Fault data scarcity in HVAC fault detection: systematic review data and code

Data, protocols, checking files and the grading script behind the systematic review Fault data scarcity in HVAC fault detection: a critical review of transfer learning, synthetic data and foundation models by Raimo Simson, Karl-Villem Võsa, Martin Kiil and Jarek Kurnitski (Tallinn University of Technology, 2026). Contents: the supplementary material of the review (Supplementary_material.pdf with the text supplements, Supplementary_data.xlsx with the tables); the tables as CSV, JSON and Markdown (the extraction table, every screened record and its decision, the PRISMA counts, the evidence tables, the evidence grades and the references of the included studies); the search, screening and extraction protocols; the checking files (the extraction check of 30 studies and the records of the Semantic Scholar search); and the Python script that rebuilds the evidence grades from the extraction table. See README.md. Not included: the full texts of the reviewed studies (publishers' copyright; each record carries its DOI) and abstracts that may not be redistributed. The screened-records table keeps an abstract only where it was deposited with Crossref or is held by OpenAlex. Licence: data, documentation and text CC BY 4.0; code MIT, as stated in LICENSE.md. Funding: Estonian Research Council grants TEM-TA227 and PRG2154; the Estonian Centre of Excellence in Energy Efficiency, ENER (grant TK230), funded by the Estonian Ministry of Education and Research; the research infrastructure "Energy efficiency and renewable energy research infrastructure" funded by the Estonian Research Council (TARISTU24-TK12).