Best AI Datasets 2026
The #1 ai datasets in 2026 is csv dengan Skor Kepercayaan Nerq sebesar 83/100 (A-), based on Nerq's independent analysis of 50 ai datasets across 5 trust dimensi. Diperbarui setiap hari — terakhir diperbarui: 2026-11-05.
Menurut 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 dimensi including keamanan, pemeliharaan, and adopsi komunitas. Diperbarui setiap hari.
| # | Nama | Kepercayaan | Nilai |
|---|---|---|---|
| 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 berdasarkan Nerq Trust Score
| # | Nama | Kepercayaan | Nilai | Stars | Deskripsi |
|---|---|---|---|---|---|
| 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. |
Cara Kami Memberi Peringkat AI Datasets
These ai datasets are ranked berdasarkan Nerq Trust Score, which evaluates keamanan, pemeliharaan, adopsi komunitas, and transparency across multiple data points. Only entities with a trust score of 30 or above are included. Skor diperbarui secara berkelanjutan saat data baru tersedia.
Pertanyaan yang Sering Diajukan
Apa Best AI Datasets terbaik di tahun 2026?
Berdasarkan skor kepercayaan Nerq, Best AI Datasets dengan peringkat tertinggi tercantum di atas, dinilai berdasarkan keamanan, pemeliharaan, dokumentasi, dan adopsi komunitas.
Bagaimana Best AI Datasets dirangking?
Nerq merangking alat menggunakan Trust Score v2, yang menggabungkan analisis keamanan, aktivitas pemeliharaan, kualitas dokumentasi, dan adopsi komunitas.
Apakah Best AI Datasets ini aman digunakan?
Setiap alat memiliki laporan keamanan individual. Klik nama alat untuk melihat analisis kepercayaan detailnya.
Apa arti Nerq Trust Score A?
Nilai A (80–89) berarti entitas memiliki sinyal kuat di keamanan, pemeliharaan, dokumentasi, dan adopsi komunitas. A+ (90–100) adalah peringkat tertinggi.
Bagaimana Nerq mengevaluasi Best AI Datasets?
Nerq menganalisis Best AI Datasets di berbagai dimensi termasuk kerentanan keamanan, kepatuhan lisensi, aktivitas pemeliharaan, kualitas dokumentasi, dan adopsi komunitas. Setiap dimensi dinilai secara independen dan digabungkan menjadi skor kepercayaan keseluruhan (0–100).