Massive-STEPS-Sydney

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:
   • Repository: foursquare/fsq-os-places
   • Documentation: Foursquare Open Source Places

Dataset Structure

.
├── sydney_checkins_test.csv # test set check-ins
├── sydney_checkins_train.csv # train set check-ins
├── sydney_checkins_validation.csv # validation set check-ins
├── sydney_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 sydney_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_1140,26,3353,-33.88408179250253,151.2067973613739,Platforms 16 & 17,Central Station,Platform,4f4531504b9074f6e4fb0102,336,Haymarket,-33.87868,151.20526,AU,2012-04-19 00:05:00
2013_1140,26,4812,-33.79804527395917,151.1809942132529,Platform 2,Railway St,Train Station,4bf58dd8d48988d129951735,73,Chatswood,-33.8,151.18333,AU,2012-04-19 06:28:00
2013_1141,26,3862,,,,,Home (private),4bf58dd8d48988d103941735,6,Sydney,-33.86785,151.20732,AU,2012-05-13 03:31:00
2013_1141,26,266,-33.87521272869442,151.20667290492102,eVent Cinemas,505-525 George St,Multiplex,4bf58dd8d48988d180941735,151,Haymarket,-33.87868,151.20526,AU,2012-05-13 05:06:00
2013_1142,26,901,-33.92147853346653,151.2268477675372,Kingsford Chinese Restaurant,426 Anzac Pde,Chinese Restaurant,4bf58dd8d48988d145941735,99,Kingsford,-33.92399,151.22749,AU,2012-06-03 03:59:00

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
Sydney 🇦🇺	740	10,148	8,986	29,900	7,103	1,015	2,030

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.