignisse in Deutschland.
This dataset records how individual visitors move through theme parks. Twenty-three consenting adults each carried a 1 Hz GPS logger through one of three Southern-California parks, including Knott's Berry Farm, Disneyland, or Disney California Adventure, on operating days in March 2026, and completed a short exit survey on return. (Four park-hoppers visited both Disney parks, giving 26 analyzed park-visits in total.) From each track, the visitor's day was coded into a sequence of point-of-interest (POI) stops with arrival and departure times and walked-versus-shortest-path distances, summarized into per-visit movement metrics (time in park, walking speed, distance traveled, visit and attraction rates, route directness, dwell time, and more), and tagged with a movement-style label (wader, swimmer, or diver). Each visitor's exit-survey responses (prior visitation, planning, priorities, map use, self-described movement) are included as well. Contents and structure. The data is organized one folder per park ( kbf/ , dlr/ , dca/ ), each with the same layout, in open formats (CSV and GeoPackage): tables/ : participants, per-visit movement metrics, the stop-by-stop timetable, and exit-survey responses; gps/ : raw and cleaned GPS point tracks (longitude/latitude, elevation, speed, local time-of-day); gis/ : park boundary, walkways, commercial and attraction areas, and a points-of-interest layer (all parks); Knott's additionally includes a walkway routing network ( PathNetwork ) used for shortest-path and agent-based modeling; heatmaps/ : observed occupancy rasters (GeoTIFF) for each movement type - waders, swimmers, divers, and all participants. A code/ folder accompanies the data with the analysis and agent-based-simulation code that regenerates the associated article's data-driven figures, tables, and statistics directly from these files (see code/README.md ). Within each park, every file is keyed by participant_id ; see README.md for full field definitions. The data supports analyses of pedestrian movement, dwell and routing behavior, visitor segmentation, and spatial or agent-based modeling of theme-park circulation. De-identification and ethics. Data were collected under Princeton University IRB Protocol #19130 with informed consent. Participants appear only as codes; GPS timestamps give local time-of-day with calendar dates removed; coordinates are WGS84 (EPSG:4326). This is a small, non-representative sample collected on a few operating days; best treated as a pilot/exemplar rather than a representative survey. The reproduction code is included in this record under code/ , and a related study by the authors is linked under the record's Related works . The data are released under CC-BY-4.0 and the code under the MIT License. Theme-park and attraction names appear only for geographic context and remain the property of their respective owners.
This dataset contains the Scopus search strings, raw yearly publication count exports, and derived data used to prepare Figure 1 of the DFG project proposal "Multi-edge laboratory XAS for operando and in situ measurement on 3d-transition metals". The figure illustrates publication trends relevant to the methodological motivation for simultaneous multi-edge laboratory X-ray absorption spectroscopy (XAS). The dataset includes four Scopus TITLE-ABS-KEY searches covering the broader XAS literature, the in situ/operando XAS parent field, explicitly identifiable multi-edge XAS publications, and multimetallic material systems relevant to catalysis and energy storage. Raw Scopus "Analyze search results by year" exports are provided together with derived tab-separated data files used for the indexed growth plot and the multi-edge XAS share relative to the in situ/operando XAS parent field. The data were retrieved from Scopus on 23 June 2026. The counts should be interpreted as conservative trend indicators rather than a complete bibliometric analysis, because relevant studies may not explicitly use the searched terms in title, abstract, or keywords.
This dataset contains the sequencing reads and mapping-derived coverage files corresponding to the UG5 genomic island of Sinorhizobium meliloti RMO17. Paired-end reads mapped to the UG5 region were extracted and processed using Bowtie2, Samtools, Bedtools and deepTools. The dataset includes raw FASTQ.gz files (R1, R2 and unpaired), the reference sequence of the UG5 genomic island (FASTA), genomic annotations (BED), genome size file, and all mapping-derived products (sorted BAM/BAl, bedGraph, and bigWig files with raw and CPM-normalized coverage). The dataset is organised in a structured directory (raw_reads, reference, mapping_products, metadata) to facilitate reuse and reproducibility. This resource supports the analyses reported in the associated manuscript.
Vasina, Michal · Kovář, David · Kizovský, Martin · et al.
2 files · 16 MB · zip
The dataset comprises raw and processed data from the CascadeMAP microfluidic platform collected during optimization of glycerol detection pathway by the approach of Design-of-Experiments using fluorescence detection. All the details information about a particular experiment are summarized in relevant readme text files. Experiment 01 presents data from optimization of enzyme ratios, while Experiment 02 extends the optimization to enzyme ratios, temperature and pH. The results from this dataset are presented in the CascadeMAP preprint, to be found on bioRxiv. The results from Experiment 01 and 02 appear in Figure 2 c and e , respectively.
The data and python scripts used in the Paper Techno-Economic Analysis of Hydrocarbon-CO 2 Binary Mixtures in Heat Pump-Based Thermal Energy Storages published in Energy Technology, Volume 14 , Issue 4, Apr 2026, https://doi.org/10.1002/ente.202502620 is provided here. These are data for heat pump simulations with zeotropic mixtures, which are coupled to thermal energy storages, as used in Carnot batteries. Butane, isobutane, pentane, and isopentane mixtures with CO2 are investigated as working fluids. In addition investment costs and levelized costs of heat are analyzed and their global sensitivity and uncertainty is estimated.
Source data used to produce the journal article " Predominant proton insertion during electrochemical cycling of ε-VOPO 4 in a non-aqueous Ca ion electrolyte"
Winter, Henry · Severino, MaryKay · Volunteer Scientist
7 rows × 11 cols · 985 B · csv, pdf, zip
11 categorical
These are audio recordings taken by an Eclipse Soundscapes (ES) Data Collector during the week of the April 08, 2024 Partial Solar Eclipse. It was decided to include only raw, unprocessed audio data files in each site-specific ZIP archive and in each Zenodo record. This decision was so that any researcher can independently verify, reproduce, and extend the analysis performed. As a result, some sites have WAV files with 0 bytes of data or timestamps outside the range of probable recording times. Procedures used by the Eclipse Soundscapes team to process audio data for its purposes are outlined in the Data Management reports located in the Eclipse Soundscapes Zenodo community. Data with 0 bytes of data were included for completeness. Data Site location information: Latitude: 29.523398 Longitude: -95.803043 Local Eclipse Type: Partial Solar Eclipse Solar Eclipse Eclipse Percent (%): 94.47 WAV files Time & Date Settings: Set with Automated AudioMoth Time Chime (More information on TimeStamp Setting below) Data Collector Start Time Notes: N/A Included Data: Audio files in WAV format with the date and time in UTC within the file name: YYYYMMDD_HHMMSS meaning YearMonthDay_HourMinuteSecond For example, 20240411_141600.WAV means that this audio file starts on April 11, 2024 at 14:16:00 Coordinated Universal Time (UTC) CONFIG Text file: Includes AudioMoth device setting information, such as sample rate in Hertz (Hz), gain, firmware, etc. README.md: Markdown formatted file with information about the recording and recording site. file_list.csv: A machine and human file that gives the following information on each file in the record: File Name, File Type, Description, File Size in kilobytes, Name of Associated Data Dictionary with the file, calculated SHA-512 Hash of the file as a unique identifier to insure data integrity during transfer and compression. total_eclipse_data.csv: A machine and human readable file that gives the following information about the site where the audio data recording was taken: ESID#, Latitude, Longitude, Eclipse_type, CoveragePercent, Eclipse Start UTC (1st contact), Totality Start UTC (2nd contact), Totality End UTC (3rd Contact), Eclipse End UTC (4th Contact), Max Eclipse Time UTC License.txt: A human readable file that explains the terms and conditions under which the data can be used. AudioMoth_Operation_Manual.pdf: A human readable document that explains the use of an AudioMoth device. The document is current up to the time of the AudioMoth's use in the Eclipse Soundscapes project. file_list_data_dict.csv: A machine and human data dictionary file that gives information on the variables contained within the file_list.csv file. CONFIG_data_dict.csv: A machine and human data dictionary file that gives information on the variables contained within the CONFIG.TXT file. eclipse_data_data_dict.csv: A machine and human data dictionary file that gives information on the variables contained within the total_eclipse_data.csv file. WAV_data_dict.csv: A machine and human data dictionary file that gives information on the variables contained within the *.WAV files. ES_Data_Management_Pre-Eclipse_Data_Infrastructure_Stage_0.pdf: PDF document that describes Stage 0 (Pre-Eclipse Infrastructure and Data Stewardship Planning) of the Eclipse Soundscapes (ES) data lifecycle. ES_Data_Management_Receipt_Sorting_and_Metadata_Organization_Stage_1.pdf: PDF document that describes Stage 1 (Receipt, Sorting, and Metadata Organization) of the Eclipse Soundscapes (ES) data lifecycle. ES_Data_Management_Data_Processing_Stage_2.pdf: PDF document that describes Stage 2 (Data Processing) of the Eclipse Soundscapes (ES) data Volunteer Scientists. 2023 and 2024 solar eclipse soundscapes audio datalifecycle. ES_Data_Management_Data_Sharing_Stage_3.pdf: PDF document that describes Stage 3 (Public Data Sharing) of the Eclipse Soundscapes (ES) data lifecycle. Eclipse Information for this location: Eclipse Date: April 08, 2024 Eclipse Start Time (UTC) (1st Contact): 17:18:47 Totality Start Time (UTC) (2nd Contact): [N/A if partial eclipse] N/A Eclipse Maximum Time [when the most possible amount of the Sun in blocked] (UTC): 18:38:58 Totality End Time (UTC) (3rd Contact): [N/A if partial eclipse] N/A Eclipse End Time (UTC) (4th Contact): [N/A if partial eclipse] 20:00:03 Audio Data Collection During Eclipse Week ES Data Collectors used AudioMoth devices to record audio data, known as soundscapes, over a 5-day period during the eclipse week: 2 days before the eclipse, the day of the eclipse, and 2 days after. The complete raw audio data collected by the Data Collector at the location mentioned above is provided here. This data may or may not cover the entire requested timeframe due to factors such as availability, technical issues, or other unforeseen circumstances. ES ID# Information: Each AudioMoth recording device was assigned a unique Eclipse Soundscapes Identification Number (ES ID#). This identifier connects the audio data, submitted via a MicroSD card, with the latitude and longitude information provided by the data collector through an online form. The ES team used the ES ID# to link the audio data with its corresponding location information and then uploaded this raw audio data and location details to Zenodo. This process ensures the anonymity of the ES Data Collectors while allowing them to easily search for and access their audio data on Zenodo. TimeStamp Information: The ES team and the Data Collectors took care to set the date and time on the AudioMoth recording devices using an AudioMoth time chime before deployment, ensuring that the recordings would have an automatic timestamp. However, participants also manually noted the date and start time as a backup in case the time chime setup failed. The notes above indicate whether the WAV audio files for this site were timestamped manually or with the automated AudioMoth time chime. Common Timestamp Error: Some AudioMoth devices experienced a malfunction where the timestamp on audio files reverted to a date in 1970 or before, even after initially recording correctly. Despite this issue, the affected data was still included in this ES site's collected raw audio dataset. Latitude & Longitude Information: The latitude and longitude for each site was taken manually by data collectors and submitted to the ES team, either via a web form or on paper. It is shared in Decimal Degrees format. General Project Information: The Eclipse Soundscapes Project is a NASA Volunteer Science project funded by NASA Science Activation that is studying how eclipses affect life on Earth during the October 14, 2023 annular solar eclipse and the April 8, 2024 total solar eclipse. Eclipse Soundscapes revisits an eclipse study from almost 100 years ago that showed that animals and insects are affected by solar eclipses! Like this study from 100 years ago, ES asked for the public's help. ES uses modern technology to continue to study how solar eclipses affect life on Earth! Eclipse Soundscapes is an enterprise of ARISA Lab, LLC and is supported by NASA award No. 80NSSC21M0008. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Aeronautics and Space Administration. Eclipse map/figure/table/predictions courtesy of Fred Espenak, NASA/Goddard Space Flight Center, from eclipse.gsfc.nasa.gov . Eclipse Data Version Definitions {1st digit = year, 2nd digit = Eclipse type (1=Total Solar Eclipse, 9=Annular Solar Eclipse, 0=Partial Solar Eclipse), 3rd digit is unused and in place for future use} 2023.9.0 = Week of October 14, 2023 Annular Eclipse Audio Data, Path of Annularity (Annular Eclipse) 2023.0.0 = Week of October 14, 2023 Annular Eclipse Audio Data, OFF the Path of Annularity (Partial Eclipse) 2024.1.0 = Week of April 8, 2024 Total Solar Eclipse Audio Data, Path of Totality (Total Solar Eclipse) 2024.0.0 = Week of April 8, 2024 Total Solar Eclipse Audio Data , OFF the Path of Totality (Partial Solar Eclipse) *Please note that this dataset's version number is listed below. Eclipse Soundscapes Data Collector Role Training and Implementation Resources Manual (2023-2024) (Archival Copy) This site-level record includes the Eclipse Soundscapes Data Collector Role Training and Implementation Resources Manual (2023-2024) . The manual documents the participant training, device setup procedures, metadata submission requirements, ES ID system, timestamp protocols, data return workflow, and public archiving processes used during the October 14, 2023 annular solar eclipse and the April 8, 2024 total solar eclipse. The manual is preserved for transparency and reproducibility and reflects the procedures under which this dataset was collected and processed. (DOI 10.5281/zenodo.18623442) Data Receipt, Processing, and Analysis Methods All programs supporting Stages 1–3 are openly available in the: Eclipse Soundscapes GitHub repository: https://github.com/ARISA-Lab-LLC/ESCSP Data Management Lifecycle The following section documents the relationship of this record to the full Eclipse Soundscapes (ES) data lifecycle, a multi-stage workflow designed to support large-scale participatory science, long-term data stewardship, open science, and scientific reuse. Each stage addressed a different operational need, beginning before eclipse deployment and continuing through validation, public archiving, and scientific analysis. Together, these stages transformed distributed volunteer-submitted audio recordings into structured, documented, publicly accessible NASA-funded research assets. Stage 0: Pre-Eclipse Infrastructure and Deployment Preparation Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Management: Pre-Eclipse Infrastructure and Deployment Preparation (Stage 0). Zenodo. https://doi.org/10.5281/zenodo.20413370 Stage 0 focused on building the operational foundation required to support geographically distributed eclipse data collection at national scale. This stage included AudioMoth device preparation, accessibility modifications, ES ID # assignment systems, metadata collection workflows, participant training materials, deployment logistics, and planning for downstream data stewardship and archival workflows. The 2023 annular eclipse served as both a scientific investigation and a large-scale operational beta test that informed improvements for the 2024 total solar eclipse campaign. Related Citations and Resources: Severino, M., & Kline, T. (2025, November 24). Eclipse Soundscapes Apprentice Role Curriculum: Solar Eclipses and Multi-Sensory Observing (Informal Education). Zenodo. https://doi.org/10.5281/zenodo.17703003 Severino, M., & Bauer, D. J. (2026). Eclipse Soundscapes Observer Role Training and Resources Manual (2023–2024). Zenodo. https://doi.org/10.5281/zenodo.18633602< /li> Severino, M., Winter, H., & Bauer, D. J. (2026). Eclipse Soundscapes Data Collector Role Training and Implementation Manual (2023–2024). Zenodo. https://doi.org/10.5281/zenodo.18623443 Stage 1: Receipt, Sorting, and Metadata Organization Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Management: Receipt, Sorting, and Metadata Organization (Stage 1). Zenodo. https://doi.org/10.5281/zenodo.19471425 Stage 1 transformed returned participant materials into organized, traceable site-level records. This included receiving mailed microSD cards, consolidating participant-submitted metadata, reconciling handwritten and online records, organizing physical audio media by ES ID #, and deriving eclipse timing and coverage information using NASA eclipse prediction datasets. The outputs of Stage 1 established the structured metadata relationships required for downstream validation, processing, archiving, and analysis workflows. Related Citations and Resources: Winter, H., & Goncalves, J. (2026). EPTT (Eclipse Phase Timing Tool) [Computer software]. GitHub. https://github.com/ARISA-Lab-LLC/ESCSP-Eclipse-Phase-Timing-Tool /li> Espenak, F. (n.d.). Eclipse predictions by Fred Espenak, NASA's GSFC Eclipse Web Site. NASA Goddard Space Flight Center. http://eclipse.gsfc.nasa.gov/eclipse.html Stage 2: Data Processing and Validation Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Management: Data Processing (Stage 2). Zenodo. https://doi.org/10.5281/zenodo.18683402 Stage 2 focused on centralized audio ingestion, validation, timestamp verification, metadata reconciliation, and preparation of datasets for analysis and public sharing. During this stage, returned audio recordings were processed using custom open-source tools developed by the ES team, including ES WAVES and ES AMES. The project implemented scalable infrastructure capable of processing large volumes of participant-submitted microSD cards while preserving all raw audio data without modification. Stage 2 established the validated dataset structure required for long-term preservation and scientific analysis. Related Citations and Resources: Winter, H., & Goncalves, J. (2026). ES WAVES (Eclipse Soundscapes WAV Audio Validation & Extraction Suite) [Computer software]. GitHub. https://github.com/ARISA-Lab-LLC/ESCSP-ES-WAV-Audio-Validation-Extraction-Suite Winter, H., & Goncalves, J. (2026). ES AMES (Eclipse Soundscapes AudioMoth Metadata Extractor Suite) [Computer software]. GitHub. https://github.com/ARISA-Lab-LLC/ESCSP-ES-AMES-AudioMoth-Metadata-Extractor-Suite Stage 3: Public Data Sharing and Open Archiving Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Management: Public Audio Data Sharing (Stage 3). Zenodo. https://doi.org/10.5281/zenodo.18683437 Stage 3 transformed validated site-level datasets into publicly archived, DOI-assigned research records published through the Eclipse Soundscapes Zenodo Community. This stage included dataset packaging, metadata standardization, README generation, integrity verification, DOI assignment, and automated repository upload workflows using the Automated Zenodo Upload Software (AZUS). These workflows established the project's long-term open-science infrastructure and ensured that datasets remained findable, accessible, interoperable, reusable, and citable for future scientific and educational use. Related Citations and Resources: Winter, H., & Goncalves, J. (2026). AZUS (Automated Zenodo Upload Software) [Computer software]. GitHub. https://github.com/ARISA-Lab-LLC/AZUS-Automated-Zenodo-Upload-Software Stage 4: Scientific Analysis and Research Use Stage 4 involves the scientific analysis and interpretation of validated eclipse soundscape datasets. Analysis workflows utilized datasets verified during earlier stages to investigate eclipse-related environmental and animal vocalization changes across hundreds of recording sites. This stage also includes broader scientific interpretation, publication development, and continued reuse of Eclipse Soundscapes datasets and infrastructure for future research, education, and open-science applications. Related Citations and Resources: Pease, B., Gilbert, N., & Severino, M. (2026). Eclipse Soundscapes Preliminary Findings – How Eclipses Affect Nature as determined by Sound (Recorded Webinar). Zenodo. https://doi.org/10.5281/zenodo.18613979 Gilbert, N. A., Pease, B. S., Severino, M., & Winter, H. III. (2026). Photic niche explains avian behavioral responses to solar eclipses. Ecology and Evolution, 16(2), e73090. https://doi.org/10.1002/ece3.73090 Analysis code repository: https://github.com/BrentPease1/eclipse-traits Companion Zenodo record archiving structured analysis scripts and derived outputs: https://doi.org/10.5281/zenodo.15790879[r] Public Archiving, Privacy, and Data Transparency The Eclipse Soundscapes Data Collector Role Training and Implementation Manual (2023-2024) includes a detailed explanation of how Eclipse Soundscapes audio data are publicly archived on Zenodo, how participant privacy is protected through the ES ID system, and how transparency and traceability are maintained. It also outlines the criteria for determining which recordings are included in the public archive, as well as the distinction between publicly shared archival data and datasets used for ES-led scientific analyses. Participants and data users can consult this section for full documentation of the project's open science and privacy practices. Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Collector Role Training and Implementation Manual (2023–2024). Zenodo. https://doi.org/10.5281/zenodo.18623443 Citations Individual Site Citation: APA Citation (7th edition) Winter, H., Severino, M., & Volunteer Scientist. (2026). 2024 solar eclipse soundscapes audio data [Audio dataset, ES ID# 204]. Zenodo.{Insert DOI} Collected by volunteer scientists as part of the Eclipse Soundscapes Project. This project is supported by NASA award No. 80NSSC21M0008. Eclipse Community Citation Winter, H., Severino, M., & Volunteer Scientists. 2023 and 2024 solar eclipse soundscapes audio data [Collection of audio datasets]. Eclipse Soundscapes Community, Zenodo. https://zenodo.org/communities/eclipsesoundscapes/ Collected by volunteer scientists as part of the Eclipse Soundscapes Project This project is supported by NASA award No. 80NSSC21M0008.
Winter, Henry · Severino, MaryKay · Volunteer Scientist
16 files · 31 MB · csv, pdf, zip
These are audio recordings taken by an Eclipse Soundscapes (ES) Data Collector during the week of the April 08, 2024 Total Solar Eclipse. It was decided to include only raw, unprocessed audio data files in each site-specific ZIP archive and in each Zenodo record. This decision was so that any researcher can independently verify, reproduce, and extend the analysis performed. As a result, some sites have WAV files with 0 bytes of data or timestamps outside the range of probable recording times. Procedures used by the Eclipse Soundscapes team to process audio data for its purposes are outlined in the Data Management reports located in the Eclipse Soundscapes Zenodo community. Data with 0 bytes of data were included for completeness. Data Site location information: Latitude: 32.20485 Longitude: -97.65127 Local Eclipse Type: Total Solar Eclipse Solar Eclipse Eclipse Percent (%): 100 WAV files Time & Date Settings: Set with Automated AudioMoth Time Chime (More information on TimeStamp Setting below) Data Collector Start Time Notes: N/A Included Data: Audio files in WAV format with the date and time in UTC within the file name: YYYYMMDD_HHMMSS meaning YearMonthDay_HourMinuteSecond For example, 20240411_141600.WAV means that this audio file starts on April 11, 2024 at 14:16:00 Coordinated Universal Time (UTC) CONFIG Text file: Includes AudioMoth device setting information, such as sample rate in Hertz (Hz), gain, firmware, etc. README.md: Markdown formatted file with information about the recording and recording site. file_list.csv: A machine and human file that gives the following information on each file in the record: File Name, File Type, Description, File Size in kilobytes, Name of Associated Data Dictionary with the file, calculated SHA-512 Hash of the file as a unique identifier to insure data integrity during transfer and compression. total_eclipse_data.csv: A machine and human readable file that gives the following information about the site where the audio data recording was taken: ESID#, Latitude, Longitude, Eclipse_type, CoveragePercent, Eclipse Start UTC (1st contact), Totality Start UTC (2nd contact), Totality End UTC (3rd Contact), Eclipse End UTC (4th Contact), Max Eclipse Time UTC License.txt: A human readable file that explains the terms and conditions under which the data can be used. AudioMoth_Operation_Manual.pdf: A human readable document that explains the use of an AudioMoth device. The document is current up to the time of the AudioMoth's use in the Eclipse Soundscapes project. file_list_data_dict.csv: A machine and human data dictionary file that gives information on the variables contained within the file_list.csv file. CONFIG_data_dict.csv: A machine and human data dictionary file that gives information on the variables contained within the CONFIG.TXT file. eclipse_data_data_dict.csv: A machine and human data dictionary file that gives information on the variables contained within the total_eclipse_data.csv file. WAV_data_dict.csv: A machine and human data dictionary file that gives information on the variables contained within the *.WAV files. ES_Data_Management_Pre-Eclipse_Data_Infrastructure_Stage_0.pdf: PDF document that describes Stage 0 (Pre-Eclipse Infrastructure and Data Stewardship Planning) of the Eclipse Soundscapes (ES) data lifecycle. ES_Data_Management_Receipt_Sorting_and_Metadata_Organization_Stage_1.pdf: PDF document that describes Stage 1 (Receipt, Sorting, and Metadata Organization) of the Eclipse Soundscapes (ES) data lifecycle. ES_Data_Management_Data_Processing_Stage_2.pdf: PDF document that describes Stage 2 (Data Processing) of the Eclipse Soundscapes (ES) data Volunteer Scientists. 2023 and 2024 solar eclipse soundscapes audio datalifecycle. ES_Data_Management_Data_Sharing_Stage_3.pdf: PDF document that describes Stage 3 (Public Data Sharing) of the Eclipse Soundscapes (ES) data lifecycle. Eclipse Information for this location: Eclipse Date: April 08, 2024 Eclipse Start Time (UTC) (1st Contact): 17:20:54 Totality Start Time (UTC) (2nd Contact): [N/A if partial eclipse] 18:38:29 Eclipse Maximum Time [when the most possible amount of the Sun in blocked] (UTC): 18:40:14 Totality End Time (UTC) (3rd Contact): [N/A if partial eclipse] 18:42:00 Eclipse End Time (UTC) (4th Contact): [N/A if partial eclipse] 20:00:33 Audio Data Collection During Eclipse Week ES Data Collectors used AudioMoth devices to record audio data, known as soundscapes, over a 5-day period during the eclipse week: 2 days before the eclipse, the day of the eclipse, and 2 days after. The complete raw audio data collected by the Data Collector at the location mentioned above is provided here. This data may or may not cover the entire requested timeframe due to factors such as availability, technical issues, or other unforeseen circumstances. ES ID# Information: Each AudioMoth recording device was assigned a unique Eclipse Soundscapes Identification Number (ES ID#). This identifier connects the audio data, submitted via a MicroSD card, with the latitude and longitude information provided by the data collector through an online form. The ES team used the ES ID# to link the audio data with its corresponding location information and then uploaded this raw audio data and location details to Zenodo. This process ensures the anonymity of the ES Data Collectors while allowing them to easily search for and access their audio data on Zenodo. TimeStamp Information: The ES team and the Data Collectors took care to set the date and time on the AudioMoth recording devices using an AudioMoth time chime before deployment, ensuring that the recordings would have an automatic timestamp. However, participants also manually noted the date and start time as a backup in case the time chime setup failed. The notes above indicate whether the WAV audio files for this site were timestamped manually or with the automated AudioMoth time chime. Common Timestamp Error: Some AudioMoth devices experienced a malfunction where the timestamp on audio files reverted to a date in 1970 or before, even after initially recording correctly. Despite this issue, the affected data was still included in this ES site's collected raw audio dataset. Latitude & Longitude Information: The latitude and longitude for each site was taken manually by data collectors and submitted to the ES team, either via a web form or on paper. It is shared in Decimal Degrees format. General Project Information: The Eclipse Soundscapes Project is a NASA Volunteer Science project funded by NASA Science Activation that is studying how eclipses affect life on Earth during the October 14, 2023 annular solar eclipse and the April 8, 2024 total solar eclipse. Eclipse Soundscapes revisits an eclipse study from almost 100 years ago that showed that animals and insects are affected by solar eclipses! Like this study from 100 years ago, ES asked for the public's help. ES uses modern technology to continue to study how solar eclipses affect life on Earth! Eclipse Soundscapes is an enterprise of ARISA Lab, LLC and is supported by NASA award No. 80NSSC21M0008. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Aeronautics and Space Administration. Eclipse map/figure/table/predictions courtesy of Fred Espenak, NASA/Goddard Space Flight Center, from eclipse.gsfc.nasa.gov . Eclipse Data Version Definitions {1st digit = year, 2nd digit = Eclipse type (1=Total Solar Eclipse, 9=Annular Solar Eclipse, 0=Partial Solar Eclipse), 3rd digit is unused and in place for future use} 2023.9.0 = Week of October 14, 2023 Annular Eclipse Audio Data, Path of Annularity (Annular Eclipse) 2023.0.0 = Week of October 14, 2023 Annular Eclipse Audio Data, OFF the Path of Annularity (Partial Eclipse) 2024.1.0 = Week of April 8, 2024 Total Solar Eclipse Audio Data, Path of Totality (Total Solar Eclipse) 2024.0.0 = Week of April 8, 2024 Total Solar Eclipse Audio Data , OFF the Path of Totality (Partial Solar Eclipse) *Please note that this dataset's version number is listed below. Eclipse Soundscapes Data Collector Role Training and Implementation Resources Manual (2023-2024) (Archival Copy) This site-level record includes the Eclipse Soundscapes Data Collector Role Training and Implementation Resources Manual (2023-2024) . The manual documents the participant training, device setup procedures, metadata submission requirements, ES ID system, timestamp protocols, data return workflow, and public archiving processes used during the October 14, 2023 annular solar eclipse and the April 8, 2024 total solar eclipse. The manual is preserved for transparency and reproducibility and reflects the procedures under which this dataset was collected and processed. (DOI 10.5281/zenodo.18623442) Data Receipt, Processing, and Analysis Methods All programs supporting Stages 1–3 are openly available in the: Eclipse Soundscapes GitHub repository: https://github.com/ARISA-Lab-LLC/ESCSP Data Management Lifecycle The following section documents the relationship of this record to the full Eclipse Soundscapes (ES) data lifecycle, a multi-stage workflow designed to support large-scale participatory science, long-term data stewardship, open science, and scientific reuse. Each stage addressed a different operational need, beginning before eclipse deployment and continuing through validation, public archiving, and scientific analysis. Together, these stages transformed distributed volunteer-submitted audio recordings into structured, documented, publicly accessible NASA-funded research assets. Stage 0: Pre-Eclipse Infrastructure and Deployment Preparation Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Management: Pre-Eclipse Infrastructure and Deployment Preparation (Stage 0). Zenodo. https://doi.org/10.5281/zenodo.20413370 Stage 0 focused on building the operational foundation required to support geographically distributed eclipse data collection at national scale. This stage included AudioMoth device preparation, accessibility modifications, ES ID # assignment systems, metadata collection workflows, participant training materials, deployment logistics, and planning for downstream data stewardship and archival workflows. The 2023 annular eclipse served as both a scientific investigation and a large-scale operational beta test that informed improvements for the 2024 total solar eclipse campaign. Related Citations and Resources: Severino, M., & Kline, T. (2025, November 24). Eclipse Soundscapes Apprentice Role Curriculum: Solar Eclipses and Multi-Sensory Observing (Informal Education). Zenodo. https://doi.org/10.5281/zenodo.17703003 Severino, M., & Bauer, D. J. (2026). Eclipse Soundscapes Observer Role Training and Resources Manual (2023–2024). Zenodo. https://doi.org/10.5281/zenodo.18633602< /li> Severino, M., Winter, H., & Bauer, D. J. (2026). Eclipse Soundscapes Data Collector Role Training and Implementation Manual (2023–2024). Zenodo. https://doi.org/10.5281/zenodo.18623443 Stage 1: Receipt, Sorting, and Metadata Organization Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Management: Receipt, Sorting, and Metadata Organization (Stage 1). Zenodo. https://doi.org/10.5281/zenodo.19471425 Stage 1 transformed returned participant materials into organized, traceable site-level records. This included receiving mailed microSD cards, consolidating participant-submitted metadata, reconciling handwritten and online records, organizing physical audio media by ES ID #, and deriving eclipse timing and coverage information using NASA eclipse prediction datasets. The outputs of Stage 1 established the structured metadata relationships required for downstream validation, processing, archiving, and analysis workflows. Related Citations and Resources: Winter, H., & Goncalves, J. (2026). EPTT (Eclipse Phase Timing Tool) [Computer software]. GitHub. https://github.com/ARISA-Lab-LLC/ESCSP-Eclipse-Phase-Timing-Tool /li> Espenak, F. (n.d.). Eclipse predictions by Fred Espenak, NASA's GSFC Eclipse Web Site. NASA Goddard Space Flight Center. http://eclipse.gsfc.nasa.gov/eclipse.html Stage 2: Data Processing and Validation Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Management: Data Processing (Stage 2). Zenodo. https://doi.org/10.5281/zenodo.18683402 Stage 2 focused on centralized audio ingestion, validation, timestamp verification, metadata reconciliation, and preparation of datasets for analysis and public sharing. During this stage, returned audio recordings were processed using custom open-source tools developed by the ES team, including ES WAVES and ES AMES. The project implemented scalable infrastructure capable of processing large volumes of participant-submitted microSD cards while preserving all raw audio data without modification. Stage 2 established the validated dataset structure required for long-term preservation and scientific analysis. Related Citations and Resources: Winter, H., & Goncalves, J. (2026). ES WAVES (Eclipse Soundscapes WAV Audio Validation & Extraction Suite) [Computer software]. GitHub. https://github.com/ARISA-Lab-LLC/ESCSP-ES-WAV-Audio-Validation-Extraction-Suite Winter, H., & Goncalves, J. (2026). ES AMES (Eclipse Soundscapes AudioMoth Metadata Extractor Suite) [Computer software]. GitHub. https://github.com/ARISA-Lab-LLC/ESCSP-ES-AMES-AudioMoth-Metadata-Extractor-Suite Stage 3: Public Data Sharing and Open Archiving Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Management: Public Audio Data Sharing (Stage 3). Zenodo. https://doi.org/10.5281/zenodo.18683437 Stage 3 transformed validated site-level datasets into publicly archived, DOI-assigned research records published through the Eclipse Soundscapes Zenodo Community. This stage included dataset packaging, metadata standardization, README generation, integrity verification, DOI assignment, and automated repository upload workflows using the Automated Zenodo Upload Software (AZUS). These workflows established the project's long-term open-science infrastructure and ensured that datasets remained findable, accessible, interoperable, reusable, and citable for future scientific and educational use. Related Citations and Resources: Winter, H., & Goncalves, J. (2026). AZUS (Automated Zenodo Upload Software) [Computer software]. GitHub. https://github.com/ARISA-Lab-LLC/AZUS-Automated-Zenodo-Upload-Software Stage 4: Scientific Analysis and Research Use Stage 4 involves the scientific analysis and interpretation of validated eclipse soundscape datasets. Analysis workflows utilized datasets verified during earlier stages to investigate eclipse-related environmental and animal vocalization changes across hundreds of recording sites. This stage also includes broader scientific interpretation, publication development, and continued reuse of Eclipse Soundscapes datasets and infrastructure for future research, education, and open-science applications. Related Citations and Resources: Pease, B., Gilbert, N., & Severino, M. (2026). Eclipse Soundscapes Preliminary Findings – How Eclipses Affect Nature as determined by Sound (Recorded Webinar). Zenodo. https://doi.org/10.5281/zenodo.18613979 Gilbert, N. A., Pease, B. S., Severino, M., & Winter, H. III. (2026). Photic niche explains avian behavioral responses to solar eclipses. Ecology and Evolution, 16(2), e73090. https://doi.org/10.1002/ece3.73090 Analysis code repository: https://github.com/BrentPease1/eclipse-traits Companion Zenodo record archiving structured analysis scripts and derived outputs: https://doi.org/10.5281/zenodo.15790879[r] Public Archiving, Privacy, and Data Transparency The Eclipse Soundscapes Data Collector Role Training and Implementation Manual (2023-2024) includes a detailed explanation of how Eclipse Soundscapes audio data are publicly archived on Zenodo, how participant privacy is protected through the ES ID system, and how transparency and traceability are maintained. It also outlines the criteria for determining which recordings are included in the public archive, as well as the distinction between publicly shared archival data and datasets used for ES-led scientific analyses. Participants and data users can consult this section for full documentation of the project's open science and privacy practices. Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Collector Role Training and Implementation Manual (2023–2024). Zenodo. https://doi.org/10.5281/zenodo.18623443 Citations Individual Site Citation: APA Citation (7th edition) Winter, H., Severino, M., & Volunteer Scientist. (2026). 2024 solar eclipse soundscapes audio data [Audio dataset, ES ID# 294]. Zenodo.{Insert DOI} Collected by volunteer scientists as part of the Eclipse Soundscapes Project. This project is supported by NASA award No. 80NSSC21M0008. Eclipse Community Citation Winter, H., Severino, M., & Volunteer Scientists. 2023 and 2024 solar eclipse soundscapes audio data [Collection of audio datasets]. Eclipse Soundscapes Community, Zenodo. https://zenodo.org/communities/eclipsesoundscapes/ Collected by volunteer scientists as part of the Eclipse Soundscapes Project This project is supported by NASA award No. 80NSSC21M0008.
Zhang, Song · Wang, Xiaoyu · Zhang, Jiayi · et al.
17 files · 1.4 MB · csv, xlsx, zip
This dataset contains raw and processed data underlying the study on Vibrio-phage interactions, including genome sequences, CRISPR arrays, spacer-protospacer mappings, defense system annotations, phylogenetic analyses, and structural modeling outputs. It also includes scripts used for analysis and figure generation. All raw sequencing reads are deposited in NCBI SRA and genome accession numbers are provided in Supplementary files.
DFT calculations for KV3Sb5 kagome metal including relaxation, self-consistent, Wannier and bands calculations for the primitive unit cell. Representative calculation for 2x2 and 2x2x2 supercell to obtain the total energies contours. The calculations were done on the GCS Supercomputer SuperMUC-NG at Leibniz Supercomputing Centre (www.lrz.de).
Der Datensatz "Daten der Notaufnahmesurveillance" wird durch das Robert Koch-Institut und das AKTIN-Notaufnahmeregister bei Krankenhausaufnahmen bereitgestellt. Der Datensatz beinhaltet aggregierte Routinedaten aus deutschen Notaufnahmen zur syndromischen Überwachung von akuten Erkrankungen. Dazu zählen grippeähnliche Erkrankungen (ILI), Coronavirus-Erkrankungen (COVID-19), akute respiratorische Erkrankungen (ARE), gastrointestinale Infektionen (GI) und schwere akute respiratorische Infektionen (SARI). Dabei wird der relative Anteil dieser Erkrankungen an der Gesamtzahl der Notaufnahmevorstellungen sowie die berechneten Erwartungswerte und Prädiktionsintervalle ausgewiesen. Die Daten sind nach Notaufnahmetypen und Altersgruppen aggregiert. Damit bietet der Datensatz eine wertvolle Ressource für die Forschung im Bereich der Notfallmedizin und der Überwachung akuter Gesundheitsereignisse in Deutschland.
A multi-arena corpus of the discourse of Germany's Alternative für Deutschland (AfD), assembled for corpus-assisted critical discourse analysis. It documents the AfD across four communicative arenas - federal election manifestos (2013-2025), the 2016 founding programme, state (Landtag) manifestos (2024), flagship rally speeches, and Bundestag plenary speeches (2017-2026, 7,810 speeches) - together with a comparative reference set of all major parties' manifestos (2013-2025). Owing to copyright, only the public-domain parliamentary-speech layer (derived from the CPP-BT corpus, CC0) is included in full; all other materials are documented with full provenance and a reconstruction recipe in README.md and MANIFEST.csv, so that the complete corpus can be reproduced from its original sources (Manifesto Project, afd.de, CPP-BT). See README.md for structure and licensing and CODEBOOK.md for variable documentation.
This dataset accompanies the publication 'Phase coherence and disorder-induced wave propagation in micromotor arrays'. It contains the data used to produce the figures reported in the article.