2023
DOI: 10.21105/joss.05198
|View full text |Cite
|
Sign up to set email alerts
|

unfold: removing the barriers to sharing and reproducing prospective life-cycle assessment databases

Abstract: unfold is a Python package that allows reproducing life-cycle databases which partially build on a data source that cannot be shared. It produces data packages that contain the differences between the databases to share and the licensed data source. The data package also includes a metadata file describing the databases, the author, and other helpful information. unfold allows one to pack and unpack any databases from a single data package to ease the sharing and reproducibility of prospective or scenario-base… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
1
1

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 10 publications
0
1
0
Order By: Relevance
“…Recently, other Python packages such as pycirk [11,12], and pyLCAIO [13] have also been developed to enable modeling of Circular Economy scenarios and streamline the hybridization of process-based Life Cycle Assessment and Environmentally Extended IO databases. Recently, unfold was released, a repository that improves the packaging and sharing of data, making it easier to reproduce life-cycle databases that are based on proprietary data sources [14].…”
Section: Open Science and Open-source Software In Industrial Ecologymentioning
confidence: 99%
“…Recently, other Python packages such as pycirk [11,12], and pyLCAIO [13] have also been developed to enable modeling of Circular Economy scenarios and streamline the hybridization of process-based Life Cycle Assessment and Environmentally Extended IO databases. Recently, unfold was released, a repository that improves the packaging and sharing of data, making it easier to reproduce life-cycle databases that are based on proprietary data sources [14].…”
Section: Open Science and Open-source Software In Industrial Ecologymentioning
confidence: 99%