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Material intensity database for research on infrastructure systems

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Material intensity database project 💾

🔥 🆕 New version 1.2 released (November 2023):

  • Now over 900 datapoints
  • Cleaned and revised data
  • Standardized descriptor label attributes for SSP regions, building functions, and structural construction types

🚨 The Dataset Descriptor article has been released: https://www.nature.com/articles/s41597-019-0021-x

Welcome to the Material Intensity Research Database!

This database contains data on material intensity of buildings, but can be extended for further infrastructure in the future. The initial database version was assembled (seeded) by Heeren and Fishman (2019). The publication provides some analysis of the data and discusses a number of applications for the database.

Content

Contributing

Data contributions, and further extensions to the database are very much encouraged. The more data is contained in the MIR-DB, the more meaningful analysis and can be made with it.

New data

In case you know of a potential data source, but do not want to provide the data yourself, please consider creating an issue and leaving a link to the dataset, or send me an email.

Please see CONTRIBUTING.md for more info on how to contribute data. We encourage the use of the liberated_data project if you are extracting data from non-portable, such as figures or tables in PDF files.

Database structure

For proposing new database attributes or changes to existing ones, please create an issue and propose a new codebook. Please keep in mind that the goal of this project is to provide a comprehensive and complete database. The database contains primary and secondary attributes and the former are required. See the codebook for more details.

Errors

In case you find errors in the data, please correct them (as described in CONTRIBUTING.md), create an issue, or contact me.

Citation

Please cite the following article when using the data: Heeren and Fishman. A Database Seed for a Community-Driven Material Intensity Research Platform. Scientific Data. 2019. https://doi.org/10.1038/s41597-019-0021-x.

Acknowledgements

👍 The following people supported the compilation of the original database accompanying the publication: