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metadata 
license: apache-2.0
task_categories:
  - other
tags:
  - poi-recommendation
  - trajectory-prediction
  - human-mobility
dataset_info:
  - config_name: default
    features:
      - name: user_id
        dtype: string
      - name: trail_id
        dtype: string
      - name: inputs
        dtype: string
      - name: targets
        dtype: string
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        num_examples: 27639
      - name: validation
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        num_examples: 3949
      - name: test
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        num_examples: 7897
    download_size: 4642768
    dataset_size: 17382226
  - config_name: tabular
    features:
      - name: trail_id
        dtype: string
      - name: user_id
        dtype: int64
      - name: venue_id
        dtype: int64
      - name: latitude
        dtype: float64
      - name: longitude
        dtype: float64
      - name: name
        dtype: string
      - name: address
        dtype: string
      - name: venue_category
        dtype: string
      - name: venue_category_id
        dtype: string
      - name: venue_category_id_code
        dtype: int64
      - name: venue_city
        dtype: string
      - name: venue_city_latitude
        dtype: float64
      - name: venue_city_longitude
        dtype: float64
      - name: venue_country
        dtype: string
      - name: timestamp
        dtype: string
    splits:
      - name: train
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        num_examples: 74113
      - name: validation
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      - name: test
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    dataset_size: 23067250
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
      - split: test
        path: data/test-*
  - config_name: tabular
    data_files:
      - split: train
        path: tabular/train-*
      - split: validation
        path: tabular/validation-*
      - split: test
        path: tabular/test-*

Massive-STEPS-Moscow

huggingface huggingface arXiv GitHub

Dataset Summary

Massive-STEPS is a large-scale dataset of semantic trajectories intended for understanding POI check-ins. The dataset is derived from the Semantic Trails Dataset and Foursquare Open Source Places, and includes check-in data from 15 cities across 10 countries. The dataset is designed to facilitate research in various domains, including trajectory prediction, POI recommendation, and urban modeling. Massive-STEPS emphasizes the importance of geographical diversity, scale, semantic richness, and reproducibility in trajectory datasets.

City URL
Bandung 🇮🇩 🤗
Beijing 🇨🇳 🤗
Istanbul 🇹🇷 🤗
Jakarta 🇮🇩 🤗
Kuwait City 🇰🇼 🤗
Melbourne 🇦🇺 🤗
Moscow 🇷🇺 🤗
New York 🇺🇸 🤗
Palembang 🇮🇩 🤗
Petaling Jaya 🇲🇾 🤗
São Paulo 🇧🇷 🤗
Shanghai 🇨🇳 🤗
Sydney 🇦🇺 🤗
Tangerang 🇮🇩 🤗
Tokyo 🇯🇵 🤗

Dataset Sources

The dataset is derived from two sources:

  1. Semantic Trails Dataset:
    • Repository: D2KLab/semantic-trails
    • Paper: Monti, D., Palumbo, E., Rizzo, G., Troncy, R., Ehrhart, T., & Morisio, M. (2018). Semantic trails of city explorations: How do we live a city. arXiv preprint arXiv:1812.04367.
  2. Foursquare Open Source Places:

Dataset Structure 

.
├── moscow_checkins_test.csv # test set check-ins
├── moscow_checkins_train.csv # train set check-ins
├── moscow_checkins_validation.csv # validation set check-ins
├── moscow_checkins.csv # all check-ins
├── data # trajectory prompts
│   ├── test-00000-of-00001.parquet
│   ├── train-00000-of-00001.parquet
│   └── validation-00000-of-00001.parquet
└── README.md

Data Instances

An example of entries in moscow_checkins.csv:

trail_id,user_id,venue_id,latitude,longitude,name,address,venue_category,venue_category_id,venue_category_id_code,venue_city,venue_city_latitude,venue_city_longitude,venue_country,timestamp
2013_1668,42,43,55.757967,37.619001,metro Teatralnaya (Метро Театральная),"ул. Большая Дмитровка, 2",Metro Station,4bf58dd8d48988d1fd931735,292,Moscow,55.75222,37.61556,RU,2012-04-13 04:06:00
2013_1668,42,1008,55.76487541978725,37.604403271547,metro Tverskaya (Метро Тверская),Пушкинская пл.,Metro Station,4bf58dd8d48988d1fd931735,292,Moscow,55.75222,37.61556,RU,2012-04-13 15:11:00
2013_1671,42,285,55.749941351119865,37.593326568603516,Арбат / Arbat Street,ул. Арбат,Road,4bf58dd8d48988d1f9931735,284,Moscow,55.75222,37.61556,RU,2012-04-19 04:12:00
2013_1671,42,1173,55.7822156278378,37.705470977149474,metro Elektrozavodskaya (Метро Электрозаводская),Большая Семёновская ул.,Metro Station,4bf58dd8d48988d1fd931735,292,Bogorodskoye,55.81353,37.71617,RU,2012-04-19 05:45:00
2013_1672,42,217,55.763928,37.606379,Тверская улица,Тверская ул.,Road,4bf58dd8d48988d1f9931735,284,Moscow,55.75222,37.61556,RU,2012-04-20 11:16:00

Data Fields

Field Description
trail_id Numeric identifier of trail
user_id Numeric identifier of user
venue_id Numeric identifier of POI venue
latitude Latitude of POI venue
longitude Longitude of POI venue
name POI/business name
address Street address of POI venue
venue_category POI category name
venue_category_id Foursquare Category ID
venue_category_id_code Numeric identifier of category
venue_city Administrative region name
venue_city_latitude Latitude of administrative region
venue_city_longitude Longitude of administrative region
venue_country Country code
timestamp Check-in timestamp

Dataset Statistics

City Users Trails POIs Check-ins #train #val #test
Moscow 🇷🇺 3,993 39,485 17,822 105,620 27,639 3,949 7,897

Additional Information

License 

Copyright 2024 Foursquare Labs, Inc. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License.
You may obtain a copy of the License at: http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and limitations under the License.

🔖 Citation

If you find this repository useful for your research, please consider citing our paper:

@misc{wongso2025massivestepsmassivesemantictrajectories,
  title         = {Massive-STEPS: Massive Semantic Trajectories for Understanding POI Check-ins -- Dataset and Benchmarks},
  author        = {Wilson Wongso and Hao Xue and Flora D. Salim},
  year          = {2025},
  eprint        = {2505.11239},
  archiveprefix = {arXiv},
  primaryclass  = {cs.LG},
  url           = {https://arxiv.org/abs/2505.11239}
}

Contact

If you have any questions or suggestions, feel free to contact Wilson at w.wongso(at)unsw(dot)edu(dot)au.