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hybrid · semantic + lexical · 4899 datasets ranked · 3.55s

Structuremodal8composite5tabular4tensor1
Depthcataloged4881measured18
Licenseopen4622non commercial146unknown93share alike38
Accessopen4899
Formatpdf4829zip150csv78docx61tsv44
Sourcezenodo4899
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1-20 of 4899sortrelevancemeasured firstqualitysize
modal

Morphosyntactic and Pragmatic Constructions in Jiepai Speech (Danyang, Jiangsu, China): An Emic Grammar Note

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xlsx44
png26
jpeg23
tar17
fits15
hdf515
shapefile11
parquet9
gzip8
tiff8
bzip25
torch4
geojson3
geopackage3
netcdf3
rar2
fasta1
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sqlite1
wav1
xls1
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The Jiepai Archivist

3 files · 338 KB · pdf

Abstract This open-access release provides an emic grammar note on selected morphosyntactic and pragmatic constructions in Jiepai speech, a local Sinitic speech variety from the Wu-Jianghuai contact zone in Jiepai, Danyang, Jiangsu, China. The file is prepared as a grammar appendix to the Jiepai Jianghu section of the Chuanyue archive, an emic vernacular multimodal archive created by a native insider. The note documents selected structures in grammar, syntax, aspect, disposal, passive-related expression, locative marking, shared-use constructions, degree expression, and pragmatic usage. It includes notes on ge marking; completion-question and negative-completion forms such as geng and beng; aspectual distinctions related to Mandarin le and zhe; na disposal constructions; ha / bo constructions across passive, giving, and marriage-related contexts; locative suffixes; go shared-use constructions; yanlian parallel-action structures; degree adverbs and ironic intensification; and locative lai2 / A patterns. The document is based on the Archive Author's native-speaker knowledge and ongoing documentation of Jiepai speech. It does not present a complete grammar, final character standardization, final IPA transcription, phonetic analysis, or ELAN alignment. Phonetic, tonal, and character-form notes marked as provisional or pending verification are retained as research openings rather than resolved conclusions. Authorship and deposit roles are separate. The Archive Author, The Jiepai Archivist, is the creator, archive owner, rights holder, and public contact person. The uploader provides curatorial and deposit assistance only and is not the author, creator, archive owner, rights holder, or public contact for this archive.

open·CC-BY-NC-ND-4.0·Zenodo·completeSource
modal

Structured to Fail: Gender Bias in Large Language Models Across Text and Visual Modalities Through Data Feminism and Intersectionality in the Indian Context

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Poonia, NIkita · Saraswat, Dr. Niraja · Poonia, Dr. Arun Kumar

7 files · 107 KB · pdf

This repository contains the dataset associated with the study " Structured to Fail: Gender Bias in Large Language Models Across Text and Visual Modalities Through Data Feminism and Intersectionality in the Indian Context". The deposit includes a representative subset of the full study data, comprising the following components: Sample Design: Documentation of the sampling framework and run structure across the three LLM platforms examined Prompt Battery: The complete set of prompts administered across text and image generation tasks Model-Generated Text Outputs: Textual responses generated (1,020) by the models under the study Model-Generated Image Outputs: Visual outputs generated (480) in response through image-generation prompts Codebook: Provides complete instructions for all independent coders participating in the inter-rater reliability (IRR) study Inter-rater Reliability Dataset: The double-coded subset used to establish coding agreement Reported Reliability Scores: Cohen's Kappa values and percentage agreement statistics as reported in the manuscript

open·CC-BY-4.0·Zenodo·completeSource
modal

Intensivkapazitäten und COVID-19-Intensivbettenbelegung in Deutschland

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Robert Koch-Institut

9 files · 197 KB · csv, pdf, zip

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.

open·CC-BY-4.0·Zenodo·completeSource
tabular

Pharmacokinetics of brain-penetrant, orally bioavailable ALK2 inhibitor

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Al-awar, Rima · Aman, Ahmed · Briggs, Mike · et al.

999 rows × 26 cols · 8.8 MB · pdf, xlsx

26 categorical

Diffuse Intrinsic Pontine Glioma (DIPG) is a rare and aggressive pediatric cancer located in the pons region of the brainstem, classified as a broader class of H3 K27M mutant Diffuse Midline Gliomas (DMG). Traditional drug development models struggle to address rare diseases like DIPG due to small patient populations and high risks. M4K Pharma focuses on developing an ALK2 enzyme inhibitor, the first therapeutic designed specifically for DIPG. We are leveraging highly potent, selective, and drug-like molecules targeting this protein to create a promising therapeutic option for children affected by this devastating disease. The following entries include the PK and DMPK evaluation of ALK2 inhibitor compounds, including M4K2009, M4K2281, and M4K2308, across a series of in vivo mouse studies. The datasets include oral (PO) and intraperitoneal (IP) exposure analyses, dose-escalation studies, formulation comparisons, BBB penetration assessments, tissue distribution measurements, and study protocols outlining dosing regimens, sample collection procedures, and bioanalytical methodologies. In addition, the studies characterize the metabolic conversion of M4K2281 to M4K2308 through N-demethylation and compare the brain exposure profiles of multiple ALK2 inhibitor candidates. Together, this data provides an integrated assessment of systemic exposure, tissue distribution, metabolic stability, and central nervous system penetration to support the selection and optimization of brain-penetrant ALK2 inhibitors for DIPG. The accompanying files also include key pharmacokinetic parameters, including Cmax, area under the curve (AUC), half-life (T½), mean residence time (MRT), dose proportionality analyses, and brain-to-plasma ratio measurements that inform compound progression into IND-enabling development. Table of key terms and definitions of the project. Key Term Definition Pharmacokinetics (PK) The study of how a drug is absorbed, distributed, metabolized, and eliminated over time within the body. Drug Metabolism and Pharmacokinetics (DMPK) The evaluation of a compound's absorption, distribution, metabolism, excretion, and overall exposure to support drug development. Blood-Brain Barrier (BBB) A highly selective barrier that regulates the movement of substances from the bloodstream into the brain and limits drug delivery to CNS tumors. Oral (PO) Administration Delivery of a drug by mouth to achieve systemic absorption and exposure. Intraperitoneal (IP) Administration Administration of a drug into the peritoneal cavity to achieve systemic exposure in animal studies. M4K2009 Lead orally bioavailable ALK2 inhibitor selected for development due to its favourable exposure and brain penetration properties. M4K2281 ALK2 inhibitor precursor compound that undergoes metabolic N-demethylation to form M4K2308. M4K2308 Brain-penetrant ALK2 inhibitor metabolite that demonstrates improved CNS exposure and favourable brain-to-plasma ratios. N-demethylation A metabolic process that removes a methyl group from a molecule, converting M4K2281 into M4K2308. Brain-to-Plasma Ratio A metric used to quantify CNS penetration by comparing drug concentrations in brain tissue relative to plasma concentrations. Dose Proportionality The relationship between dose and systemic exposure, where exposure increases proportionally as dose increases. Tissue Distribution The extent to which a compound is distributed into specific tissues, including brain and skeletal muscle. LC-MS/MS Liquid chromatography-tandem mass spectrometry; an analytical technique used to quantify drug concentrations in biological samples.

open·CC-BY-4.0·Zenodo·100% null·completeSource
tabular

Daten der Notaufnahmesurveillance

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Robert Koch-Institut · AKTIN-Notaufnahmeregister

86 rows × 8 cols · 10 KB · pdf, tsv, zip

4 numeric · 3 categorical · 1 text

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.

open·CC-BY-4.0·Zenodo·0% null·completeSource
modal

Open-Access Digital Humanities Research (2016-2026)

0.00

Suwarno · Akun, Andreas

2 files · 295 KB · pdf, xlsx

File ini merupakan data mentah ( raw data ) ekspor dari database Scopus yang digunakan untuk melakukan pemetaan, analisis bibliometrik, atau Tinjauan Literatur Sistematis (SLR) mengenai tren riset di bidang Digital Humanities.

open·CC-BY-4.0·Zenodo·completeSource
tabular

2024-04-08 Partial Solar Eclipse ESID#204

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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.

open·CC-BY-4.0·Zenodo·60% null·completeSource
composite

2024-04-08 Total Solar Eclipse ESID#294

0.00

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.

open·CC-BY-4.0·Zenodo·completeSource
composite

Daten der Notaufnahmesurveillance

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Robert Koch-Institut · AKTIN-Notaufnahmeregister

5 files · 10 KB · pdf, tsv, zip

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.

open·CC-BY-4.0·Zenodo·completeSource
modal

Penig Löwen-Apotheke (1924 / 1948)

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Wolf, Gerhard · Kolbe, Georg

2 files · 14 MB · pdf, tiff

Historical questionnaire/s 1924/1948 and index cards, partly selected enclosures regarding the history of a German pharmacy, catalogued via Kalliope portal (Historischer Fragebogen 1924/1948 und Karteikarten, ggf. gemeinfreie Anlagen zur Apothekengeschichte; als Katalog dient das Nachlassportal Kalliope): https://kalliope-verbund.info/DE-611-BF-70963 [Funktion: Im Findbuch anzeigen] Please note: The Kalliope catalogue entry might indicate related material in the archival folder which cannot be published due to copyright or other legal restrictions (NB: Das Katalogisat bei Kalliope kann auch auf Materialien - teils erheblichen Umfangs - verweisen, die aus archiv- oder urheberrechtlichen Gründen nicht veröffentlicht werden dürfen).

open·CC-BY-4.0·Zenodo·completeSource
modal

Data for "Reconstructing Europa's atmosphere from H2+ pickup ions detected during the Juno PJ45 flyby"

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Carberry Mogan, Shane

1 files · 17 MB · pdf

This archive contains all data products and Python scripts required to reproduce the figures presented in: Carberry Mogan et al. (2026): "Reconstructing Europa's atmosphere from H2+ pickup ions detected during the Juno PJ45 flyby".

open·CC-BY-4.0·Zenodo·completeSource
modal

"ATHLETIC PERFORMANCE ANALYTICS IN COMBAT SPORTS: CAN DATA-DRIVEN METHODS TRANSFORM HOW FIGHTERS TRAIN AND COMPETE?"

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Rakhimxon Bakhodirxonov

1 files · 595 KB · pdf

open·CC-BY-4.0·Zenodo·completeSource
modal

Dataset For "AUDIT TRANSPARANSI INFORMED CONSENT: ANALISIS KEPATUHAN KEBIJAKAN PRIVASI PLATFORM LAYANAN STREAMING VIDEO (OVER-THE-TOP) DI INDONESIA TERHADAP UU PDP NOMOR 27 TAHUN 2022"

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Putri Lenggo Genni · Tavasya Alia Anjani · Muhammad Fasha Asshofa

3 files · 2.8 MB · csv, pdf, xlsx

open·CC-BY-4.0·Zenodo·completeSource
tensor

Precomputed Databases for OMAmer

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Altenhoff, Adrian

6 files · 100 MB · hdf5

OMAmer - tree-driven and alignment-free protein assignment to subfamilies OMAmer is an alignment-free protein family assignment method designed to avoid overly specific subfamily predictions and to scale efficiently to phylogenomic databases containing thousands of genomes. It relies on an innovative approach that uses evolutionarily informed k-mers for alignment-free mapping to ancestral protein subfamilies. This dataset provides precomputed OMAmer databases derived from the Hierarchical Orthologous Groups in the OMA Browser . We aim to update these databases with every new OMA Browser release. Each OMAmer database is built using the latest version of the OMAmer package available at the time of the corresponding OMA Browser release. The dataset includes databases for different subsets of the species taxonomy. In most cases, we recommend using the LUCA.h5 database, which contains information from all species in the OMA database. The subset-specific databases are mainly useful when disk space is limited. The release May2026 is based on the OMA Browser release May 2026 which comprises 2983 species. We used OMAmer version 2.1.0 to build these databases.

open·CC-BY-4.0·Zenodo·completeSource
composite

ADM_LSIR: a physics-inspired laparoscopic aerosol degradation dataset

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guo, na · pan, jiachen · li, tiantian · et al.

14 files · 100 MB · csv, rar, tsv

ADM_LSIR is a physics-inspired laparoscopic aerosol degradation dataset for aerosol-aware surgical image analysis and image restoration. The v1.0.0 release contains: - 21,916 clean clinical laparoscopic frames (clean/) - 9,562 real intraoperative aerosol-degraded frames (degraded/) - 36,052 simulated aerosol masks, including 19,701 smoke-like masks and 16,351 trajectory masks (mask/) - Blender simulation/cache materials (ADM_LSIR_Blender_simulation_files_v1.0.rar) - metadata_quality_report_v1.0.csv - recommended_splits_v1.0.csv - video_mapping_v1.0.csv - parts_manifest.txt - checksums_v1.0.tsv - release_manifest_v1.0.json All released clinical frames are de-identified and stored as lossless PNG files. Filenames use anonymized video identifiers, e.g., C-V##-####.png for clean frames and D-V##-####.png for degraded frames. The recommended split is defined at the source_video_id/public_video_label level to reduce leakage across frames from the same source video. The public video labels in video_mapping_v1.0.csv provide privacy-safe source-video identifiers (video1-video19). The Blender archive documents the smoke and trajectory mask simulation setup and supports reuse, but it is not a guaranteed exact per-mask reproduction package. The released pre-rendered mask library is the primary reusable dataset component. Source code for synthesis and quality screening is available at: https://github.com/SweetDeathh/ADM_LSIR

open·CC-BY-4.0·Zenodo·completeSource
composite

2024-04-08 Total Solar Eclipse ESID#292

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Winter, Henry · Severino, MaryKay · Volunteer Scientist

16 files · 100 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: 44.46311 Longitude: -71.68203 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): 18:16:15 Totality Start Time (UTC) (2nd Contact): [N/A if partial eclipse] 19:28:56 Eclipse Maximum Time [when the most possible amount of the Sun in blocked] (UTC): 19:29:25 Totality End Time (UTC) (3rd Contact): [N/A if partial eclipse] 19:29:53 Eclipse End Time (UTC) (4th Contact): [N/A if partial eclipse] 20:38:30 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# 292]. 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.

open·CC-BY-4.0·Zenodo·completeSource
composite

Fast Breakdowns Observed in the Initial Leaders of Two Energetic Compact Strokes

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Yang, Qingliu

6 files · 8.0 MB · bzip2

Dataset Description This dataset contains 3D lightning location results, DALMA and FALMA waveform for two Energetic Compact Stroke (ECS) events. location results are included: HF3D_1732785151.dat - 3D lightning locations for the ECS leader A flash. HF3D_1734785454.dat - 3D lightning locations for the ECS leader B flash. The timestamp 1734785454 and 1732785151 corresponds to the occurrence time of the lightning flash in Japan Standard Time. File format and parameters The first row contains the lightning occurrence time. Column descriptions: Time (ms) - time relative to the lightning source. X, Y, Z (m) - 3D spatial coordinates relative to ground level. The origin (0, 0, 0) corresponds to latitude 36.76°N and longitude 136.76°E. FALMA and DALMA waveform ECSLeaderA_DALMA_waveform.bz2 is DALMA waveform of Leader A. ECSLeaderA_FALMA_waveform.bz2 is FALMA waveform of Leader A. ECSLeaderB_DALMA_waveform.bz2 is DALMA waveform of Leader B. ECSLeaderB_FALMA_waveform.bz2 is FALMA waveform of Leader B. This dataset allows analysis of the spatial and temporal development of these two ECS flashes.

open·CC-BY-4.0·Zenodo·completeSource
tabular

Generated ASO features for the OligoAI dataset

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Kovaliov, Michael

1 files · 100 MB · parquet

open·CC-BY-4.0·Zenodo·completeSource
declared

Source data for: Overexpression of SlMPBQMT (VTE3) enhances α-tocopherol accumulation and reduces oxidative stress in tomato

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Kim, Ah Young · Kim, Jin Su · Ko, Jung Yun · et al.

3 files · 307 KB · pdf, xlsxdeclared

This dataset contains the source data associated with the manuscript entitled "Overexpression of SlMPBQMT (VTE3) enhances α-tocopherol accumulation and reduces oxidative stress in tomato." The uploaded files include the original experimental data used to generate the figures and analyses presented in the manuscript, including: HPLC quantification of α-tocopherol. Plant phenotype measurements. qRT-PCR expression data. DAB and NBT staining quantification data. These data are provided to ensure transparency, reproducibility, and compliance with the data availability policy of BMC Plant Biology .

open·CC-BY-4.0·Zenodo·completeSource
declared

When an Asset Does Not Pay for Itself

0.00

Bell, Peter

2 files · 14 MB · pdf, zipdeclared

This working paper asks how Canada should assess strategic resource infrastructure that may not earn a commercial return on its own. A road, port, power system, pipeline, smelter, or processing plant can appear uneconomic when evaluated as an individual asset while still enabling new production, preserving difficult-to-replace processing capacity, supporting several users, or improving security of supply. The paper develops a framework for deciding when public support for such an asset may be justified. Its central rule is that an asset-level loss is defensible only when it produces wider benefits that are specific, measurable, and subject to effective public oversight. The analysis draws on Canadian wartime industrial mobilization, concentration in critical-mineral supply chains, proposed support for processing capacity at Trail, current infrastructure and northern development programs, and cautionary cases involving mining subsidies, managed decline, remote transport, and major-project governance. The paper converts the argument into a twelve-question approval test and a measurement framework for tracking public cost, avoided closure, new production, secure supply, shared infrastructure use, and signs of failure. It does not recommend a particular project and does not argue that all loss-making assets deserve public support. Its purpose is to distinguish infrastructure that creates durable public value from subsidy, bailout, or white-elephant risk.

open·CC-BY-4.0·Zenodo·completeSource
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