Alternative data datasets
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This dataset is a small parquet-format subset of clinical-trial eligibility criteria represented as entity and relation graphs. It is published on a community data hub under an unspecified license.
This dataset, published by 2001jdev on Hugging Face, packages eligibility-criteria information from clinical trials into structured entity and relation records. It is distributed in Parquet format and contains a single split of roughly 104,000 rows.
The clinical-trials-patient-graphs dataset is a small tabular collection of patient-level clinical records distributed in Parquet format by the 2001jdev publisher. It organizes entities and relations extracted from trial data into structured rows spanning 2021 through 2023.
clinical-trials-synth-patient-profiles2 is a synthetic patient-profile dataset distributed by publisher 2001jdev on a public dataset registry. It pairs clinical trial identifiers with short free-text profile descriptions and a coded entity taxonomy, designed for text and entity-recognition work rather than production research.
This dataset is a parsed snapshot of ClinicalTrials.gov records, distributed in Parquet format on the Hugging Face Hub under an unspecified license. It contains roughly 52,000 trial entries drawn from public registry filings.
clinical-trials-trec-qrels is a tabular relevance-judgment file distributed by the 2001jdev user on the Hugging Face Hub. It maps clinical-trial topic identifiers to NCT registry IDs with graded relevance scores.
The clinical-trials-trec-topics dataset is a small tabular collection of clinical-trial topic records distributed in Parquet format on the Hugging Face Hub. It appears to be derived from TREC clinical-trial retrieval topics, with rows partitioned by year.
The job-postings-english-clean dataset, published by 2024-mcm-everitt-ryan, is an English-language corpus of online job postings distributed as a single Parquet train split of roughly 1.76 million rows. It is tagged as US-region data and is intended for text-based machine learning workflows.
The job-postings-raw dataset is a large-scale tabular collection of scraped job postings distributed in Parquet format. It aggregates records across multiple sources and locales, with US coverage indicated in the dataset metadata.
credit_card_transactions is a small tabular dataset published by aegisheld containing anonymized customer-level credit card account and spending summaries. It is distributed as CSV with a single training split of 8,950 rows.
About 1.5 million US patent claims split into training and test partitions in CSV, organized for claim-level classification and summarization work (Apache 2.0). A large, ready-split corpus for IP-claims modeling.
A component of the ALEA Institute's KL3M Data Project supplying training material cleared of copyright concerns. The dataset card is currently a placeholder, directing readers to the GitHub repo and project paper for full documentation.
The KL3M Data Project from the ALEA Institute supplies copyright-clean training material, and the dataset listed here is one component pending further documentation on its dedicated page.
Material contracts and agreements extracted from EDGAR filings by the KL3M project: debt, M&A, employment and license agreements, millions of documents in Parquet. Contract language is a niche but real input for M&A, financing and litigation-event signals.
The kl3m-index-edgar-filings dataset, published by ALEA Institute, is a Parquet-format index of SEC EDGAR filings distributed via the Hub datasets library. It contains roughly 20 million tabular records spanning the 10M–100M size category, with an unstated license.
The KL3M Index of EDGAR 10-K Filings is a tabular index published by the Alea Institute that catalogs SEC EDGAR filings with associated issuer metadata. It is distributed in Parquet format and is tagged for use with pandas, polars, and the mlcroissant dataset library.
The kl3m-index-edgar-filings-8-k dataset is an indexed catalog of Form 8-K filings from the SEC's EDGAR system, published by the ALEA Institute. It provides structured metadata for over 1.8 million corporate event reports distributed in Parquet format.
EDGAR_FILINGS_DATASET_2016_2021 is a Hugging Face mirror of parsed SEC EDGAR filings spanning 2016 through 2021, distributed as a single train split of about 6 million rows in Parquet format. It is published by anonymous-md with an unstated license.
EDGAR_FILINGS_DATASET_2022_2026H1 is a Hugging Face dataset that compiles parsed SEC EDGAR filings into a single tabular corpus. It covers roughly 2022 through the first half of 2026 and is distributed as Parquet with about 1.7 million records.
Dataset Card for "earnings21-gold-transcripts-non-normalized" More Information needed
The TREC Clinical Trials collections released in 2021, 2022, and 2023 are available through the TREC homepage, with corresponding papers for each year. Artur Guimarães ([email protected]) serves as the dataset curator, while inquiries regarding the original authors can be directed separately. The dataset addresses the task of linking patient profiles with appropriate clinical trials, containing entries formatted as JSON objects with fields including query identifiers, disease labels, and accompanying clinical text.
The awinml/earnings_calls_transcripts dataset on the Hugging Face Hub packages a small collection of earnings-call transcript segments formatted as chat-style messages for fine-tuning language models. It is distributed as a parquet file and is tagged for text modality with libraries including datasets, pandas, mlcroissant, and polars.
The airline-otp-data dataset is a large-scale, public-style tabular repository of U.S. domestic flight records covering on-time performance, delay attribution and cancellation outcomes. Published on Hugging Face under an unstated license, it contains roughly 30 million rows in CSV format and is aimed at analysts working with airline operations data.
This dataset is a filtered version of https://huggingface.co/datasets/vincha77/filtered_yelp_restaurant_reviews
yelp_restaurant_reviews_5k is a small text dataset of 5,079 Yelp reviews distributed by bespokelabs, distributed as a single train split. It is structured for straightforward text classification with numeric and categorical fields.
PatentMatch pairs US patents with matching reference patents for retrieval evaluation, a few thousand records in JSON (Apache 2.0). A niche evaluation set for patent-similarity and citation-link models.
A reference collection drawn from the U.S. Patent Phrase to Phrase Matching Kaggle competition, containing additional details that are still required for full documentation.
Cadenza-Labs/apollo-llama3.3-insider-trading-generations is a small text dataset on Hugging Face containing 1,660 training rows used to fine-tune a Llama 3.3 model for detecting dishonest messages. It is distributed in Parquet format and released under an unstated license.
A sample of US patent titles, abstracts and CPC classification labels built for multi-class patent classification, tens of thousands of text records in Parquet. Useful as training material for mapping innovation activity onto technology categories over time.
clinical-trials-v2 is a Hugging Face dataset published by chemNLP containing processed ClinicalTrials.gov records stored in Parquet. It exposes three columns — filename, xml, and text — drawn from the official clinical-study XML schema.
Chinese patents paired with their abstractive summaries in Mandarin, a few thousand records in JSON (Apache 2.0). A window into the pace and direction of patenting inside the Chinese technology base.
A small text-classification dataset by ClarusC64 that labels whether borrow-rate, short-interest and price signals cohere into a real short squeeze or diverge into a false signal. It is published on a model hub with an MIT license tag and a 10-row train split.
GenAI-job-postings-Dataset is a small, US-focused text corpus of generative-AI and machine-learning job postings distributed in Parquet format. The dataset is published on the Hugging Face Hub under an unstated license and comprises a single train split of roughly 120 rows.
A collection of restaurant reviews was assembled in 2019 through Python-based web scraping focused on Dutch establishments, capturing both visit experiences and feature-related information. It is organized in the DatasetDict format with three splits: 116,693 training records, 14,587 test records, and 14,587 validation records.
Records of initial public offerings launched on Indian markets between 2006 and 2025, with fields covering open and close dates, listing date, face value, issue price and size, lot size, first-day price, total shares offered and their allocation across anchor, NII, QIB and retail categories, minimum investment, and subscription figures for each investor class.
A tabular extract of clinical study descriptions drawn from ClinicalTrials.gov on 5 February 2025, emphasizing eligibility, design, and objective fields for healthcare and machine learning research.
Dattito's clinical-trials-data is a Parquet-format dataset of roughly 24 million clinical trial records sourced from public trial registries. It aggregates identifiers, conditions, and standardized medical terminology into a single table for large-scale analysis.
An artificially generated collection of apparel product listings and accompanying advertisements produced by prompting GPT-4 to invent one hundred clothing items with descriptions and then write promotional copy for each, output in a structured product and description format without subsequent manual verification.
stk-sec-filings is a small Hugging Face dataset by publisher deerfieldgreen that consolidates U.S. SEC filings into a single Parquet resource. The file covers fewer than one thousand rows distributed across a training split, with no stated update cadence or refresh policy.
DerivedFunction01's sec-filings-snippets is a public-records dataset of short text excerpts drawn from U.S. SEC filings, released on Hugging Face in Parquet format. It is sized for language-model fill-mask work and is not positioned as a commercial alternative-data product.
airline-disruption-data is a tabular dataset of U.S. domestic flight records published on the datasets hub, tagged as covering between 10 million and 100 million rows in Parquet format. The schema describes per-flight scheduling, delay, cancellation, and routing fields.
The airline-disruption-data-phase1b dataset is a tabular release hosted by publisher Dev123Hug456Face that compiles scheduled and actual flight-level operations data with delay, cancellation and diversion flags. It is distributed as a single Parquet split of roughly 12 million rows.
ClinicalTrials.gov XML for studies registered between 2018 and 2024, parsed into CSV, hundreds of thousands of records under CC0. A clean, licensed point-in-time history of US clinical-trial registrations.
MolMole_Patent300 is a curated evaluation benchmark for extracting chemical information from full patent pages, supporting end-to-end testing of molecule detection, reaction parsing, and optical chemical structure recognition.
A large granted-patent text collection from the USPTO, tens of millions of records in Parquet (Apache 2.0). Broad coverage of claims and descriptions for IP-intensity and technology-trend measurement.
Restaurant Reviews Parsing NER Aspects This dataset is for the task of identifying the aspects of the restaurants mentioned in the reviews where aspect contains information about both the entities (FOOD, AMBIENCE, ...) and the attached sentiments. The input texts are from SemEval dataset. Labels for train and val datasets are generated by prompting Llama3 while the test dataset is curatedly manual
Generated with the LeRobot framework, this dataset comprises 80 episodes demonstrating a pick-and-place routine using a single orange cube positioned at varying locations within the workspace. Each episode requires the robot to rotate toward the cube, open its gripper, close it around the object, and transport it to a specified drop zone.
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v3.0", "fps": 30, "features": { "action": { "dtype": "float32", "names": [ "shoulder_pan.pos", "shoulder_lift.pos", "elbow_flex.pos", "wrist_flex.pos", "wrist_roll.pos", "gripper.pos" ], "shape": [ 6… See the full description on the dataset page: https://huggingface.co/datasets/Edgarium/rangement_pq_20
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v2.1", "robot_type": "so101_follower", "total_episodes": 24, "total_frames": 5358, "total_tasks": 1, "total_videos": 48, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:24" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path":… Se
A LeRobot-formatted dataset captured with a so101_follower robot, comprising 30 episodes, 6,788 frames, 60 video files, and a single chunk at 30 fps, with training covering the full episode range.
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v2.1", "robot_type": "so101_follower", "total_episodes": 50, "total_frames": 13379, "total_tasks": 1, "total_videos": 100, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:50" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path":…
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v2.1", "robot_type": "so101_follower", "total_episodes": 709, "total_frames": 187905, "total_tasks": 1, "total_videos": 1418, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:709" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path
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This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v2.1", "robot_type": "so101_follower", "total_episodes": 50, "total_frames": 12620, "total_tasks": 1, "total_videos": 100, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:50" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path":…
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