Alternative data datasets
Browse by provider, category, marketplace, access, delivery and license
Parsed eligibility criteria from 13,229 ClinicalTrials.gov studies representing the candidate pool gathered by two first-stage retrievers during TREC Clinical Trials 2021–2023, formatted as typed entity-relation graphs for reranking models.
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.
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.
An aggregation of 1.3 million U.S. patent records each accompanied by a human-written abstractive summary, sorted into nine Cooperative Patent Classification groupings spanning human necessities, chemistry, textiles, and related domains.
Collection of historical Swedish patent texts from 1885 to 1972 assigned multi-label Cooperative Patent Classification (CPC) codes, intended for retrieval, prior art searching, and multi-label classification tasks.
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.
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.
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.
titer · EDGAR officer corpus 4,206,080 attested person–company–role–date tuples from SEC Forms 3/4/5, published as pointers rather than records, alongside the frozen pre-registrations that were hash-published before any measurement ran. edgar_officers.parquet: 4.2M rows, 230,405 distinct people, 20,266 issuers, 2006q1–2026q2. Column Meaning accession SEC accession number, the pointer that reconstr
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.
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.
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.
Vector embeddings of clinical-trial records, hundreds of thousands of entries in Parquet (Apache 2.0). Enables similarity and retrieval analysis of trial design, indication crowding and competitive positioning.
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.
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.
edgar_xbrl_companyfacts is a Hugging Face dataset published by DenyTranDFW that aggregates U.S. SEC EDGAR XBRL company-facts filings into a single Parquet file. The training split contains roughly 125 million rows of structured financial facts tagged by reporting period and unit.
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.
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
An adaptation of the CelebA-HQ face image set at 512 resolution that retains the original photographs while appending identity-cluster labels produced automatically through face embedding grouping.
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
A robotics dataset generated with the LeRobot framework contains two recorded episodes totaling 897 frames at 30 frames per second, captured using an SO100 robot performing a single task, with four video files and accompanying parquet data organized in a single chunk of up to 1,000 entries and partitioned as a train split covering episodes zero through one.
Another LeRobot so100 robotics dataset containing 50 episodes, 29,874 frames, and 100 videos at 30 fps, structured identically to the related edgar-block release.
A LeRobot dataset captured on the so100 robot platform, consisting of 50 episodes, 44,746 frames, and 100 videos recorded at 30 fps and split for training.
A robotics dataset assembled with the LeRobot framework for the SO100 platform, containing 20 episodes totaling 11,940 frames captured at 30 fps, stored in parquet data files alongside 40 corresponding video chunks.
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":…
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v2.1", "robot_type": "so101_follower", "total_episodes": 500, "total_frames": 136475, "total_tasks": 1, "total_videos": 1000, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:500" }, "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": 500, "total_frames": 137269, "total_tasks": 1, "total_videos": 1000, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:500" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path
A LeRobot-formatted robotics capture set for the so101_follower arm, comprising 51 episodes, 13,109 frames, and 102 videos at 30 fps stored across parquet chunks.
A LeRobot-generated dataset comprising 149 episodes, 27,628 frames, and 298 video files captured at 30 fps on a so101_follower robot, with all episodes assigned to the training split and stored in the chunk-based Parquet layout expected by the codebase.
Prepared by Electric Sheep Africa, this MDPA-sourced dataset supplies 10 entries of hotel room occupancy rates for Mauritius over 2019-2023, delivered as ML-ready Parquet files accompanied by uniform Hugging Face metadata and source provenance.
A small Parquet-format collection from Electric Sheep Africa reporting room occupancy rates for large hotels in Mauritius from 2019 to 2023, containing ten records drawn from MDPA and packaged with Hugging Face metadata for machine learning workflows.