Hackl, Jürgen

6 files · 132 MB · parquet, tiffdeclared

EuroFlood is an open, cloud-native index over the JRC/Copernicus CEMS-EFAS Satellite-Derived Flood Depth Maps for Europe (Betterle & Salamon, 2025; CC-BY-4.0) - ~3,280 satellite-derived observed flood-depth maps across Europe, 2015-2024. The bundle is a sparse Cloud-Optimized GeoTIFF encoding, per pixel, the set of flood events that inundated it, plus a combo_id -sorted GeoParquet dictionary and a small events table. Query by region and time via HTTP range reads (GDAL /vsicurl + DuckDB) to retrieve matching events, then fetch only the source depth rasters needed. Built with the open-source EuroFlood Python package ( pip install euroflood ).

Walsh, Calum · Srinivas, Meghana · Stinear, Timothy · et al.

100 files · 2.7 GB · gzip, tsvdeclared

GROND (Genome-derived Ribosomal OperoN Database) A quality-checked and publicly-available database of 16S-ITS-23S RRNA operon sequences and their constituent 16S and 23S genes. Based on GTDB release R232.

Geisler, Jan · Rakhimberdiev, Eldar · Boom, Michiel P. · et al.

29 files · 124 MB · csv, shapefiledeclared

1. Many migratory birds now reach their Arctic breeding grounds earlier in order to keep pace with advancing springs and shifting nutrient peaks, either by departing earlier from non-breeding grounds or by travelling faster. For dark-bellied brent geese, there is limited potential to travel faster, as their migration to the Siberian breeding grounds is already among the fastest of Arctic geese and swans. Earlier departure would require reaching departure body mass earlier, either through a faster accumulation of energy stores during spring staging or via adjustments earlier in the annual cycle. 2. We examined long-term shifts in spring staging phenology and changes in winter and spring body mass trajectories of brent geese at the population level, with particular emphasis on the effects of winter temperature on body mass and spring body mass on departure timing. 3. We used more than five decades of body mass measurements from individuals caught in the United Kingdom and France, and in the Dutch Wadden Sea to reconstruct changes in spring and winter mass trajectories, respectively. These data were combined with over five decades of migration counts in the Netherlands and more than two decades of counts in Denmark to quantify changes in spring staging phenology. 4. We found that brent geese have not shifted their spring arrival in the Wadden Sea but have advanced departure timing. Furthermore, brent geese were heavier during and after milder winters, and have changed mass trajectories over recent decades. They no longer lose mass during winter and the second spring staging phase, and fuelling rates in the first spring staging phase have declined. Annual variation in body mass was not related to annual departure timing. 5. These results suggest that milder winters have relaxed energetic constraints and improved body condition in brent geese throughout the non-breeding season. Our findings highlight the importance of considering the full annual cycle when assessing how animals with limited capacity to adjust migration timing or speed respond to global change.

Robert Koch-Institut · AKTIN-Notaufnahmeregister

5 files · 24 MB · pdf, tsv, zipdeclared

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.

Filippova, Nina · Bulyonkova, Tatiana · Zvyagina, Elena · et al.

1 files · 1.4 MB · tsvdeclared

Best hit results with analytical parameters

Tolksdorf, Kristin · Goerlitz, Luise · Staat, Doreen · et al.

4 files · 309 KB · pdf, tsv, zipdeclared

Im Datensatz "SARI-Hospitalisierungsinzidenz" des Robert Koch-Instituts werden die wöchentlichen Inzidenzen schwerer akuter respiratorischer Infektionen (SARI) auf Bundesebene in Deutschland bereitgestellt. Die Daten stammen aus der syndromischen Krankenhaussurveillance ICOSARI, die auf ICD-10-Diagnosecodes aus etwa 70 Sentinelkliniken basiert. Der Datensatz umfasst Hospitalisierungsinzidenzen pro 100.000 Einwohner, aufgeschlüsselt nach Altersgruppen, Saison und Kalenderwoche. Neben der Gesamtheit aller SARI-Fälle werden auch Fälle mit zusätzlicher COVID-19-, Influenza- oder RSV-Diagnose separat erfasst. Die Surveillance liefert entscheidende Informationen zur Krankheitslast akuter respiratorischer Erkrankungen und dient als Grundlage für epidemiologische Bewertungen und Empfehlungen für gesundheitspolitische Maßnahmen.

Buchholz, Udo · Lehfeld, Ann-Sophie · Loenenbach, Anna · et al.

5 files · 953 KB · pdf, tsv, zipdeclared

Im Datensatz "GrippeWeb - Daten des Wochenberichts" des Robert Koch-Instituts werden wöchentliche, bevölkerungsbasierte Schätzungen zur Inzidenz akuter respiratorischer Erkrankungen (ARE) und grippeähnlicher Erkrankungen (ILI) in Deutschland bereitgestellt. GrippeWeb als Online-Portal zur partizipativen syndromischen Surveillance nutzt Selbstauskünfte freiwilliger, pseudonym registrierter Teilnehmender ab 16 Jahren zu Symptomen wie Husten, Fieber und Halsschmerzen. Daraus werden Inzidenzen nach Altersgruppen und Regionen errechnet. Die erhobenen Daten unterstützen die Überwachung saisonaler Infektionen und dienen der Risikobewertung in Pandemien wie COVID-19.

Goerlitz, Luise · Tolksdorf, Kristin · Prahm, Kerstin · et al.

4 files · 1.0 MB · pdf, tsv, zipdeclared

Im Datensatz "ARE-Konsultationsinzidenz" des Robert Koch-Instituts werden wöchentliche Inzidenzen von ambulanten Konsultationen mit akuter respiratorischer Erkrankung (ARE) in Deutschland bereitgestellt. Die Daten stammen vom ARE-Praxis-Sentinel des RKI. Hier werden aus Sentinelpraxen Daten von gesetzlich versicherten Patientinnen und Patienten mit einer akuten Atemwegserkrankung entweder einzelfallbasiert anhand von ICD-10-Diagnosecodes mit dem SEED/ARE-Modul oder aggregiert nach Altersgruppen über eine Online-Eingabemaske erfasst. Die ARE-Konsultationsinzidenz wird pro 100.000 Einwohner und nach Altersgruppen und Bundesländern ausgewiesen. Ziel ist es, die Krankheitslast und den saisonalen Verlauf von Atemwegserkrankungen wie Influenza, COVID-19 und RSV-Erkrankungen zu bewerten sowie epidemiologische Entwicklungen frühzeitig zu erkennen

Robert Koch-Institut

5 files · 1.5 MB · pdf, tsv, zipdeclared

Im Datensatz "Respiratorische Synzytialvirusfälle in Deutschland" des Robert Koch-Instituts werden die Daten basierend auf Meldungen zu Infektionen mit dem Respiratorischen Synzytial-Virus (RSV) nach dem Infektionsschutzgesetz (IfSG) bereitgestellt. Darin enthalten sind Informationen auf Bundeslandebene zu Infektionen nach Falldefinition des Robert Koch-Instituts, differenziert nach Altersgruppen. Diese Daten dienen als Grundlage für epidemiologische Bewertungen und gesundheitspolitische Maßnahmen.

Robert Koch-Institut

5 files · 2.1 MB · pdf, tsv, zipdeclared

Im Datensatz "Laborbestätigte Influenzafälle in Deutschland" des Robert Koch-Instituts werden die Daten basierend auf Meldungen zu Infektionen mit dem Influenzavirus nach dem Infektionsschutzgesetz (IfSG) bereitgestellt. Darin enthalten sind Informationen auf Bundeslandebene zu Infektionen nach Falldefinition des Robert Koch-Instituts, differenziert nach Altersgruppen. Diese Daten dienen als Grundlage für epidemiologische Bewertungen und gesundheitspolitische Maßnahmen.

Vanstreels, Ralph E. T. · Serafini, Patricia P. · Giacinti, Jolene · et al.

3 files · 55 KB · tsvdeclared

High pathogenicity avian influenza (HPAI) viruses have rapidly emerged as a major global threat to wildlife, with severe consequences for seabird populations. Albatrosses and petrels (order Procellariiformes) are particularly vulnerable due to their long lifespan, low reproductive rates and strong site fidelity. Since 2021, HPAI viruses have caused unprecedented mortality in seabird communities worldwide and have expanded into the core range of procellariiform species, including sub-Antarctic and Antarctic regions. In response to the urgent need for timely, species-relevant information, the Agreement on the Conservation of Albatrosses and Petrels (ACAP) established the High Pathogenicity H5Nx Avian Influenza Intersessional Correspondence Group (HPAI-ICG), which developed the ACAP HPAI database - an openly accessible, regularly updated resource that consolidates all known suspected and confirmed HPAI events involving procellariiform birds. The database compiles information from global and national reporting systems, scientific literature, genetic repositories, government communications and direct expert notifications. Events are standardised using transparent case definitions, cross-referenced and validated by subject-matter experts and complemented by additional data on case impacts and viral characteristics. The database provides a critical decision-support tool for governments, researchers, conservation practitioners and tourism operators, contributing to the planning and implementation of HPAI biosafety, surveillance, monitoring and outbreak response activities.

Radisky, Derek · Cruz-Reyes, Nicole

4 files · 12 MB · tsv, xlsxdeclared

This record contains the processed proteomics data, sample metadata, and differential-abundance results for the BRCA Prevention Tissue Cohort (sub-study 1), a study of the baseline breast-tissue proteome in women carrying germline BRCA1/2 mutations. Histologically normal breast tissue from non-carrier controls, cancer-free BRCA1/2 carriers, and BRCA1/2 carriers with a prior cancer history was profiled by global mass- spectrometry proteomics (DIA-NN). The record includes: (1) the DIA-NN protein-level abundance matrix (8,684 proteins x 72 samples); (2) de-identified per-sample clinical and sample-source metadata; and (3) differential protein-abundance results across six model specifications and three biological-group contrasts. Dataset prepared by D. C. Radisky and N. Cruz-Reyes on behalf of the study authors; the full author list appears in the associated publication. See README.txt for file-level details.

Robert Koch-Institut

8 files · 223 MB · pdf, tsv, xzdeclared

Im Datensatz "SARS-CoV-2-Sequenzdaten aus Deutschland" umfasst vollständige Virusgenomsequenzen sowie zugehörige Metadaten aus bundesweit erhobenen Proben. Die Proben werden in Zusammenarbeit vom IMSSC2-Labornetzwerk, dem Nationalen Referenzzentrum für Coronaviren an der Charité sowie dem RKI sequenziert und bioinformatisch analysiert. Der Datensatz ermöglicht eine fundierte molekular-epidemiologische Analyse der SARS-CoV-2-Ausbreitung in Deutschland und stellt eine zentrale Ressource für Forschung und öffentliche Gesundheitsüberwachung dar.

Kavanagh, Jack · Anthony, Patrick

6 files · 11 MB · geojson, geopackage, shapefiledeclared

A historical map showing a segment of the boundaries of New Spain in c. 1800. This map is fully open to fellow researchers and is available in multiple open source formats (SHP, GPKG, GeoJSON).

Robert Koch-Institut · Umweltbundesamt

7 files · 50 MB · pdf, tsv, zipdeclared

Im Datensatz "Abwassersurveillance AMELAG" des Robert Koch-Instituts und Umweltbundesamts werden Daten aus der Überwachung von Infektionserregern im Abwasser bereitgestellt. Die Daten zur SARS-CoV-2-Viruslast werden seit Februar 2022 in einem bundesweiten Netzwerk von Kläranlagen, Laboren und Behörden erhoben. Seitdem wurden die Daten um die Viruslast weiterer respiratorischer Viren (Influenza A/B, RSV) ergänzt. Der Datensatz enthält neben Einzelwerten der Kläranlagen auch bevölkerungsgewichtete, aggregierte Zeitreihen. Darüber hinaus werden Auswertungsskripte als Kontextmaterialien bereitgestellt.

Njie, Adama · Torkayesh, Ali E · Venghaus, Prof. Dr. Sandra

10 files · 1.6 GB · csv, gzip, parquetdeclared

Structured, speaker-attributed corpus of all German Bundestag plenary session transcripts ( Plenarprotokolle ) from the first legislative period to the present (WP01-WP21, September 1949 - April 2026). Every attributed speech is extracted from the official PDFs published by the Deutscher Bundestag under open data policy and linked to the speaker's name, parliamentary role, party affiliation, and gender. Scale: 4,611 sessions · 1,033,723 speeches · 4,205 identified MdBs · 76 years of parliamentary debate Dataset files speeches.parquet - one row per attributed speech: speaker name, role, party, gender, stammdaten_id, full German text (~1 GB) persons.parquet - one row per MdB: cross-session identity linking all name variants via stammdaten_id; canonical name, birth date, career span, total speeches. Use this - not speakers.parquet - for person-level analysis sessions.parquet - one row per plenary session: date, city, Wahlperiode, source PDF hash, extraction engine speakers.parquet - name-string index: one row per unique name string as extracted from the transcripts. Useful for understanding extraction quality; not suitable for person-level aggregation (the same politician often appears under several name variants across sessions) parties.csv - reference table of 31 German parliamentary parties, 1949-present speeches.csv.gz - CSV fallback for Stata and Excel users (same columns as speeches.parquet) datapackage.json - Frictionless Data schema with column descriptions and foreign key constraints Cross-session identity The same politician often appears under different name strings across sessions (e.g. "Schmidt", "Dr. Schmidt", "Frau Dr. Schmidt"). Cross-session person linkage is provided via stammdaten_id , matched against the official Bundestag Stammdaten biographical XML. The persons.parquet table aggregates all name variants for the same MdB into one row with correctly summed speech counts, career span, and birth date. Coverage: ~98.5% of speeches are linked to a stammdaten_id; the remaining ~1.5% are ambiguous surname-only attributions or speakers not in the Stammdaten. Coverage and sources Source PDFs are the official Stenografische Berichte downloaded from the Bundestag open-data portal (bundestag.de). Party-share normalisation in the corpus statistics uses official seat counts per Wahlperiode sourced from the Federal Returning Officer (Bundeswahlleiter, bundeswahlleiter.de). Two PDF generations are covered: scanned and OCR'd documents (WP01-WP09, Bonn era, 1949-1987) and born-digital documents (WP10-WP21, 1987-present). The engine column in sessions.parquet flags whether pdftotext (born-digital) or pdfminer (OCR fallback) was used; this is the primary data-quality indicator for NLP use. Speaker attribution Each speech is attributed using four patterns extracted from the transcript format: presiding officers (Präsident/in, Vizepräsident/in), regular members (name + party), government officials (name + Bundeskanzler/in, Bundesminister/in, etc.), and procedural roles (Berichterstatter/in, etc.). The party field is null for ~60% of speeches - this is expected, as presiding officers and ministers are not identified by party in the transcript. Gender annotation & distribution Gender is derived by matching speaker names against the official Bundestag Stammdaten biographical XML (all MdBs since 1949), with fallbacks for role title, honorific prefix, manually researched overrides, and a gender_guesser first-name heuristic. The gender_source column distinguishes stammdaten (authoritative, 83%), role_title (gendered job title in attribution, 6.4%), title_prefix (Frau/Herr honorific, 0.5%), manual (historically researched, 2.9%), and inferred (name-based heuristic, 4.7%). Gender distribution: Female 26.6% · Male 73.4% · Unknown 0.0%. Data quality All speeches pass automated validation: zero null speaker names, zero sequence gaps, zero CID artefacts, zero party-misclassified-as-Bundesland errors. Eight sessions with conflicting source PDFs were deduplicated (first lexicographic occurrence retained). 252 non-person names incorrectly accepted by the parser (table headers, legislative terms, agenda fragments) are excluded at build time via a curated exclusion list. OCR sessions (WP01-WP09) may contain Unicode replacement characters (U+FFFD); the engine field identifies these sessions. Licence CC BY 4.0. The underlying Plenarprotokolle are official government documents of the Deutscher Bundestag and are in the public domain.

abdulwahab, samaa · aduallah, mahmood z. · Sallomi, Adheed H.

34 files · 2.7 GB · csv, gzip, parquetdeclared

Intrusion-detection research on Internet Protocol version 6 (IPv6) remains bottlenecked by the scarcity of labelled, protocol-aware flow datasets. Existing machine-learning IDS benchmarks are overwhelmingly IPv4-centric, and the few IPv6 corpora that have been released target narrow attack families or rely on small academic testbeds that cannot be re-created by third parties. We present IPv6-CyberBench, a reproducible eight-phase pipeline that constructs a large, protocol-aware translated-flow corpus by harmonising CIC-IDS-2017, CIC-IDS-2018 and CIC-DDoS-2019, applying deterministic IPv4→IPv6 address translation (6to4, NAT64, Teredo, EUI-64), synthesising 27 IPv6-specific flow features grouped in six protocol families, enforcing nineteen RFC-derived constraint categories together with temporal address dynamics, and rebalancing the long-tailed class distribution with a feature-group-conditioned per-class Wasserstein-GAN-GP augmenter and a SMOTE-KDE fallback selected per class by a formal decision rule. We scope the contribution honestly: because the seed corpora are IPv4 captures, the resulting 2,285,774-record benchmark is a translated-flow corpus suitable for training and evaluating flow-level IPv6 IDS classifiers on flooding, brute-force, scan, web-attack and infiltration traffic under IPv6 protocol-header semantics, and for studying IPv6-specific feature engineering and address dynamics in a reproducible setting. It is not a substitute for protocol-native IPv6 attack capture, and we explicitly exclude ICMPv6 Neighbour-Discovery flooding, SEND flooding, NDP exhaustion and extension-header covert-tunnelling from the threat model. The benchmark is evaluated on four axes - fidelity (Kolmogorov-Smirnov, MMD, Fréchet feature distance), utility (stratified 5×5 nested cross-validation over six classifier families including CNN-LSTM and LightGBM), privacy (Shokri-style membership-inference advantage AUC), and external fidelity against a 24 h anonymised CAIDA IPv6 trace (equinix-chicago, US backbone) and a MAWI samplepoint-F trace (WIDE backbone, Tokyo, Japan). The full pipeline, the hyper-parameter manifest, the RFC-constraint manifest, the reproduction scripts, and the 2,285,774-record benchmark are released unconditionally on Zenodo under CC BY 4.0; the dataset and pipeline are openly available at https://doi.org/10.5281/zenodo.19503446 (CC BY 4.0).

Kavanagh, Jack · Anthony, Patrick

6 files · 9.3 MB · geojson, geopackage, shapefiledeclared

A historical map of the boundaries of Prussia in c. 1795. This map is fully open to fellow researchers and is available in multiple open source formats (SHP, GPKG, GeoJSON).

Francescone, Marco

14 files · 380 KB · shapefile, zipdeclared

This dataset contains original geomorphic mapping of surface fault traces along the Dixie Valley Fault (DVF) range front and piedmont zone, central Nevada, USA. Traces were mapped directly from a 1-m bare-earth lidar digital elevation model (DEM), using hillshade and slope-raster visualizations. This dataset accompanies the manuscript: Francescone, M., et al. (in review), LiDAR-Based Fault-Scarp Analysis and Rupture Hazard Assessment: Earthquake Scenarios of the Dixie Valley Fault System (Nevada, USA). See Section 3.1 ("Fault Trace Mapping") of the manuscript for full methodological details