mlsanityData to 7 Oct 2026

BTS: Building Timeseries Dataset: Empowering Large-Scale Building Analytics

arXiv 2406.08990 ↗First posted 13 Jun 2024cs.LGcited by 5

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Abstract (arXiv)

Buildings play a crucial role in human well-being, influencing occupant comfort, health, and safety. Additionally, they contribute significantly to global energy consumption, accounting for one-third of total energy usage, and carbon emissions. Optimizing building performance presents a vital opportunity to combat climate change and promote human flourishing. However, research in building analytics has been hampered by the lack of accessible, available, and comprehensive real-world datasets on multiple building operations. In this paper, we introduce the Building TimeSeries (BTS) dataset. Our dataset covers three buildings over a three-year period, comprising more than ten thousand timeseries data points with hundreds of unique ontologies. Moreover, the metadata is standardized using the Brick schema. To demonstrate the utility of this dataset, we performed benchmarks on two tasks: timeseries ontology classification and zero-shot forecasting. These tasks represent an essential initial step in addressing challenges related to interoperability in building analytics. Access to the dataset and the code used for benchmarking are available here: https://github.com/cruiseresearchgroup/DIEF_BTS .

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 22 of its 96 references that are in the map. First posted on arXiv 13 Jun 2024.

Builds on

22 of 96 references.

References · 22

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10 more
  1. 2022Beyond Just Vision: A Review on Self-Supervised Representation Learning on Multimodal and Temporal Datacited by 27
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 1; 2026: 3.

5 papers.

  1. 2025Can Time-Series Foundation Models Perform Building Energy Management Tasks?cited by 2
  2. 2024Exploring Capabilities of Time Series Foundation Models in Building Analyticscited by 1
  3. 2026RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Modelscited by 1
  4. 2026TopoBrick: Agentic Topology Sampling of Exogenous Variables for Zero-Shot Building IoT Forecastingcited by 0
  5. 2026BTS-AgentBench: A Deterministic, Replayable Pipeline from Read-Only Telemetry Logs to Agent Benchmarkscited by 0