bacardi-prov-model
A reference implementation for the BACARDI PROV data model.
Science Score: 85.0%
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✓CITATION.cff file
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✓codemeta.json file
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✓DOI references
Found 2 DOI reference(s) in README -
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Organization dlr-sc has institutional domain (www.dlr.de) -
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Low similarity (15.9%) to scientific vocabulary
Keywords
Repository
A reference implementation for the BACARDI PROV data model.
Basic Info
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- Stars: 2
- Watchers: 4
- Forks: 0
- Open Issues: 0
- Releases: 2
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Metadata Files
README.md
Welcome to the BACARDI PROV Data Model! 👋
A reference implementation for the BACARDI PROV Data Model.
️🏗️ ️Installation
Clone the project and install using pip from the project root directory:
bash
pip install .
⚡ Getting started
The BACARDI PROV data model has been designed according to W3C PROV specification. The reference implementation uses the Python library prov.
Task Model
Currently, only the task model is defined and documented in docs/task.md.
It specifies how provenance of a task in BACARDI must be recorded according to the W3C PROV standard.
The reference implementation can be found in the task module.
🚀 Execute Examples
Once installed, the example scripts can be executed on the command line.
All scripts create a directory example-output in the current working directory and generate their content into it.
You can execute the scripts as follows:
```sh
Generates provenance bundle using the extended task model
task-bundle
Generates provenance bundle using the simplified task model
simple-task-bundle
Generates two provenance bundles using the simplified task model
multi-task-bundle ```
✨ How to cite
If you use the BACARDI PROV data model in a scientific publication, we would appreciate citing the following paper:
- M. Stoffers, M. Meinel, B. Hofmann and A. Schreiber, "Integrating Provenance-Awareness into the Space Debris Processing System BACARDI," 2022 IEEE Aerospace Conference (AERO), 2022, pp. 1-12, doi: 10.1109/AERO53065.2022.9843783.
Bibtex entry:
BibTeX
@INPROCEEDINGS{9843783,
author={Stoffers, Martin and Meinel, Michael and Hofmann, Benjamin and Schreiber, Andreas},
booktitle={2022 IEEE Aerospace Conference (AERO)},
title={Integrating Provenance-Awareness into the Space Debris Processing System BACARDI},
year={2022},
volume={},
number={},
pages={1-12},
doi={10.1109/AERO53065.2022.9843783}
}
You can also cite specific releases published on Zenodo:
✏️ References
Papers that refer to the BACARDI PROV Data Model:
- Stoffers, Martin and Meinel, Michael and Hofmann, Benjamin and Fiedler, Hauke (2022) A use case study on provenance-based data assessments for mission critical software systems. In: 73rd International Astronautical Congress (IAC 2022). 73rd International Astronautical Congress (IAC 2022), 18.-22. Sep. 2022, Paris, France. (In Press)
📝 License
Please see the file LICENSE.md for further information about how the content is licensed.
Owner
- Name: DLR Institute for Software Technology
- Login: DLR-SC
- Kind: organization
- Email: opensource@dlr.de
- Location: Cologne, Berlin, Braunschweig, Oberpfaffenhofen, Bremen
- Website: http://www.dlr.de/sc
- Twitter: DLR_software
- Repositories: 62
- Profile: https://github.com/DLR-SC
German Aerospace Center (DLR)
Citation (CITATION.cff)
cff-version: 1.2.0
title: BACARDI PROV Models
message: >-
If you use the BACARDI PROV model in your research, please
cite it using these metadata.
type: software
authors:
- given-names: Martin
family-names: Stoffers
email: martin.stoffers@dlr.de
affiliation: German Aerospace Center (DLR)
orcid: 'https://orcid.org/0000-0003-2987-4345'
identifiers:
- type: doi
value: 10.5281/zenodo.7554678
repository-code: 'https://github.com/DLR-SC/bacardi-prov-model'
abstract: |
A reference implementation for the BACARDI PROV models.
keywords:
- provenance
- w3c-prov
- provenance model
license: MIT
version: 1.0.0
date-released: '2023-01-20'
references:
- authors:
- given-names: Martin
family-names: Stoffers
email: martin.stoffers@dlr.de
affiliation: German Aerospace Center (DLR)
orcid: 'https://orcid.org/0000-0003-2987-4345'
- given-names: Michael
family-names: Meinel
email: michael.meinel@dlr.de
affiliation: German Aerospace Center (DLR)
orcid: 'https://orcid.org/0000-0001-6372-3853'
- given-names: Benjamin
family-names: Hofmann
email: benjamin.hofmann@dlr.de
affiliation: German Aerospace Center (DLR)
- family-names: Schreiber
given-names: Andreas
affiliation: German Aerospace Center (DLR)
orcid: 'https://orcid.org/0000-0001-5750-5649'
title: >-
Integrating Provenance-Awareness into the Space Debris Processing System
BACARDI
type: conference-paper
conference:
name: 2022 IEEE Aerospace Conference (AERO)
year: 2022
pages: 1-12
doi: 10.1109/AERO53065.2022.9843783
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| Name | Commits | |
|---|---|---|
| Martin Stoffers | m****s@d****e | 2 |
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