BTS: Building Timeseries Dataset
Summary
BTS is a real-world irregular building-telemetry dataset from three anonymized non-residential Australian buildings. It combines 14,547 time series and about 2.864 billion timestamp-value observations with Brick 1.2.1 semantic graphs of equipment, locations, points, and relationships.
Official Artifacts
- Full raw data: https://doi.org/10.6084/m9.figshare.28705559
- Repository and documentation: https://github.com/cruiseresearchgroup/DIEF_BTS
- NeurIPS 2024 paper: https://proceedings.neurips.cc/paper_files/paper/2024/hash/f0430903a14db90e5ce96f101902d6d7-Abstract-Datasets_and_Benchmarks_Track.html
- OpenReview: https://openreview.net/forum?id=6cCFK69vJI
- Brick by Brick competition archive: https://doi.org/10.6084/m9.figshare.28720391
- Dataset metadata snapshot: bts-2024
Dataset Shape
BTS stores each stream as timestamps plus numeric values, associates it with a StreamID, and links that identifier to per-building CSV metadata and RDF/Turtle Brick graphs. The channel inventory includes sensors, setpoints, commands, statuses, alarms, parameters, equipment, and locations. Raw timestamps are irregular; published benchmark pipelines resample them.
Role In The Wiki
BTS is a strong public substrate for:
- cross-building channel and ontology transfer;
- graph-conditioned time-series modeling;
- high-channel irregular telemetry;
- long-tail and imbalance studies;
- testing whether semantic channel context improves forecasting and representation learning.
It is a passive near-miss for action-conditioned world models. Command and Setpoint classes are control-input-like, but the release does not establish an aligned action/execution/outcome interface.
Infrastructure Assessment
The surrounding ecosystem is unusually valuable: CSIRO Data Clearing House ingestion and semantic modeling, versioned Figshare releases, inspection notebooks, benchmark code, a concluded AIcrowd challenge, a permanent competition archive, published winning solutions, and a separate FlexTrack follow-on challenge.
The GitHub repository itself is an archival research bundle rather than a maintained installable benchmark package. Reproductions should pin the exact Git commit, Figshare version, ontology, split, preprocessing, environment, and metric.
Relation To Foundation TSFM Agenda
Use the source-level agenda mapping in bts-2024 rather than duplicating verdict rows here.
At the entity level, BTS is most valuable as a benchmark substrate for typed channel context, graph structure, irregular time, cross-system transfer, and long-tail telemetry. The missing step is to use those artifacts in a model interface that handles changing channel inventories and, eventually, validated control inputs and outcomes.