Scientific Machine Learning for Structural Engineering Repository (SciML4StructEng_Repository)

We maintain data sets from structural engineering as a service to the enable and foster scientific machine learning and its community. All data sets through our searchable interface. For a general overview of the Repository, please visit our About page. For information about citing data sets in publications, please read our citation policy. If you wish to donate a data set, please consult our donation policy. For any other questions, feel free to contact the Repository librarians.

Background and Motivation

The SciML4StructEng_Repository is a collection of databases from civil structural engineering to be used by the scientific machine learning community for the empirical analysis of machine and deep learning algorithms. The archive was created in 2022 by M.Sc. Andreas Müller, M.Sc. Sophia Kuhn and Dr. Michael A. Kraus at ETH Zurich.

Many people deserve thanks for making the repository a success. Foremost among them are the donors and creators of the databases and data generators.

Citation

If you publish material based on databases obtained from this repository, then, in your acknowledgements, please note the assistance you received by using this repository. This will help others to obtain the same data sets and replicate your experiments. We suggest the following pseudo-APA reference format for referring to this repository:

Müller, A. and Kuhn, S. and Kraus, M. (2022). Scientific Machine Learning for Structural Engineering Repository (SciML4StructEng_Repository) [https://sciml4structeng.github.io/Repository/]. Zurich, CH: ETH Zurich, D-BAUG.

Here is a BiBTeX citation as well:

@misc{MullerKuhnKraus_SciML_2022,
author = "M\"uller, Andreas and Kuhn, S. and Kraus, Michael",
year = "2022",
title = "Scientific Machine Learning for Structural Engineering Repository (SciML4StructEng_Repository)",
url = "https://sciml4structeng.github.io/Repository/",
institution = "ETH Zurich"}

Some data sets have additional citation requests, which can be found on the bottom of each data set’s page.

Data Set Donation

Thank you for considering donating a dataset to the SciML4StructEng_Repository! Through donating a dataset, you are helping keep scientific machine learning and civil structural engineering a vital research area.

Before donating a dataset, please read the IMPORTANT information below:

  1. You must have explicit permission to make the dataset publicly available. If you are not the original dataset collector, the original dataset collector should be aware that you are donating the dataset to UCI and provide their consent.
  2. If your dataset contains Personally Identifiable Information (PII), this information should be removed prior to donation, such that no individuals can be identified through your dataset.
  3. Datasets approved to be in the repository will be assigned a Digital Object Identifier (DOI) if they do not already possess one. DOIs allow for “persistent and actionable identification” of datasets, which is an important component of reproducible research. For more information on DOIs, please read more in the DOI Handbook.
  4. Datasets will be licensed under a Creative Commons Attribution 4.0 International license (CC BY 4.0) which allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given (see Citation Policy). For more information on the CC BY 4.0 license, please read more in the license deed.

For questions, please email one of the contacts.

Contact

M.Sc. Andreas Müller Institut für Baustatik und Konstruktion (IBK) ETH Zürich andreas.mueller@ibk.baug.ethz.ch https://taras.ibk.ethz.ch/de/personen/wissenschaftliche-mitarbeitende/andreas-mueller.html

M.Sc. Sophia Kuhn Institut für Baustatik und Konstruktion (IBK) Design++ Initiative ETH Zürich sophia.kuhn@ibk.baug.ethz.ch https://kaufmann.ibk.ethz.ch/de/personen/mitarbeitende/sophia-kuhn.html

Dr. Michael A. Kraus, M.Sc.(hons) Institut für Baustatik und Konstruktion (IBK) Design++ Initiative ETH Zürich kraus@ibk.baug.ethz.ch https://kaufmann.ibk.ethz.ch/de/personen/mitarbeitende/dr-michael-anton-kraus.html

The MIT License (MIT) Copyright (c) 2022, Michael Kraus

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.