data-hazards
Data Hazards is a project to find a shared vocabulary for talking about worst-case scenarios of data science - and to use that vocabulary to help people understand and avoid Data Hazards.
Science Score: 54.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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✓Academic publication links
Links to: zenodo.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (13.0%) to scientific vocabulary
Keywords
Repository
Data Hazards is a project to find a shared vocabulary for talking about worst-case scenarios of data science - and to use that vocabulary to help people understand and avoid Data Hazards.
Basic Info
- Host: GitHub
- Owner: very-good-science
- License: other
- Language: HTML
- Default Branch: main
- Homepage: https://datahazards.com
- Size: 110 MB
Statistics
- Stars: 36
- Watchers: 4
- Forks: 17
- Open Issues: 46
- Releases: 2
Topics
Metadata Files
README.md
Data Hazards Project
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Data Ethics Club and the Jean Golding Institute are working with interdisciplinary researchers to create the Data Hazards Project. Please see the project website for the most up-to-date information.
Aims
We are creating resources to help interdisciplinary researchers and citizens consider the worse-case scenarios of data science work together, and for these ethical concerns to be embedded in the research. For a full list of our aims and strategies to achieve them, please see our website.
Re-using our materials
We really welcome people re-using the materials we have made! This repository is licensed under a CC-BY 4.0 license. This translates to: yes, please do use, remix, and share anything you find in this repo, but you must credit us with attribution (a link to this repo is okay!).
If you'd like to work with us to use these materials in a new context, please do get in touch.
Contact us
The Data Hazards Project was founded by Dr Natalie Zelenka and Dr Nina Di Cara, and is now co-led by Dr Huw Day, Dr Will Chapman, Natalie, and Nina. We’re always keen to hear from people interested in the project, or wanting to get involved!
Huw and Will both work at the Jean Golding Institute at the University of Bristol are interested in hearing from (primarily Bristol based) collaborators. Will (will.chapman@bristol.ac.uk) is the person to talk to about applying and using the Data Hazards labels in research. Huw (huw.day@bristol.ac.uk) is the person to talk to about applying and using the Data Hazards in teaching (e.g. getting students to consider the ethical implications of data science applications using the hazards labels as a framework). Nina (nina.dicara@bristol.ac.uk) now works in industry but remains an honorary researcher at the University of Bristol and is happy to chat with people interested in extending the Data Hazards into new application areas or giving advice on future research using them.
Contributors
We use the all-contributors specification to celebrate all kinds of contributions to this project. Emoji key here!
If you'd like to join us as a contributor, check out our contributor's guide for ways to get involved.
Owner
- Name: Very Good Science
- Login: very-good-science
- Kind: organization
- Repositories: 3
- Profile: https://github.com/very-good-science
Citation (CITATION.cff)
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: Data Hazards
message: >-
If you use the materials or ideas from this
repository, please cite it using the following
metadata.
type: software
authors:
- family-names: Zelenka
given-names: Natalie
email: natalie.zelenka@bristol.ac.uk
orcid: 'https://orcid.org/0000-0002-1007-0286'
- given-names: Nina H.
family-names: Di Cara
email: ninadicara@protonmail.com
orcid: 'https://orcid.org/0000-0002-6179-1067'
repository-code: 'https://github.com/very-good-science/data-hazards'
url: 'https://very-good-science.github.io/data-hazards/'
abstract: >-
Data Hazards is a project to find a shared
vocabulary for talking about worst-case scenarios
of data science - and to use that vocabulary to
help people understand and avoid Data Hazards.
keywords:
- ethics
- data science
- data ethics
- responsible innovation
license: CC-BY-4.0
version: '1.0'
GitHub Events
Total
- Issues event: 4
- Watch event: 3
- Delete event: 1
- Issue comment event: 1
- Push event: 16
- Pull request event: 4
- Fork event: 1
- Create event: 2
Last Year
- Issues event: 4
- Watch event: 3
- Delete event: 1
- Issue comment event: 1
- Push event: 16
- Pull request event: 4
- Fork event: 1
- Create event: 2
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 2
- Total pull requests: 1
- Average time to close issues: N/A
- Average time to close pull requests: less than a minute
- Total issue authors: 2
- Total pull request authors: 1
- Average comments per issue: 0.0
- Average comments per pull request: 0.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 2
- Pull requests: 1
- Average time to close issues: N/A
- Average time to close pull requests: less than a minute
- Issue authors: 2
- Pull request authors: 1
- Average comments per issue: 0.0
- Average comments per pull request: 0.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- ninadicara (16)
- NatalieZelenka (11)
- HuwWDay (3)
- Lextuga007 (2)
- Susana465 (1)
- cthoyt (1)
Pull Request Authors
- ninadicara (3)
- allcontributors[bot] (3)
- harrietrs (2)
- dsmukilan (1)
- OliverDavis (1)
- HuwWDay (1)
Top Labels
Issue Labels
Pull Request Labels
Dependencies
- myst-nb *
- pydata-sphinx-theme *
- sphinx *
- sphinx-panels *