What problem does it solve? AEC researchers often struggle to find credible open datasets, benchmarks, and the right software tools for their studies, and frequently forget to cite software and data properly, undermining reproducibility. ## Core Features & Use Cases - Domain-organized tool reference: Covers building energy simulation (EnergyPlus, OpenStudio, Modelica), BIM/IFC tooling (IfcOpenShell, Speckle), computer vision and point-cloud benchmarks (S3DIS, ScanNet, SODA), structural FEM (OpenSees, CalculiX), computational design (Grasshopper, Dynamo, COMPAS), and statistics/qualitative software (R, SmartPLS, NVivo). - Dataset and benchmark guidance: Points to open datasets such as the Building Data Genome Project, ASHRAE Great Energy Predictor III, and SHM benchmarks, while flagging license and availability caveats. - Citation and reproducibility practices: Reminds users to cite software versions and DOIs, report dataset provenance and splits, and pin versions for reproducible pipelines. - Use Case: A PhD student designing an energy prediction study asks which dataset and simulation tool to use; the Skill recommends the Building Data Genome Project with EnergyPlus via eppy, and explains how to cite both. ## Quick Start Ask which open dataset and simulation tool to use for a study on building energy benchmarking, and how to cite them in the paper.
