Hubbard, Alfred · Solares, Edwin · Hemming-Schroeder, Elizabeth

88 rows · 18 KB · fasta

These are the files needed to run the Broad Institute's malaria amplicon pipeline for the PvGAP Plasmodium vivax panel, described in detail here . They consist of FASTA files containing the forward and reverse primers and another FASTA file containing reference sequences for each target, derived from the PvP01 reference genome.

Yuan, Guangyuan

72 rows × 13 cols · 6.0 KB · csv, fasta

11 numeric · 2 categorical

This dataset supports the findings of the manuscript "Root anatomical traits modulate the assembly and nitrogen transformation potential of root-associated microbiomes in a temperate steppe" (NPH-MS-2026-55667). It contains root traits data, bacterial 16S rRNA gene absolute abundances, functional genes relative abundances, DNA extraction metadata, and phylogenetic marker sequences for 37 plant species from a temperate steppe ecosystem. The dataset includes the following files: 1. root traits.csv - Root traits including average diameter (AD), specific root length (SRL), specific root area (SRA), root tissue density (RTD), root nitrogen content (RNC), root carbon content (RCC), carbon‑nitrogen ratio (RCN), cortex layer number (CLN), cortex thickness (CT), and the ratio of cortex thickness to root diameter (CTRD). The first column lists plant species names. 2. Absolute abundance of 16S rRNA gene.csv - Quantitative PCR (qPCR) derived absolute abundances of bacterial 16S rRNA gene copies (copies/ng DNA) across different root compartments (rhizosphere, rhizoplane, endosphere), host species, root orders, and cotyledon classes (monocot/dicot). 3. DNA extraction sample weight.csv - Fresh weight (grams) of root material used for DNA extraction for each sample, linked by SampleID to the abundance data. 4. DNA extraction concentration.csv - Qubit‑measured DNA concentrations (ng/μL) and the sample volume (μL) used for quality control, together with sample metadata. 5. 37species.fasta - DNA sequences of two chloroplast markers (matK and rbcL) for the 37 plant species included in the study. The sequences are in FASTA format with headers formatted as ">Species". These were used for host phylogeny construction and Pagel's λ analyses. 6. Quantitative PCR results of functional gene.csv - Quantitative PCR (qPCR) derived relative abundances of bacterial 16S rRNA gene and functional genes across different root compartments (rhizosphere, rhizoplane, endosphere), host species, root orders, and cotyledon classes (monocot/dicot). 7. README.md - A detailed description of each file, column headers, abbreviations, units, and any missing value codings (NA). All data are provided to ensure transparency and reproducibility of the analyses. For methodological details, please refer to the Materials and Methods section of the associated publication. These data are under embargo until the associated research article is published. After that date, they will be freely available under a Creative Commons Attribution 4.0 International (CC BY 4.0) license. During the embargo period, the metadata (title, authors, abstract) and the DOI remain publicly visible, but the data files are not accessible. For access requests before the embargo expires, please contact the corresponding author.

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.

Requena Rolanía, Jose María · Greif, Gonzalo · ROBELLO, CARLOS

1 files · 8.0 MB · fasta

This dataset contains the genome sequence for Trypanosoma cruzi (strain Dm28c). This genome sequence was de novo assembled using PacBio Hi-Fi and Illumina sequencing platforms by Greif et al (2026. PMID: 41501640). The genome was assembled into 32 contigs, which represent complete chromosomes. The provided Fasta file also contains an additional contig corresponding to the maxicircle (mitochondrial genome) sequence. The Fasta files included in this dataset were downloaded from GenBank (assembly GCA_044048535.1; May 22, 2026). Additional information about the Dm28cT2T genome assembly and gene annotations may be accessed through the link: https://cruzi.pasteur.uy/

Burman, Nathaniel · Buyukyoruk, Murat · Wiegand, Tanner · et al.

4 files · 8.0 MB · fasta

This folder contains a multiple sequence alignment of Cas7 homologs in .fasta format, the domain-level annotations from PFAM and CasFinder, and an associated phylogenetic tree in .newick format.

Kovaliov, Michael

1 files · 100 MB · parquet

Madhusudan, Gujral

6 files · 29 MB · parquetdeclared

Large language models (LLMs) are trained on massive, publicly available text datasets comprising trillions of tokens, enabling them to excel at general language tasks like next-token prediction. However, LLMs often struggle with domain-specific prompts, exhibiting reduced accuracy or generating inaccurate information (hallucinations). This is because they lack sufficient subject matter expertise. Two primary approaches exist to address this limitation for augmenting LLMs knowledge: Retrieval-Augmented Generation (RAG) and fine-tuning. This presentation focuses on fine-tuning smaller LLMs with domain-specific instruct datasets using the LoRA (Low-Rank Adaptation) technique on Gaudi hardware. We will leverage publicly available LLMs and datasets from the Hugging Face Hub for this demonstration. Though it is possible to fine tune LLMs with plain text data - sourced from documents, articles, and other materials.

Austin, Timothy · do Valle Chagas Azaneu, Marina · Roughan, Moninya

26 files · 29 MB · netcdf, pdf, pngdeclared

Data collected from a temperature mooring at Lord Howe Island maintained by UNSW Sydney and funded by Parks Australia. The mooring position is longitude = 158.97°E and latitude = -31.51°, and local depth of approximately 52 m. The data were sampled using a series of thermistors (aqualogger 520PTs) deployed on a mooring line at 4m intervals through the water column, with shallowest instrument at 13 m and deepest at 53 m. The time period spans between 14-05-2025 and 22-04-2026. IMOS standard data quality assurance and quality control processes have been followed and the data formatted following IMOS conventions. Data quality control includes automated routines and visual inspection (expert QC) and flagging of obvious errors. File are c.f. compliant NetCDF files, and file name format follows IMOS conventions and includes sampling period in the format: UNSW_Lord_Howe_Marine_Park_TZ_ yyyymmddThhmmss Z_LH050_FV01_ LH050-2511-Aqualogger-AQUAlogger-520PT16-max160m-13_END- yyyymmddThhmmssZ.

Wang, Chang · Lu, Xingcheng

2 files · 222 MB · netcdfdeclared

Machine-learning-inferred monthly anthropogenic NOx emission over the 2026 Strait-of-Hormuz disruption (global, 0.1 degree, January 2025 - May 2026). This dataset is the top-down NOx emission product underlying the companion manuscript on the 2026 Strait-of-Hormuz shipping-emission collapse. A LightGBM estimator trained on the CAMS-GLOB-ANT v6.2 inventory (2018-2024), with the observed TROPOMI NO2 column and GEOS-CF chemistry/meteorology as predictors, is applied month by month to 2025-01 through 2026-05 to infer the anthropogenic NOx emission flux. Provided as a single self-describing CF-1.8 NetCDF containing: the total anthropogenic NOx flux (kg m-2 s-1, reported as NO) and a per-pixel cross-validation uncertainty (log-space). The estimator resolves the total emission only; no sector decomposition is distributed, because over open ocean the total is essentially ship emission while on land a sector split would only re-apply the CAMS-GLOB-ANT prior shares and is not constrained by the observations. Coverage is land and ocean within +/-60 degrees latitude on a regular 0.1-degree global grid. All units and coordinates are embedded in the file.

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 ).

Zhang, Yunwei

6 files · 40 GB · hdf5, zipdeclared

Files related to INVNET, a deep learning model for surface wave dispersion spectrum inversion in geophysics.

Miszczyszyn, Jakub · Radoń, Radosław

20 files · 2.1 GB · csv, netcdfdeclared

Monthly 1-km SPI, SPEI and SRI drought-indicator rasters for Poland (1995-2024) This dataset provides monthly gridded drought indicators for the entire territory of Poland at 1-km resolution for the period 1995-2024. Three complementary standardized indices are included: the Standardized Precipitation Index (SPI, precipitation-based), the Standardized Precipitation-Evapotranspiration Index (SPEI, based on the climatic water balance P - PET) and the Standardized Runoff Index (SRI, runoff-based). Each index is provided at five accumulation scales: 1, 3, 6, 12 and 24 months. Methods. Station indices were computed from IMGW-PIB precipitation and river-runoff observations and from AgERA5 potential evapotranspiration (used for SPEI). SPI and SRI were fitted with a gamma distribution and SPEI with a log-logistic distribution. Station values were then interpolated to a 1-km grid (EPSG:2180, PUWG 1992) by ordinary kriging. Elevation-assisted kriging (kriging with external drift) was evaluated by leave-one-out cross-validation but produced no net national improvement and was not adopted for the final product. File structure. Data are provided as CF-compliant NetCDF (CF-1.8), one file per indicator and accumulation scale (e.g. SPI_s06m_PL_1km_1995-2024_EPSG2180.nc ) . Each file has dimensions (time, y, x) with a regular monthly time axis (360 steps, 1995-01 to 2024-12) and the coordinate reference system stored as a grid_mapping variable. Months in which an index cannot be formed at the edges of the accumulation window are present as fill-valued (missing) layers, so the time axis is continuous; their completeness is documented in raster_index.csv . Contents. netcdf/ - the 15 index rasters; metadata/raster_index.csv - per-layer inventory with min/max/mean, missing-data fraction and a "present" flag; metadata/variables_dictionary.csv - variable definitions; metadata/mckee_classes.csv - the seven-class drought/wetness classification (McKee et al., 1993) with colours; CITATION.cff and checksums.md5 . Usage note. In GIS software the temporal dimension is read via the temporal/time controls (e.g. in QGIS: Layer Properties → Temporal → Dynamic Temporal Control, then the Temporal Controller); in Python the files open directly with xarray, with time parsed as dates. Coordinate reference system. EPSG:2180 (PUWG 1992 / Poland CS92). Map extents delineate the study area and do not necessarily depict accepted national boundaries.

Wyatt, James · Larsen, Karin Margretha H.

2 files · 21 MB · netcdfdeclared

A monthly dataset of volume, heat and salt transport through the Faroe-Shetland Channel. The time step is monthly, from 1993-01 to 2025-08. This data accompanies the paper 'Strengthening of the Atlantic Water Inflow through the Faroe-Shetland Channel'.

Tiskus, Edvinas · Tiškuvienė, Rūta · Bučas, Martynas · et al.

37 files · 1.6 GB · hdf5, tiff, torchdeclared

This record contains the labeled data, trained models, and analysis code supporting the article "Comparing a Vision Foundation Model (DINOv3) and a Task-Specific U-Net for Mapping Emergent Aquatic Vegetation from Fused UAV Multispectral and LiDAR Data" (Remote Sensing in Ecology and Conservation). Contents: - masks/ : georeferenced ground-truth segmentation masks (five classes: aquatic vegetation, water, sand, other objects, background), aligned to the fused UAV orthomosaics and spanning 13 sites across nine Lithuanian waterbodies surveyed between May and August 2024. - models/ : the two final trained segmentation models, a Keras/HDF5 U-Net and a PyTorch DINOv3 model. - code/ : Python scripts for training, evaluation, the label-efficiency experiment, and full-scene prediction. The fused 9-band orthomosaics (five-band multispectral, RGB, and a LiDAR canopy height model; approximately 62 GB) are archived separately because of their size and are available from the corresponding author on request. The DINOv3 SAT-493M pretrained backbone is distributed by Meta under its own license and is not redistributed here; obtain it from the official DINOv3 release.

Vines, Jose I.

1 files · 3.0 GB · hdf5declared

Pre-computed, resolution-broadened (R=1500) stellar atmosphere spectra cache for the astroARIADNE SED fitting package. Contains 7 model grids (Phoenix v2, BT-Settl, BT-NextGen, BT-Cond, Castelli & Kurucz 2004, Kurucz 1993, Coelho 2014) resampled to a common logarithmic wavelength grid (0.125-4.629 µm). This cache eliminates the need to download the full ~770 GB model libraries for SED plotting.

Chen, Xiao · Huang, Yibin

2 files · 237 MB · netcdfdeclared

This archive contains a global monthly marine net primary productivity (NPP) product derived from the Data-based Productivity Model (DbPM), an observationally constrained machine-learning framework developed using an expanded global compilation of in situ 14 C/ 13 C-based NPP measurements and satellite-derived environmental predictors. Original DbPM NPP product - generated directly from satellite observations and therefore containing gaps associated with missing satellite data coverage. Gap-filled DbPM NPP product - reconstructed using Empirical Orthogonal Function (EOF)-based interpolation to fill missing values caused by satellite data gaps, providing a spatially complete global monthly NPP field. Chen, X., Huang, Y., Liu, H., Cassar, N., Liu, X., Wang, W., Chai, F., Kang, J., & Huang, B. (2026). Reduced estimate of global marine primary productivity and hemispheric redistribution over the satellite era revealed by an expanded global observational database. Submitted to Communications Earth & Environment .

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.

Lopez Dubon, Sergio · Sgarabotto, Alessandro · Lanzoni, Stefano

11 files · 38 MB · hdf5, npydeclared

This record contains the trained autoencoder, extracted encoder, and processed world/real-river latent-space reference cloud associated with the manuscript *A data-driven approach to discern the curvature spectral complexity of compound meander bends*. The full autoencoder is provided to support reconstruction-based validation and reproducibility of the learned representation. The extracted encoder is provided for inference and future software tools. It maps preprocessed 64 × 64 single-channel curvature-spectrum images to the two-dimensional latent space used to analyse meander shape complexity and skewness. The file `world_latent_cloud.npy` contains the two-dimensional latent coordinates of the world/real-river meander dataset used as the reference background cloud in the manuscript latent-space figures. This file is a processed latent-coordinate dataset only; it does not contain raw satellite imagery, raw centreline geometries, or training images. The release includes model weights, architecture files, model summaries, export metadata, the world/real-river latent cloud, example inference scripts, a validation script, environment files, and a minimal example input. The models should only be applied to curvature-spectrum images generated consistently with the preprocessing workflow described in the associated manuscript. Main files included in this release are: - trained_autoencoder.h5: full trained autoencoder. - encoder_only.h5: extracted encoder in HDF5/Keras format. - encoder_only.keras: extracted encoder in native Keras format. - model_architecture.json: full autoencoder architecture. - encoder_architecture.json: encoder architecture. - model_summary.tx and encoder_summary.txt: layer summaries. - world_latent_cloud.npy: world/real-river reference latent-space cloud. - world_latent_cloud_metadata.json: metadata for the world/real-river latent-space cloud. - model_card.md: intended use, inputs, outputs, limitations, and citation guidance.

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).