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Industry Datasets.

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# Industry Datasets

A curated list of business datasets from the fields of Machine Learning, Marketing, Economics, Transportation, Operations, and Computer Science.

> **241 datasets** across 31 categories — last updated May 2026

Added 1 logistics dataset for packaging optimization benchmarks:

- **Logistics** — Packrift Packaging Optimization Benchmark Corpus

</details>

Added 14 industrial datasets for DDC/IRL estimation:

- **Healthcare** — MIMIC-IV, eICU, ICU-Sepsis MDP
- **Discrete Economic Choices** — Igami HDD Industry, Collard-Wexler Concrete, EPA CEMS Emissions, USDA Cropland Data Layer
- **Taxi/Ride-Hailing** — Chicago Taxi Trips, Bay Wheels
- **Travel** — Airline DB1B Tickets
- **Financial** — FDIC Summary of Deposits
- **Auctions** — FCC Spectrum Auctions
- **Grocery** — Aguirregabiria Supermarket
- **Fashion** — H&M Personalized Fashion

</details>

Added 19 datasets from route choice, gig-economy labor supply, and browsing DDC research:

- **Driving/Mobility** — NYC Yellow Taxi (2009–2013), NYC HVFHV (Uber/Lyft), DiDi GAIA Chengdu, Shanghai Taxi (AIRL), SF Cabspotting, METR-LA, PEMS-BAY
- **Search/Rec** — KuaiRand, KuaiRec, Tenrec, Baidu-ULTR, TianGong-ST
- **Commerce** — REES46 Multi-Category Store, OTTO RecSys 2022, MerRec (Mercari)
- **Music** — Deezer Listening Events, Last.fm 1K
- **News** — Adressa, Globo.com

</details>

## Contents

- [LLM Interaction Datasets with Sequential Feedback](#llm-interaction-datasets-with-sequential-feedback)
- [General e-Commerce](#general-e-commerce)
- [E-Commerce Sessions](#e-commerce-sessions)
- [A/B Tests and Experiments](#ab-tests-and-experiments)
- [Browsing and Search](#browsing-and-search)
- [Search and Ranking](#search-and-ranking)
- [Video Search and Recommendation](#video-search-and-recommendation)
- [Video Engagement](#video-engagement)
- [News and Media](#news-and-media)
- [Product and Reviews](#product-and-reviews)
- [Sales and Forecasting](#sales-and-forecasting)
- [Supermarkets and Grocery](#supermarkets-and-grocery)
- [Financial Transactions](#financial-transactions)
- [Fashion](#fashion)
- [Cars and Used Cars](#cars-and-used-cars)
- [Discrete Economic Choices](#discrete-economic-choices)
- [Travel](#travel)
- [Music](#music)
- [Procurement and Online Auctions](#procurement-and-online-auctions)
- [Display Advertising and Sponsered Search Auctions](#display-advertising-and-sponsered-search-auctions)
- [Healthcare](#healthcare)
- [Logistics](#logistics)
- [Taxi and Ride-Hailing GPS](#taxi-and-ride-hailing-gps)
- [Driving Behavior and Traffic Sensors](#driving-behavior-and-traffic-sensors)
- [Human Trajectories](#human-trajectories)
- [Check-in and Location Data](#check-in-and-location-data)
- [Housing and Residential Prices](#housing-and-residential-prices)
- [Research Datasets and Collections](#research-datasets-and-collections)
- [Competitions](#competitions)
- [Gaming](#gaming)
- [Others](#others)

---

## LLM Interaction Datasets with Sequential Feedback

Datasets capturing multi-turn dialogues with LLMs, including quality feedback and preference signals.

## General e-Commerce

Datasets focusing on online retail transactions and purchase logs.

| Dataset              | Description                                                                                                                                                       | URL                                                                 |
|----------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------|
| **Brazilian eCommerce** | 100,000 orders (2016-2018) from Olist marketplaces across Brazil, structured in 9 relational tables (customers, orders, payments, products, geolocation, reviews). | [Source](https://www.kaggle.com/datasets/olistbr/brazilian-ecommerce) |
| **JD.com (2011-2014)** | Consumer behavior (2011-2014), 15/987 categories, ~2M users, >100k products, 60M+ reviews (positive/negative/overall), purchase behavior, ratings, metadata.    | [Source](https://www.yongfeng.me/dataset/) |
| **JD.com 2020 (MSOM-20)** | Transaction-level data (March 2018) featuring 2.5M customers (457k purchasers) and 31,868 SKUs, emphasizing purchase conversion pathways.                     | [Source](https://connect.informs.org/msom/events/datadriven2020) |
| **Alibaba Ads (IJCAI-18)** | 6 billion display ad/click logs over 8 days from 100 million users and 70 million items.                                                                     | [Source](https://tianchi.aliyun.com/dataset/147588) |
| **Alibaba Mobile (6GB)** | Mobile e-commerce user behavior data, including clicks, purchases, user profiles.                                                                                | [Source](https://www.yongfeng.me/dataset/) |
| **Google Merchandise** | 3 months obfuscated GA4 e-commerce data (Nov 2020-Jan 2021), traffic sources, content behavior, transaction data. Via BigQuery Public Datasets.                   | [Source](https://support.google.com/analytics/answer/7586738#) |
| **Shopee**           | Dataset from Shopee's Code League competition in 2020.                                                                                                           | [Source](https://www.kaggle.com/datasets/davydev/shopee-code-league-20) |
| **Flipkart**         | Sales dataset from the Indian e-commerce platform Flipkart.                                                                                                      | [Source](https://www.kaggle.com/datasets/iyumrahul/flipkartsalesdataset?select=Sales.csv) |
| **Pakistan e-commerce** | Largest retail e-commerce dataset from Pakistan: 500k+ transactions (Mar 2016 - Aug 2018).                                                                       | [Source](https://www.kaggle.com/datasets/zusmani/pakistans-largest-ecommerce-dataset) |
| **Instacart**        | 3.4M orders, 206k+ users, 49k+ products (134 aisles, 21 depts), order timing, prior orders. Avg reorder ~59%. (More detailed view).                               | [Source](https://mdporter.github.io/DS6030/other/instacart.html#:~:text=,measure%20of%20time%20between%20orders) |
| **Open E-Commerce 1.0 (MIT)** | 1.8M Amazon purchase records with demographic attributes (age, gender, location), enabling research on consumer behavior across population segments. | [Source](https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/YGLYDY) |

---

## E-Commerce Sessions

Session-based e-commerce datasets capturing multi-event click trails (views, carts, purchases) within user sessions, suited for sequential recommendation and DDC modeling.

| Dataset | Description | URL |
|---------|-------------|-----|
| **Open CDP** | Open-source Customer Data Platform by REES46 aggregating omnichannel interactions (web, app, POS) with AI-driven identity resolution and event tracking (14+ types). | [Source](https://rees46.com/en/datasets) |
| **Coveo Shopping (SIGIR-21)** | Session-based dataset with 30M+ browsing events, featuring query vectors, image vectors, and description embeddings for recommendation and purchase intent tasks. | [Source](https://github.com/coveooss/SIGIR-ecom-data-challenge#how-to-start) |
| **Retail Rocket** | 4.5-month clickstream dataset with 2.76M events (views, carts, purchases) from 1.4M visitors across 417k items; includes a deduplicated version. | [Source](https://www.kaggle.com/datasets/retailrocket/ecommerce-dataset?select=events.csv) |
| **YOOCHOOSE RecSys 2015** | Session-based click and purchase events from a European e-commerce retailer, used in the RecSys Challenge 2015 for session-based recommendation research. | [Source](https://www.kaggle.com/datasets/chadgostopp/recsys-challenge-2015) |
| **REES46 Multi-Category Store** | 285M events (view, cart, remove-from-cart, purchase) from October 2019–April 2020 with explicit user_session IDs, millisecond timestamps, product category hierarchies (e.g., "electronics.smartphone"), brand names, and prices. Companion datasets for a cosmetics shop and electronics store have identical schemas. | [Source](https://www.kaggle.com/datasets/mkechinov/ecommerce-behavior-data-from-multi-category-store) |
| **OTTO RecSys 2022** | 220M events across 12M sessions from the German e-commerce platform OTTO, with clicks, cart additions, and orders timestamped within sessions. Large, clean, and CC BY 4.0 licensed. Item features are anonymized (IDs only, no categories or prices). | [Source](https://www.kaggle.com/datasets/otto/recsys-dataset) |
| **MerRec (Mercari)** | Large-scale C2C marketplace dataset from Mercari with millions of users, session IDs, timestamped action types, product taxonomy, and textual attributes over 6 months. CC BY-NC 4.0. Published at KDD 2025. | [Source](https://huggingface.co/datasets/mercari-us/merrec) |

---

## A/B Tests and Experiments

Datasets resulting from controlled experiments, often used for causal inference or evaluating interventions.

| Dataset                      | Description                                                                                                                                    | URL                                                                                |
|------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------|
| **Upworthy News Headlines**  | Largest public A/B testing repository: 32,487 headline/image experiments (2013-2015) on 538M participant assignments, including engagement metrics. | [Source](https://upworthy.natematias.com/)                                         |
| **ASSISTments Dataset**      | Data from the ASSISTments online tutoring platform, often used for educational data mining and A/B testing research.                             | [Source](https://sites.google.com/site/las2016data/home?authuser=0)                |
| **Gamified Learning**        | Dataset related to experiments on gamification in learning environments.                                                                         | [Source](https://www.sciencedirect.com/science/article/pii/S2352340917301646#s0010) |
| **Collection (GSB DBI)**     | A collection of datasets suitable for experimentation analysis maintained by Stanford GSB Data, Analytics & Research Computing.                 | [Source](https://github.com/gsbDBI/ExperimentData)                                 |
| **Athey's course**           | Datasets used in Susan Athey's course materials, often related to causal inference and experimental design.                                      | [Source](https://github.com/itamarcaspi/experimentdatar/tree/master)               |
| **Development (PEP)**        | Experimental research datasets focused on development economics from the Partnership for Economic Policy (PEP).                                  | [Source](https://www.pep-net.org/publications/datasets/experimental-research-datasets) |
| **Computational Neuroscience**| Datasets for computational neuroscience research, often involving experimental data from neural recordings or behavior.                         | [Source](https://crcns.org/)                                                       |
| **ASOS experiments**       | 99 real e-commerce experiments from ASOS with daily metric checkpoints (4 KPIs) and p-values, used for validating adaptive stopping rules.       | [Source](https://www.kaggle.com/datasets/marinazmieva/asos-digital-experiments-dataset?select=document.pdf) |

---

## Browsing and Search

Platform clickstream, user behavior logs, and e-commerce browsing data.

| Dataset                       | Description                                                                                                                                         | URL                                                                          |
|-------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------|
| **Amazon Sessions (KDD Cup 23)** | Multilingual Shopping Session Dataset: Sessions from 6 locales (DE, JP, UK, ES, FR, IT), ~40k-500k products per locale, rich product attributes.        | [Source](https://www.aicrowd.com/challenges/amazon-kdd-cup-23-multilingual-recommendation-challenge) |
| **JD.com Search**             | 170,000 users' real search queries (2021-2022) with multi-channel interactions (clicks, carts, purchases), 987 categories, and exposed candidate lists. | [Source](https://github.com/rucliujn/JDsearch)                               |
| **JD-pretrain-data**          | Encoded search queries, item titles, categories for user intent detection and embedding retrieval (5 TSV files).                                      | [Source](https://github.com/jdcomsearch/jd-pretrain-data)                    |
| **BestBuy**                   | Mobile website clicks (~42k) for Xbox games: user IDs, queries, product IDs, timestamps, game attributes. ~3.8k unique queries after cleaning.        | [Source](https://www.kaggle.com/c/acm-sf-chapter-hackathon-big/data)         |
| **Ele Search**                | Search log dataset from Ele.me (Chinese food delivery platform).                                                                                    | [Source](https://tianchi.aliyun.com/dataset/120281)                          |
| **Ele Clickstream**           | Clickstream data from Ele.me.                                                                                                                       | [Source](https://tianchi.aliyun.com/dataset/131047)                          |
| **Alibaba Industrial Dump (150GB)** | Large-scale industrial dataset from Alibaba Cloud.                                                                                                | [Source](https://tianchi.aliyun.com/dataset/81505)                           |
| **Alibaba Fashion Combo**     | Dataset focusing on fashion item combinations from Alibaba.                                                                                         | [Source](https://tianchi.aliyun.com/dataset/131519)                          |
| **Alibaba Brick and Mortar (IJCAI-16)** | Combines online browsing/purchase data with offline check-ins/purchases from 1,000+ physical stores linked to Alibaba's O2O platform.       | [Source](https://tianchi.aliyun.com/dataset/53)                              |
| **Alibaba Mobile 2021**       | Mobile user behavior data from Alibaba for 2021.                                                                                                    | [Source](https://tianchi.aliyun.com/dataset/109858)                          |
| **Alibaba Clickstream 2018**  | Clickstream data from Alibaba users in 2018.                                                                                                        | [Source](https://tianchi.aliyun.com/dataset/56)                              |
| **Alibaba Cloud Theme**       | Themed dataset related to Alibaba Cloud services or usage.                                                                                          | [Source](https://tianchi.aliyun.com/dataset/9716)                            |
| **Alibaba Ads**               | Advertising-related dataset from Alibaba (distinct from IJCAI-18).                                                                                  | [Source](https://tianchi.aliyun.com/dataset/148347)                          |
| **Alibaba User Behavior 2018**| 649M user interactions (clicks, carts, buys) on 25M items over 9 days (2017), CTR, dwell times. (15 structured columns: user profiles, item positions, predicted metrics). | [Source](https://tianchi.aliyun.com/dataset/649)                             |
| **Alibaba Personalized Re-Ranking** | Mobile shopping user click data on recommended items (30 per instance), item features, user interactions.                                         | [Source](http://yongfeng.me/dataset/)                                         |
| **Online Shopping Intention** | 12,330 user sessions (1 year), 10 numerical (page metrics, bounce/exit rates, page values, special day proximity) & 8 categorical attributes (OS, browser, traffic type, visitor type, weekend flag, revenue). | [Source](https://www.kaggle.com/datasets/henrysue/online-shoppers-intention) |

---

## Search and Ranking

Search engine logs, query-relevance judgments, SERP click models, and CTR prediction datasets.

| Dataset | Description | URL |
|---------|-------------|-----|
| **Rakuten** | E-commerce dataset provided for a SIGIR ecom workshop data task. | [Source](https://sigir-ecom.github.io/ecom2018/data-task.html) |
| **Wayfair Search (WANDS)** | Largest public e-commerce search relevance dataset: 233k human-annotated query-product judgments, 43k products with 40+ attributes (categories, ratings). | [Source](https://github.com/wayfair/WANDS) |
| **Criteo Display Advertising** | Massive display ad dataset (24 daily files, 342GB total): click feedback, 13 integer features, 26 hashed categorical features. | [Source](https://ailab.criteo.com/ressources/) |
| **Avazu** | Dataset for predicting click-through rates (CTR) on mobile ad placements. | [Source](https://www.kaggle.com/competitions/avazu-ctr-prediction/overview) |
| **Yoyi** | Dataset related to computational advertising provided by Yoyi Digital. | [Source](https://apex.sjtu.edu.cn/datasets/7) |
| **Yandex Personalized Web Search** | Large-scale search log dataset with 35M queries from 5.7M users, featuring click-through data and user session information for personalized search ranking. | [Source](https://www.kaggle.com/c/yandex-personalized-web-search-challenge) |
| **Baidu-ULTR** | Largest public SERP dataset: 1.2 billion search sessions with clicks, dwell time, skip behavior, scroll depth, display features (query/document tokens, position, displayed height), and pre-trained BERT embeddings. Expert-annotated subset has 7,008 queries with 397,572 query-doc pairs. Access via WSDM Cup 2023. | [Source](https://github.com/lixsh6/Baidu-ULTR) |
| **TianGong-ST** | 147,155 Sogou search sessions with queries, top-10 SERPs, clicks, query reformulations, timestamps, and labels from 6 click models (TCM, DBN, PSCM, TACM, UBM, CM). Includes 2,000 sessions with human relevance labels and dwell-time data for modeling temporal attention. | [Source](http://www.thuir.cn/tiangong-st/) |

---

## Video Search and Recommendation

User interaction data specifically related to online video platforms.

| Dataset       | Description                                                                                                                                                      | URL                                               |
|---------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------|
| **MicroLens** | Micro-video recommendation dataset with 1 billion interactions from 34 million users on 1 million videos, including raw multimodal data (titles, audio, full videos). | [Source](https://github.com/westlake-repl/MicroLens) |
| **KuaiSAR**   | Unified Search And Recommendation dataset from Kuaishou: 5M search actions, 14.6M recommendation events from 25k users over 19 days (8 interaction types).        | [Source](https://kuaisar.github.io/)              |
| **KuaiRand** | Short-video recommendation dataset from Kuaishou with 12 feedback signals (click, like, follow, comment, forward, hate, long_view, play_time_ms, etc.) and randomly exposed items inserted into normal feeds, enabling off-policy evaluation and causal inference. KuaiRand-27K has 27K+ users and 32M+ interactions. | [Source](https://zenodo.org/records/10439422) |
| **KuaiRec** | Near-fully-observed user-item interaction matrix (99.6% density) for 1,411 users × 3,327 short videos from Kuaishou, with watch ratio, like, follow, click, hate, comment, and forward signals. Unique for counterfactual evaluation due to near-complete observation. | [Source](https://github.com/chongminggao/KuaiRec) |
| **Tenrec** | Tencent recommendation dataset spanning 4 scenarios across 2 feed apps (QK-video, QK-article, QB-video, QB-article) with 5M users and 140M interactions including clicks, likes, shares, follows, reads, watch times, and true negative feedback (exposed but not clicked). | [Source](https://tenrec0.github.io/) |

---

## Video Engagement

Datasets measuring viewer engagement, attention, and emotional response to video content.

---

## News and Media

Datasets related to news consumption, media recommendations, and content engagement.

---

## Product and Reviews

Datasets containing product attributes (images, descriptions) and user reviews, often without user activity logs.

| Dataset                             | Description                                                                                                                                 | URL                                                                          |
|-------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------|
| **Amazon Reviews (2023)**           | Expanded version: 571M reviews (1996-2023), 33 categories, 48M items, 30B metadata tokens, standardized splits for benchmarking LLMs.         | [Source](https://cseweb.ucsd.edu/~jmcauley/datasets.html#amazon_reviews)     |
| **M5Product (Video, Audio, Text)**  | Large multi-modal e-commerce pretraining dataset: 5 modalities (image, text, table, video, audio), 6M+ samples, 6,232 categories, varied completeness. | [Source](https://xiaodongsuper.github.io/M5Product_dataset/index.html)       |
| **Tmall reviews**                   | Collection of product reviews from Tmall, Alibaba's B2C platform.                                                                           | [Source](https://tianchi.aliyun.com/dataset/140281)                          |
| **Home Depot Product Search**       | Product search relevance dataset: real customer search terms, products, human-rated relevance scores (1-3), product descriptions/attributes.   | [Source](https://www.kaggle.com/datasets/thedevastator/the-home-depot-products-dataset) |
| **Innerwear**                       | Data scraped from Victoria's Secret and other innerwear retailers.                                                                          | [Source](https://www.kaggle.com/datasets/PromptCloudHQ/innerwear-data-from-victorias-secret-and-others) |
| **Flipkart products**               | Product information scraped from Flipkart.                                                                                                  | [Source](https://www.kaggle.com/datasets/PromptCloudHQ/flipkart-products)    |
| **Stanford Datasets (Amazon/Beer)** | Collection including Amazon product data/metadata and BeerAdvocate reviews (ratings, text).                                                 | [Source](https://snap.stanford.edu/data/#amazon)                             |
| **Metacritic Video Games**          | Dataset related to video game reviews or metadata from Metacritic, hosted on Tianchi.                                                       | [Source](https://tianchi.aliyun.com/dataset/144719)                          |
| **Goodreads**                       | Datasets containing book information (metadata) and user reviews from Goodreads.                                                            | [Source](https://mengtingwan.github.io/data/goodreads.html#datasets)         |

---

## Sales and Forecasting

Datasets focused on individual or aggregate sales data, primarily for time-series forecasting tasks.

| Dataset             | Description                                                                                                  | URL                                                                                           |
|---------------------|--------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------|
| **Wallmart (M5)**   | Hierarchical sales data (unit sales) for 3,049 products across 10 Walmart stores (CA, TX, WI) used in the M5 forecasting competition. | [Source](https://www.kaggle.com/competitions/m5-forecasting-accuracy/)                         |
| **Ecuador Grocery** | Unit sales data (Corporacion Favorita, Ecuador), store/item metadata (type, cluster, family, perishable), transactions, oil prices, events. Favorita Grocery Sales Forecasting competition. | [Source](https://www.kaggle.com/competitions/favorita-grocery-sales-forecasting/data)          |
| **Ukraine ecommerce** | E-commerce sales data from the Fozzy Group retail chain in Ukraine, used for Hack4Retail competition.      | [Source](https://www.kaggle.com/datasets/picklenik/fozzy-group-hack4retail/data)                |
| **Office Supplies** | Dataset related to office supply sales, used for a data mining workshop challenge (DMDA 2023).               | [Source](https://sites.google.com/view/dmdaworkshop2023/data-challenge)                         |
| **Brazilian Drugs** | Sales data for controlled substances (drugs) in Brazil, reported by ANVISA (National Health Surveillance Agency). | [Source](https://www.kaggle.com/datasets/tiagoacardoso/venda-medicamentos-controlados-anvisa) |
| **Indian Sales**    | Sales forecasting dataset for small basket items in India.                                                   | [Source](https://www.kaggle.com/datasets/girishvutukuri/sales-forecasting-for-small-basket?select=train.csv) |
| **Wallmart Sales**  | General sales data from Walmart stores including features like CPI, unemployment rate.                       | [Source](https://www.kaggle.com/datasets/yogesh174/wallmart-sales/data)                         |
| **Montgomery Liquor**| Warehouse and retail liquor sales data (volume, price) from Montgomery County, MD's Department of Liquor Control. | [Source](https://data.montgomerycountymd.gov/Community-Recreation/Warehouse-and-Retail-Sales/v76h-r7br) |
| **Iowa Liquor**     | Monthly Class E liquor sales data (Iowa): store, county (w/ population), item, volume, price, cost, revenue details. | [Source](https://data.iowa.gov/Sales-Distribution/Iowa-Liquor-Sales/m3tr-qhgy/data)           |
| **Brazil Medical**  | Data on medicine sales in Brazil, potentially including industrialized medicines.                            | [Source](https://www.kaggle.com/datasets/tgomesjuliana/brazil-medicine-sales?select=EDA_Industrializados_202002.csv) |
| **Store Item**      | Demand forecasting dataset tracking sales of 50 items across 10 different stores over 5 years.                 | [Source](https://www.kaggle.com/c/demand-forecasting-kernels-only/)                             |
| **Italian Grocers** | Sales data (receipt-level) from Italian grocery stores for demand pattern analysis.                          | [Source](https://data.mendeley.com/datasets/s8dgbs3rng/1)                                     |

---

## Supermarkets and Grocery

Datasets containing prices and purchases from supermarkets or grocery stores, often with less granular detail.

| Dataset             | Description                                                                                              | URL                                                                                                     |
|---------------------|----------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|
| **Tesco Data**      | Grocery purchase data from Tesco stores, including loyalty card transactions over several months.          | [Source](https://figshare.com/collections/Tesco_Grocery_1_0/4769354)                                     |
| **Rossman Store**   | Historical sales data for 1,115 Rossmann drug stores across Germany, including promotional info and store details. | [Source](https://www.kaggle.com/c/rossmann-store-sales)                                                 |
| **Polish Grocery**  | Yearly sales data (2018) from a grocery shop in Poland.                                                  | [Source](https://www.kaggle.com/datasets/agatii/total-sale-2018-yearly-data-of-grocery-shop/data)      |
| **UK Gift Shop**    | Online retail transactions (2010-2011) from a UK-based non-store gift shop (UCI dataset).                  | [Source](http://archive.ics.uci.edu/dataset/352/online+retail)                                           |
| **Turkish Drugs**   | Drug sales data from Turkey, potentially monthly sales across provinces.                                   | [Source](https://www.kaggle.com/datasets/emrahaydemr/drug-sales-data)                                   |
| **NYC Shopping**    | Large sales dataset, potentially from retail locations in New York City.                                   | [Source](https://www.kaggle.com/datasets/pigment/big-sales-data)                                        |
| **Mexican Grocery** | Data from a grocery store in Mexico.                                                                     | [Source](https://www.kaggle.com/datasets/martinezjosegpe/grocery-store/data)                              |
| **Vietnam Supermarket** | Sales and inventory snapshot data from a supermarket in Vietnam.                                         | [Source](https://www.kaggle.com/datasets/tienanh2003/sales-and-inventory-snapshot-data)                 |
| **Indian Grocery**  | Transaction and product details for grocery items from Flipkart's Supermart.                               | [Source](https://www.kaggle.com/datasets/aryansingh95/flipkart-grocery-transaction-and-product-details?select=fact_sales_apr1.csv) |
| **Instacart (Market Basket)**| 3 million grocery orders from 200k+ Instacart users, detailing products purchased and sequence of orders. (Kaggle competition focus). | [Source](https://www.kaggle.com/competitions/instacart-market-basket-analysis/data)                     |
| **Israeli Grocery** | Grocery purchase data potentially from the Shufersal chain in Israel, possibly scraped product listings. | [Source](https://www.kaggle.com/datasets/arielpazsawicki/kimonaim?select=shufersalist.db)                 |
| **Brazilian store** | Sales data for a chain of stores in Brazil.                                                              | [Source](https://www.kaggle.com/datasets/marcio486/sales-data-for-a-chain-of-brazilian-stores)          |
| **Dominiks Soft drinks** | Weekly scanner data (prices, volume, display/feature ads) focusing on soft drink purchases from Dominick's Finer Foods (Chicago). | [Source](https://www.chicagobooth.edu/research/kilts/research-data/dominicks)                           |
| **Aguirregabiria Supermarket** | Panel of prices, sales, and inventories for 3,742 products in a single supermarket, used for dynamic pricing and inventory management models (Aguirregabiria 1999). | [Source](http://individual.utoronto.ca/vaguirre/data/data.html) |

---

## Financial Transactions

Datasets focusing on banking transactions or financial product purchases.

| Dataset                                       | Description                                                          | URL                                       |
|-----------------------------------------------|----------------------------------------------------------------------|-------------------------------------------|
| **Hashed Multimodal Banking Transactions**    | Dataset containing hashed banking transactions and product purchases. | [Source](https://github.com/dzhambo/mbd) |
| **IEEE-CIS Fraud Detection** | 590K+ payment transactions with identity and device features from the IEEE-CIS Kaggle competition for fraud detection research. | [Source](https://www.kaggle.com/competitions/ieee-fraud-detection) |
| **FDIC Summary of Deposits** | Annual survey of all FDIC-insured branch deposits (1994–present) with branch addresses, GPS coordinates, deposit amounts, and establishment dates. Public domain. | [Source](https://www.fdic.gov/bank-financial-reports/summary-deposits) |

---

## Fashion

Datasets specific to the fashion industry, including products, styles, and user interactions.

---

## Cars and Used Cars

Market-level or transaction data related to new and used automobiles.

---

## Discrete Economic Choices

Datasets used in structural econometric models of discrete decision-making under uncertainty.

---

## Travel

Data related to travel bookings, transactions, delays, and recommendations.

| Dataset           | Description                                                                                         | URL                                                                 |
|-------------------|-----------------------------------------------------------------------------------------------------|---------------------------------------------------------------------|
| **Fliggy Travel** | Travel-related dataset from Fliggy, Alibaba's online travel platform, potentially including bookings or user behavior. | [Source](https://tianchi.aliyun.com/dataset/113649)                 |
| **Fliggy Transfers**| Dataset focusing on transfer-related data within the Fliggy platform, such as connecting flights or ground transport. | [Source](https://tianchi.aliyun.com/dataset/140721)                 |
| **Expedia**       | Hotel booking or search data from Expedia, often used for recommendation or ranking tasks.          | [Source](https://www.kaggle.com/datasets/vijeetnigam26/expedia-hotel) |
| **Trivago Travel**| Dataset released for a RecSys challenge by Trivago, involving user interactions with hotel listings. | [Source](https://recsys.trivago.cloud/challenge/dataset/)           |
| **Airline delay** | Data on airline flight delays, including carriers, origins, destinations, and delay times.         | [Source](https://www.kaggle.com/datasets/sriharshaeedala/airline-delay) |
| **SwissMetro** | Stated preference survey of 1,192 respondents choosing between rail, car, and the hypothetical SwissMetro for intercity travel in Switzerland, a canonical dataset for discrete choice modeling. | [Source](https://biogeme.epfl.ch/data.html) |
| **LPMC (London Passenger Mode Choice)** | Revealed preference dataset of 81K+ trips in London with mode choices (walk, cycle, drive, bus, rail) and detailed trip attributes for transport demand modeling. | [Source](https://biogeme.epfl.ch/data.html) |
| **Chicago TNC Trips** | Publicly released ride-hailing trip records from the City of Chicago, including pickup/dropoff areas, timestamps, fares, and trip durations. | [Source](https://data.cityofchicago.org/Transportation/Transportation-Network-Providers-Trips-2018-2022-/m6dm-c72p) |
| **Uber Movement** | Aggregated travel time and speed data across major global cities, derived from Uber trip data for urban transportation analysis and planning. | [Source](https://movement.uber.com/) |
| **TrajAir** | General aviation trajectory dataset capturing aircraft operations around a non-towered airport, with recorded trajectories and corresponding weather conditions. | [Source](https://theairlab.org/trajair/) |
| **Airline DB1B Tickets** | 10% sample of all US domestic airline tickets (quarterly, 1993–present). Routes, fares, carriers, passengers across Coupon/Market/Ticket tables. Public domain. | [Source](https://www.transtats.bts.gov/Tables.asp?DB_ID=125) |

---

## Music

Datasets focusing on music listening behavior, sales, and reviews.

---

## Procurement and Online Auctions

Data from online auction platforms, public procurement processes, or tender databases.

| Dataset              | Description                                                                           | URL                                                                       |
|----------------------|---------------------------------------------------------------------------------------|---------------------------------------------------------------------------|
| **Online Auctions**  | Collection of datasets related to various online auctions (e.g., eBay, experimental). | [Source](https://www.modelingonlineauctions.com/datasets)                 |
| **Crypto Art**       | Bids and transactions data from the SuperRare crypto art (NFT) platform.              | [Source](https://www.kaggle.com/datasets/franceschet/superrare?select=bids.csv) |
| **Ukraine Procurement**| Public procurement data (tenders, contracts, bidders) from Ukraine's ProZorro system. | [Source](https://www.kaggle.com/datasets/oleksastepaniuk/prozorro-public-procurement-dataset) |
| **Romania Tenders**  | Public tender data from Romania (2007-2016).                                          | [Source](https://www.kaggle.com/datasets/gpreda/public-tenders-romania-20072016) |
| **Art Auction**      | Data from the "Artists for Lahaina" benefit art auction in 2023.                       | [Source](https://www.kaggle.com/datasets/quillen/artists-for-lahaina-2023)  |
| **Used Car Auction** | Listings data from PakWheels, a Pakistani used car marketplace/auction site.          | [Source](https://www.kaggle.com/datasets/asimzahid/pakistans-largest-pakwheels-automobiles-listings) |
| **Bidoo**            | Data from closed penny auctions on the Bidoo platform.                                | [Source](https://www.kaggle.com/datasets/federicominutoli/bidoo-closed-auctions) |
| **FCC Spectrum Auctions** | Round-by-round bid data from 87+ FCC wireless spectrum auctions since 1994, with bidder identities, amounts, and license details. Public domain. | [Source](https://auctiondata.fcc.gov/) |

---

## Display Advertising and Sponsered Search Auctions

Bidding logs and ad clickstream data from online advertising platforms.

| Dataset                 | Description                                                                                              | URL                                                                                                                                               |
|-------------------------|----------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------|
| **Ipinyou**             | Real-time bidding (RTB) dataset from Ipinyou for CTR prediction and advertising research.                  | [Source](http://contest.ipinyou.com/)                                                                                                             |
| **Alibaba**             | Advertising dataset from Alibaba (potentially related to sponsored search or display ads).                 | [Source](https://tianchi.aliyun.com/dataset/148347)                                                                                               |
| **Adform**              | Display advertising dataset (impressions, clicks, auction details) hosted on Harvard Dataverse.            | [Source](https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/TADBY7)                                                          |
| **Tencent**             | Advertising or algorithm competition data from Tencent (e.g., social ad CTR prediction).                   | [Source](https://algo.qq.com/index.html)                                                                                                          |
| **Outbrain**            | Click prediction dataset based on users' browsing history (page views, ad clicks) provided by Outbrain.    | [Source](https://www.kaggle.com/c/outbrain-click-prediction)                                                                                      |
| **Soso**                | Dataset from the KDD Cup 2012 Track 2, focusing on predicting click-through rates for Tencent Soso search ads. | [Source](https://www.kaggle.com/competitions/kddcup2012-track2/overview)                                                                           |
| **Yahoo**               | Advertising and search log datasets available via Yahoo Webscope (e.g., sponsored search clicks, ad impressions). | [Source](https://webscope.sandbox.yahoo.com/catalog.php?datatype=a)                                                                               |
| **Display Advertising** | Real-time advertiser auction dataset, likely containing bid requests and outcomes.                         | [Source](https://www.kaggle.com/datasets/saurav9786/real-time-advertisers-auction)                                                                |
| **ICPSR**               | Search results for auction-related studies within the ICPSR data archive.                                  | [Source](https://www.openicpsr.org/openicpsr/search/studies?start=0&ARCHIVE=openicpsr&sort=score%20desc%2CDATEUPDATED%20desc&rows=25&q=auction) |
| **Replication Data (Harvard)** | Search results for auction-related replication datasets on Harvard Dataverse.                          | [Source](https://dataverse.harvard.edu/dataverse/harvard?q=auction)                                                                             |
| **Multi-Region MMM eCommerce** | Synthetic multi-region marketing mix modeling dataset with channel spend, impressions, and sales outcomes for evaluating media attribution methods. | [Source](https://figshare.com/articles/dataset/Multi-Region_Marketing_Mix_Modeling_MMM_Dataset_for_Several_eCommerce_Brands/25314841) |
| **Criteo Counterfactual Learning** | 25M logged interactions with counterfactual propensity scores for offline policy evaluation and counterfactual reasoning in display advertising. | [Source](https://ailab.criteo.com/dataset-release-evaluation-counterfactual-algorithms/) |

---

## Healthcare

Datasets related to healthcare pricing, provider utilization, and organ allocation.

---

## Logistics

Supply-side data focusing on delivery operations, freight, and supply chain management.

| Dataset             | Description                                                                                                                             | URL                                                                                                          |
|---------------------|-----------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------|
| **MSOM18**          | Logistics or supply chain dataset from the 2018 MSOM Data Driven Research Challenge (Cainiao Last-Mile Delivery, hosted on Tianchi).       | [Source](https://tianchi.aliyun.com/competition/entrance/231623/information)                                 |
| **MSOM20**          | Dataset from the 2020 MSOM Data Driven Research Challenge (JD.com Logistics, focus on e-commerce fulfillment).                             | [Source](https://connect.informs.org/msom/events/datadriven2020)                                             |
| **MSOM21**          | Dataset from the 2021 MSOM Data Driven Research Challenge (Dmall Fresh Food Delivery).                                                  | [Source](https://pubsonline.informs.org/page/msom/data-driven-challenge)                                     |
| **Amazon Last Mile**| 9,184 historical routes (2018) across 5 US metro areas; route, stop, package features; anonymized IDs/locations. From AWS Open Data challenges. | [Source](https://registry.opendata.aws/amazon-last-mile-challenges/)                                         |
| **LaDe Last-Mile Delivery** | 10.6M+ packages, 619k trajectories, 16.7M+ GPS pings (21k couriers) across 5 cities (6 months), pickup/delivery scenarios.      | [Source](https://arxiv.org/html/2306.10675v2)                                                                |
| **DataCo**          | Widely used synthetic supply chain dataset covering sales, orders, shipping, and returns across multiple regions.                         | [Source](https://tianchi.aliyun.com/dataset/89959)                                                           |
| **Drone Delivery**  | Dataset related to drone delivery logistics or operations, possibly route planning or scheduling (hosted on Tianchi).                   | [Source](https://tianchi.aliyun.com/dataset/89726)                                                           |
| **Brewery Operations**| Dataset covering brewery operations (production, inventory) and market analysis (sales, distribution).                                | [Source](https://www.kaggle.com/datasets/ankurnapa/brewery-operations-and-market-analysis-dataset)           |
| **Shipping and Pricing**| Supply chain data focusing on shipment modes, costs, and pricing across different routes and products (provided by DataCo Global). | [Source](https://catalog.data.gov/dataset/supply-chain-shipment-pricing-data-07d29#:~:text=This%20dataset%20provides%20supply%20chain,data%20are%20particularly%20valuable%20for) |
| **Packrift Packaging Optimization Benchmark Corpus** | SKU-specific packaging records and benchmark pages for carton fit, dimensional weight, ecommerce fulfillment, warehouse planning, and packaging optimization examples. | [Source](https://packrift.github.io/packaging-optimization-benchmark-corpus/dataset-metadata.html) |

---

## Taxi and Ride-Hailing GPS

GPS trajectory and trip-record datasets from taxis, ride-hailing platforms, and bike-sharing systems.

| Dataset | Description | URL |
|---------|-------------|-----|
| **Grab Driving GPS Traces** | GPS trace data (latitude, longitude, timestamp, accuracy) from drivers using the Grab ride-hailing platform in Southeast Asia. | [Source](https://engineering.grab.com/grab-posisi) |
| **T-Driver Dataset** | GPS trajectories of 10K+ taxis in Beijing over one week, widely used for urban computing, route planning, and traffic analysis. | [Source](https://www.kaggle.com/datasets/arashnic/tdriver) |
| **Taxi Trajectory Dataset** | GPS trajectory data from taxi trips (e.g., Porto taxis from ECML-PKDD 2015), providing insights into urban mobility patterns and route optimization. | [Source](https://www.kaggle.com/datasets/crailtap/taxi-trajectory/data) |
| **Citi Bike NYC** | Trip-level data from New York City's bike-sharing system including station locations, trip durations, and user types, updated monthly. | [Source](https://citibikenyc.com/system-data) |
| **NYC Yellow Taxi (2009–2013)** | Trip-level records from ~1B+ NYC yellow taxi trips with anonymized but consistent medallion (vehicle) and hack license (driver) IDs, enabling full shift reconstruction. Key fields: pickup/dropoff datetime, fare, tip, tolls, payment type. The only major public dataset for DDC driver labor supply estimation (used by Buchholz, Shum & Xu 2025). | [Source](https://www.nyc.gov/site/tlc/about/tlc-trip-record-data.page) |
| **NYC HVFHV (Uber/Lyft)** | High-volume for-hire vehicle trip records from NYC (Feb 2019–present), ~20M trips/month. Fields include driver_pay, base_passenger_fare, tips, tolls, pickup/dropoff taxi zones. No driver identifier — shift reconstruction is impossible, but useful for earnings analysis and demand modeling. | [Source](https://www.nyc.gov/site/tlc/about/tlc-trip-record-data.page) |
| **DiDi GAIA Chengdu** | Full GPS trajectories with driver_id and order_id for November 2016 in central Chengdu (~65 km²). Used directly in IRL papers: Safarzadeh & Wang (2024) ran personalized route recommendation via IRL on 14.55M DiDi trajectories; Fan et al. applied recursive logit meta-IRL to it. Requires registration. | [Source](https://gaia.didichuxing.com) |
| **Shanghai Taxi (Zhao & Liang 2023)** | GPS traces from 10,609 taxis (April 16–21, 2015) at 10-second sampling intervals. Published adversarial IRL (AIRL) route choice model code and data on GitHub, making it the most directly replicable IRL route choice dataset. | [Source](https://github.com/liangchunyaobing/RCM-AIRL) |
| **San Francisco Cabspotting** | GPS traces from 536 San Francisco taxis over ~30 days (May–June 2008) at sub-10-second sampling. Includes an occupancy flag (1=has fare, 0=vacant) enabling clean trip segmentation without heuristics. Free IEEE DataPort account required. | [Source](https://ieee-dataport.org/open-access/crawdad-epflmobility) |
| **Chicago Taxi Trips** | ~200M taxi trips in Chicago (2013–2023) with timestamps, fares, trip distance, and community-area-level locations. CC BY 4.0. | [Source](https://data.cityofchicago.org/Transportation/Taxi-Trips-2013-2023-/wrvz-psew) |
| **Bay Wheels (Bay Area)** | Monthly trip-level bike-sharing data from the San Francisco Bay Area (2013–present), similar structure to Citi Bike NYC. | [Source](https://www.lyft.com/bikes/bay-wheels/system-data) |

---

## Driving Behavior and Traffic Sensors

Naturalistic driving studies, highway trajectory datasets, autonomous vehicle data, and loop detector traffic sensor feeds.

| Dataset | Description | URL |
|---------|-------------|-----|
| **Natural Driving in Ohio** | Data from vehicles equipped with Advanced Driver Assistance Systems (ADAS) recording naturalistic driving behavior and events. | [Source](https://data.transportation.gov/Automobiles/Advanced-Driver-Assistance-System-ADAS-Equipped-Si/iie8-uenj/about_data) |
| **NGSIM** | Detailed vehicle trajectory data (position, speed, acceleration) from US highways collected for traffic flow modeling. | [Source](https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Vehicle-Trajector/8ect-6jqj/about_data) |
| **HighD Dataset** | Naturalistic vehicle trajectory dataset recorded from German highways using drones, capturing 110K+ vehicles with high positional accuracy for traffic and lane-change analysis. | [Source](https://levelxdata.com/highd-dataset/) |
| **inD Dataset** | Naturalistic trajectory dataset of road users at German intersections captured by drones, including vehicles, bicyclists, and pedestrians with rich interaction data. | [Source](https://levelxdata.com/ind-dataset/) |
| **100-Driver Naturalistic Driving** | Large-scale naturalistic driving study tracking 100 drivers with continuous sensor data (GPS, accelerometers, cameras) capturing real-world driving behavior and safety events. | [Source](https://100-driver.github.io/) |
| **Round Dataset** | Drone-captured vehicle trajectory dataset from roundabouts in Germany for studying yielding behavior and gap acceptance in complex traffic situations. | [Source](https://levelxdata.com/round-dataset/) |
| **PishguVe Dataset** | Vehicle trajectory dataset providing positional data for driving behavior analysis including lane changes, acceleration, and braking in diverse traffic conditions. | [Source](https://github.com/TeCSAR-UNCC/PishguVe) |
| **COMPASS Connected Car** | Connected vehicle telemetry data including GPS traces, speed, and driving events from real-world driving sessions in the UK. | [Source](https://data.cdrc.ac.uk/dataset/compass-connected-car-vehicle-trajectories-and-behaviours) |
| **Ithaca365** | Autonomous driving dataset collected along a 15 km route under diverse weather (snow, rain, sun), times (day/night), and traffic conditions with LiDAR and camera data. | [Source](https://ithaca365.mae.cornell.edu/) |
| **Mobile Century Experiment** | 8 hours of GPS data from 100 vehicles on a 10-mile stretch of I-880 in California, collected to validate mobile phone-based traffic monitoring systems. | [Source](https://github.com/ucbtrans/mcdata) |
| **METR-LA** | Traffic speed readings from 207 loop detectors on Los Angeles County highways (I-10, I-110, I-405, I-5, US-101) at 5-minute intervals, March–June 2012. Introduced in Li et al.'s DCRNN paper (ICLR 2018); HDF5 file of 34,272 timesteps × 207 sensors. | [Source](https://github.com/liyaguang/DCRNN) |
| **PEMS-BAY** | Traffic speed data from 325 sensors across San Francisco Bay Area freeways, January–May 2017, at 5-minute resolution. Companion to METR-LA; same HDF5 format (52,116 timesteps × 325 sensors). Both are curated subsets of Caltrans PeMS. | [Source](https://github.com/liyaguang/DCRNN) |

---

## Human Trajectories

Datasets tracking pedestrian and general human movement patterns across various environments.

---

## Check-in and Location Data

Datasets capturing user check-ins and location-based interactions at venues and points of interest.

---

## Housing and Residential Prices

Data on property assessments, house prices, transactions, or rental bookings.

| Dataset     | Description                                                                                                                                     | URL                                                                                                  |
|-------------|-------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------|
| **AirBnb**  | Global short-term rental listings (6M+), reviews (190M+), pricing, availability calendars, host info, and amenities data compiled by Inside Airbnb. | [Source](http://insideairbnb.com/explore)                                                             |
| **Chicago** | Public data catalog for Cook County, IL, including detailed property assessment values, characteristics, and sales data from the Assessor's Office. | [Source](https://datacatalog.cookcountyil.gov/)                                                      |
| **New York**| NYC Open Data portal, including the Rolling Calendar Sales archive with details on property sales transactions across the five boroughs.          | [Source](https://data.cityofnewyork.us/Housing-Development/NYC-Calendar-Sales-Archive-/uzf5-f8n2/about_data) |

---

## Research Datasets and Collections

Aggregated collections of datasets released by companies or researchers for academic use.

| Collection          | Description                                                                                                                               | URL                                                            |
|---------------------|-------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------|
| **Yahoo**           | Yahoo Webscope program: Diverse datasets including search logs, advertising data, ratings (e.g., music), news clicks, graph data for research. | [Source](https://webscope.sandbox.yahoo.com/)                  |
| **Yelp**            | Dataset including business attributes, millions of reviews, user data, check-ins, tips, and photos from Yelp's platform.                      | [Source](https://www.yelp.com/dataset)                         |
| **Yandex**          | Research datasets released by Yandex, often related to search ranking, translation quality, machine learning tasks, and user behavior.        | [Source](https://research.yandex.com/datasets)                 |
| **Facebook (Meta)** | Research datasets accessible via platforms like the Meta Content Library (1.1B+ public FB/IG posts, engagement metrics, API access) or specific requests. | [Source](https://fort.fb.com/researcher-datasets)              |
| **Microsoft**       | Collection of research tools and datasets released by Microsoft Research across various domains (ML, NLP, vision, systems).               | [Source](https://www.microsoft.com/en-us/research/tools/?)    |
| **Amazon AWS**      | Registry of Open Data on AWS, hosting a wide variety of public datasets across many fields, often analysis-ready.                         | [Source](https://registry.opendata.aws/)                       |
| **Netflix**         | Dataset from the Netflix Prize competition (2006-2009) containing 100M+ anonymous movie ratings from 480k users for 17k movies.           | [Source](https://www.kaggle.com/datasets/netflix-inc/netflix-prize-data) |
| **JD.com**          | Open dataset portal provided by JD.com's data science division, potentially including e-commerce, logistics, or advertising data.           | [Source](https://datascience.jd.com/page/opendataset.html)     |
| **Rakuten**         | Data releases from the Rakuten Institute of Technology, including e-commerce, advertising, and multimedia datasets.                         | [Source](https://rit.rakuten.com/data_release/#access)         |
| **IBM**             | Datasets provided by IBM, often related to AI, data science technologies, healthcare, or weather (e.g., IBM Debater, EHR data).            | [Source](https://developer.ibm.com/technologies/artificial-intelligence/data/) |
| **Baidu**           | Datasets released by Baidu Research, often related to AI, NLP (e.g., DuReader), computer vision, autonomous driving (ApolloScape).         | [Source](https://ai.baidu.com/broad/download)                  |
| **AirBnb (Direct)** | Direct link to download raw data files (listings, reviews, calendar) from the Inside Airbnb project.                                      | [Source](http://insideairbnb.com/get-the-data/)               |
| **Yongfeng**        | Personal collection of datasets curated by Yongfeng Zhang, including e-commerce (JD, Alibaba) and recommendation system data.               | [Source](https://www.yongfeng.me/dataset/)                     |
| **Julian McAuley**  | Collection of datasets curated by Julian McAuley's lab at UCSD, strong focus on reviews (Amazon, Yelp), recommendations, and social network data. | [Source](https://cseweb.ucsd.edu/~jmcauley/datasets.html)      |
| **Makridakis**      | Time series data used in the Makridakis Competitions (M1-M5) for benchmarking forecasting methods across various domains (economic, demographic, industry). | [Source](https://forecasters.org/resources/time-series-data/)  |
| **bayesm R Package Datasets** | Collection of marketing and choice datasets bundled with the bayesm R package, including scanner panel data, conjoint studies, and hierarchical Bayes examples. | [Source](https://cran.r-project.org/package=bayesm) |
| **AMiner DBLP Citation Network** | Large-scale academic citation network with 5M+ papers and 36M+ citation relationships extracted from DBLP, ACM, and MAG for bibliometric and network analysis. | [Source](https://www.aminer.org/citation) |
| **LIAR** | Benchmark dataset of 12.8K short political statements labeled with six fine-grained truthfulness ratings, speaker metadata, and context for fake news and fact-checking research. | [Source](https://huggingface.co/datasets/ucsbnlp/liar) |

---

## Competitions

Platforms and conferences hosting data science competitions, often providing unique datasets.

| Platform / Event   | Description                                                                                                       | URL                                                      |
|--------------------|-------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------|
| **RecSys Datasets**| Collection of datasets used in the ACM Recommender Systems (RecSys) conference challenges over the years.           | [Source](https://github.com/RUCAIBox/RecSysDatasets)     |
| **NIPS (NeurIPS)** | Top-tier conference on Neural Information Processing Systems, often featuring competitions and benchmark datasets tracks. | [Source](https://nips.cc/)                               |
| **ICJAI**          | International Joint Conference on Artificial Intelligence, hosting various AI competitions and associated datasets. | [Source](https://www.ijcai.org/)                         |
| **MSOM**           | Manufacturing & Service Operations Management society, hosting annual Data Driven Research Challenges with unique industry datasets. | [Source](https://pubsonline.informs.org/journal/msom)    |
| **Data Mining Cups**| Competitions focused on data mining tasks, often sponsored by industry partners.                                    | [Source](https://www.data-mining-cup.com/reviews/)       |
| **KDD Cup**        | Prestigious annual data mining and knowledge discovery competition associated with the ACM SIGKDD conference.       | [Source](https://kdd.org/kdd-cup)                        |
| **Marketing Science**| INFORMS Marketing Science conference/journal, sometimes featuring datasets or data-focused competitions.          | [Source](https://pubsonline.informs.org/page/mksc/online-databases) |
| **Driven Data**    | Platform hosting data science competitions focused on social impact challenges using real-world data.               | [Source](https://www.drivendata.org/)                    |
| **Coda Labs**      | Open-source platform for running data science competitions, benchmarks, and reproducible research.                | [Source](https://codalab.lisn.upsaclay.fr/)              |
| **Open ML**        | Online platform for democratizing machine learning: sharing datasets, tasks, code, and experimental results.      | [Source](https://www.openml.org/)                        |

---

## Gaming

Datasets capturing player behavior, strategy, and engagement in digital games and sports analytics.

---

## Others

Miscellaneous datasets or categories.

*To add a dataset email me.*

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