Best AI Datasets 2026
The #1 ai datasets in 2026 is csv mit einer Nerq-Vertrauensbewertung von 83/100 (A-), based on Nerq's independent analysis of 50 ai datasets across 5 trust Dimensionen. Tägliche Aktualisierung — zuletzt aktualisiert: 2026-11-06.
Laut Nerq's analysis, the top 5 ai datasets by trust score are: 1. csv (83/100), 2. @wordpress/fields (82/100), 3. @wordpress/dataviews (82/100), 4. datasets (81/100), 5. huggingface-hub (81/100). Nerq Trust Scores range from 67 to 83 among the top 50. Scores are based on 5 independent trust Dimensionen including Sicherheit, Wartung, and Community-Akzeptanz. Täglich aktualisiert.
| # | Name | Vertrauen | Note |
|---|---|---|---|
| 1 | csv | 83 | A- |
| 2 | @wordpress/fields | 82 | A- |
| 3 | @wordpress/dataviews | 82 | A- |
| 4 | datasets | 81 | A- |
| 5 | huggingface-hub | 81 | A- |
| 6 | @sqlrooms/data-table | 76 | B+ |
| 7 | datasketch | 76 | B+ |
| 8 | @humanspeak/svelte-virtual-list | 74 | B |
| 9 | @llm-tools/embedjs | 74 | B |
| 10 | @edgeandnode/amp | 74 | B |
Top 50 AI Datasets nach Nerq-Vertrauenswertung
| # | Name | Vertrauen | Note | Sterne | Beschreibung |
|---|---|---|---|---|---|
| 1 | csv | 83 | A- | 1552.1k | A mature CSV toolset with simple api, full of options and tested against large datasets. |
| 2 | @wordpress/fields | 82 | A- | 27.3k | DataViews is a component that provides an API to render datasets using different types of layouts (t... |
| 3 | @wordpress/dataviews | 82 | A- | 47.6k | DataViews is a component that provides an API to render datasets using different types of layouts (t... |
| 4 | datasets | 81 | A- | 16324.3k | HuggingFace community-driven open-source library of datasets |
| 5 | huggingface-hub | 81 | A- | 119015.4k | Client library to download and publish models, datasets and other repos on the huggingface.co hub |
| 6 | @sqlrooms/data-table | 76 | B+ | 4.1k | A high-performance data table component library for SQLRooms applications. This package provides fle... |
| 7 | datasketch | 76 | B+ | 6569.2k | Probabilistic data structures for processing and searching very large datasets |
| 8 | @humanspeak/svelte-virtual-list | 74 | B | 2.6k | A lightweight, high-performance virtual list component for Svelte 5 that renders large datasets with... |
| 9 | @llm-tools/embedjs | 74 | B | 174 | A NodeJS RAG framework to easily work with LLMs and custom datasets |
| 10 | @edgeandnode/amp | 74 | B | 176 | Build and manage blockchain datasets. |
| 11 | @friendliai/ai-provider | 72 | B | 94 | <!-- header start --> <p align="center"> <img src="https://huggingface.co/datasets/FriendliAI/docu... |
| 12 | @datawheel/vizbuilder | 72 | B | 11 | A React component that generates multiple kinds of charts from a tesseract-olap dataset. |
| 13 | autoviz | 72 | B | 3.4k | Automatically Visualize any dataset, any size with a single line of code |
| 14 | vaex | 72 | B | 4.9k | Out-of-Core DataFrames to visualize and explore big tabular datasets |
| 15 | rio-tiler | 72 | B | 388.5k | User friendly Rasterio plugin to read raster datasets. |
| 16 | hapi-csv | 72 | B | 441 | Hapi plugin for converting a Joi response schema and dataset to csv |
| 17 | pyiceberg | 72 | B | 37398.9k | Apache Iceberg is an open table format for huge analytic datasets |
| 18 | @lovrabet/dataset-mcp-server | 72 | B | 309 | MCP server for Lovrabet Dataset access |
| 19 | process-versions | 71 | B | 130 | A dataset showing the compiled process version dependencies of different Node.js versions |
| 20 | seqio-nightly | 71 | B | 258.8k | SeqIO: Task-based datasets, preprocessing, and evaluation for sequence models. |
| 21 | vue-dataset | 71 | B | 584 | A vue component to display datasets with filtering, paging and sorting capabilities! |
| 22 | kedro-datasets | 71 | B | 1700.2k | Kedro-Datasets is where you can find all of Kedro's data connectors. |
| 23 | @donedeal0/superdiff | 70 | B | 8.4k | Superdiff provides a rich and readable diff for arrays, objects, texts and coordinates. It supports ... |
| 24 | abses | 70 | B | 116 | ABSESpy makes it easier to build artificial Social-ecological systems with real GeoSpatial datasets ... |
| 25 | pybids | 70 | B | 115.6k | bids: interface with datasets conforming to BIDS |
| 26 | cellxgene-schema | 70 | B- | 267 | Tool for applying and validating cellxgene integration schema to single cell datasets |
| 27 | rasterstats | 70 | B- | 337.3k | Summarize geospatial raster datasets based on vector geometries |
| 28 | azureml-opendatasets | 70 | B- | 8.4k | Provides a set of APIs to consume Azure Open Datasets. |
| 29 | ancpbids | 69 | B- | 3.7k | Read/write/validate/query BIDS datasets |
| 30 | @ldo/jsonld-dataset-proxy | 69 | B- | 754 | Edit RDFJS Dataset just like regular JavaScript Object Literals. |
| 31 | @muze-nl/simplystore | 69 | B- | 1 | SimplyStore is a radically simpler backend storage server. It does not have a database, certainly no... |
| 32 | img2dataset | 69 | B- | 82.2k | Easily turn a set of image urls to an image dataset |
| 33 | node-dataset | 69 | B- | 100 | A Node.js module for working with data sets created in code, loaded from files, or retrieved from a ... |
| 34 | tfds-nightly | 69 | B- | 84.6k | tensorflow/datasets is a library of datasets ready to use with TensorFlow. |
| 35 | imbalanced-learn | 68 | B- | 14138.4k | Toolbox for imbalanced dataset in machine learning |
| 36 | data_magic | 68 | B- | 14364.0k | Provides datasets to application stored in YAML files |
| 37 | cellxgene | 68 | B- | 868 | Web application for exploration of large scale scRNA-seq datasets |
| 38 | cemba-data | 68 | B- | 4 | Pipelines for single nucleus methylome and multi-omic dataset. |
| 39 | act-atmos | 68 | B- | 1.2k | Package for working with atmospheric time series datasets |
| 40 | @vespermcp/mcp-server | 67 | B- | 244 | AI-powered dataset discovery, quality analysis, and preparation MCP server with multimodal support (... |
| 41 | nuscenes-devkit | 67 | B- | 173.2k | The official devkit of the nuScenes dataset (www.nuscenes.org). |
| 42 | azureml-datadrift | 67 | B- | 220 | Contains functionality for data drift detection for various datasets used in machine learning. |
| 43 | arcana | 67 | B- | 618 | Abstraction of Repository-Centric ANAlysis (Arcana): A rramework for analysing on file-based dataset... |
| 44 | azureml-contrib-dataset | 67 | B- | 996 | Contains experimental Dataset features for the azureml-core package. |
| 45 | mnemospark | 67 | B- | 544 | mnemospark is an OpenClaw plugin that gives agentic systems instant, secure access to cloud storage,... |
| 46 | @cherrystudio/embedjs | 67 | B- | 541 | A NodeJS RAG framework to easily work with LLMs and custom datasets |
| 47 | baran | 67 | B- | 1189.5k | Text Splitter for Large Language Model Datasets. |
| 48 | devise-pwned_password | 67 | B- | 2970.8k | Devise extension that checks user passwords against the PwnedPasswords dataset https://haveibeenpwne... |
| 49 | rgeo-shapefile | 67 | B- | 3620.0k | RGeo is a geospatial data library for Ruby. RGeo::Shapefile is an optional RGeo module for reading t... |
| 50 | gruff | 67 | B- | 3776.5k | Beautiful graphs for one or multiple datasets. Can be used on websites or in documents. |
So bewerten wir AI Datasets
These ai datasets are ranked nach Nerq-Vertrauenswertung, which evaluates Sicherheit, Wartung, Community-Akzeptanz, and transparency across multiple data points. Only entities with a trust score of 30 or above are included. Bewertungen werden kontinuierlich aktualisiert, sobald neue Daten verfügbar sind.
Häufig gestellte Fragen
Welche sind die besten Best AI Datasets 2026?
Basierend auf Nerq-Vertrauenswerten sind die bestbewerteten Best AI Datasets oben aufgeführt, bewertet nach Sicherheit, Wartung, Dokumentation und Community-Nutzung.
Wie werden Best AI Datasets bewertet?
Nerq bewertet Tools mit Trust Score v2, der Sicherheitsanalyse, Wartungsaktivität, Dokumentationsqualität und Community-Akzeptanz kombiniert.
Sind diese Best AI Datasets sicher zu verwenden?
Jedes Tool hat einen individuellen Sicherheitsbericht. Klicken Sie auf einen Toolnamen, um die detaillierte Vertrauensanalyse zu sehen.
Was bedeutet ein Nerq Trust Score von A?
Die Note A (80–89) bedeutet, dass die Entität starke Signale in Sicherheit, Wartung, Dokumentation und Community-Akzeptanz hat. A+ (90–100) ist die höchste Bewertung.
Wie bewertet Nerq Best AI Datasets?
Nerq analysiert Best AI Datasets über mehrere Dimensionen einschließlich Sicherheitslücken, Lizenzkonformität, Wartungsaktivität, Dokumentationsqualität und Community-Nutzung. Jede Dimension wird unabhängig bewertet und zu einem Gesamt-Vertrauenswert (0–100) kombiniert.