Best AI Datasets 2026
The #1 ai datasets in 2026 is csv с рейтингом доверия Nerq 83/100 (A-), based on Nerq's independent analysis of 50 ai datasets across 5 trust показателей. Обновляется ежедневно — последнее обновление: 2026-11-05.
Согласно 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 показателей including безопасность, обслуживание, and принятие сообществом. Обновляется ежедневно.
| # | Название | Доверие | Оценка |
|---|---|---|---|
| 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 по Nerq Trust Score
| # | Название | Доверие | Оценка | Stars | Описание |
|---|---|---|---|---|---|
| 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. |
Как мы оцениваем AI Datasets
These ai datasets are ranked по Nerq Trust Score, which evaluates безопасность, обслуживание, принятие сообществом, and transparency across multiple data points. Only entities with a trust score of 30 or above are included. Рейтинги обновляются непрерывно по мере поступления новых данных.
Часто задаваемые вопросы
Какие лучшие Best AI Datasets в 2026 году?
На основе оценок доверия Nerq лучшие Best AI Datasets перечислены выше, оценённые по безопасности, поддержке, документации и принятию сообществом.
Как ранжируются Best AI Datasets?
Nerq ранжирует инструменты с помощью Trust Score v2, который сочетает анализ безопасности, активность поддержки, качество документации и принятие сообществом.
Безопасны ли эти Best AI Datasets для использования?
Каждый инструмент имеет индивидуальный отчёт о безопасности. Нажмите на название инструмента, чтобы увидеть подробный анализ доверия.
Что означает Nerq Trust Score A?
Оценка A (80–89) означает, что сущность имеет сильные сигналы в безопасности, поддержке, документации и принятии сообществом. A+ (90–100) — наивысшая оценка.
Как Nerq оценивает Best AI Datasets?
Nerq анализирует Best AI Datasets по нескольким измерениям, включая уязвимости безопасности, соответствие лицензиям, активность поддержки, качество документации и принятие сообществом. Каждое измерение оценивается независимо и объединяется в общий балл доверия (0–100).