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tags: TuringDataStories
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# Turing Ethics Advisory Group practice application form

## I. BACKGROUND INFORMATION AND SCOPING

Is The Alan Turing Institute the lead institution for this research?
- Yes 

Are you the principal investigator/research lead?
- Yes 

### 1. Project Goal and Purpose

Turing Data Stories, is an open and community driven project with the goal to inspire the community to harness the potential of open data by creating data stories (see our first story [here](https://alan-turing-institute.github.io/TuringDataStories-fastpages/covid-19/data%20wrangling/data%20exploration/2020/11/20/Who_was_protected_by_the_first_COVID-19_lockdown.html)).

The Turing Data Stories are detailed and pedagogic Jupyter notebooks that document an interesting insight or result using real world data.

The notebooks of a data story take the reader through each step of the analysis done to create the data story results. Turing Data Stories have the following characteristics:

- The story should be told in a pedagogical way, describing both the context of the story and the methods used in the analysis.
- The analysis must be fully reproducible (the notebooks should be able to be ran by others using a defined computer environment).
- The results should be transparent, all data sources are correctly referred to and included.
- In order to maintain the quality of the results, the Turing Data Story should be peer-reviewed by other contributors before published.
- We don't expect sophisticated analyses, just insteresting stories told with data. If you have an idea of a Turing Data Story you want to develop please follow our contributing guidelines to make sure your contributions can be easily integrated in the project.

To ensure stories follow this description, we employ a peer review process. Following discussions with the Turing Ethics Advisory Group, we are requesting an ethical review on this review process itself.

The main output of the Turing Data Stories project is educational content that provides clear and interesting examples of the data science process.

We hope that by using the story telling medium, we can bring people along the data science journey and showcase how these techniques can help us explore both fascinating and socially relevant questions. Furthermore, we hope that the content will spark curiosity and motivate more people to play with data.

The Turing Data Stories stories are published on a central platform managed by the project. This platform is the centre of the TDS community and can a be a place where:

- Data scientists/enthusiasts publish that one analysis they did in their spare time, driven by curiosity on a subject or dataset.
- People who wants to upskill in data science topics, learn new methods or get new ideas.
- Data curious persons can get inspired or entertained by socially relevant content.

Finally, Turing Data Stories community can be the place where person with domain knowledge but not technical skills, connect with technically minded folks to collaborate on a data story based on an initial idea.

### 2. Data and Research Methods Description

Describe our review/approval process:

- We expect users to use open data and provide clear provenance.
- Peer review on the content of the story
- Ethical peer review

As our project will produce many independently written stories produced by various people and using many sources of open data, it is not possible to conduct a single ethical review now for the entire project. Instead, we we have designed and implemented an ethical peer review process that will be carried out on a per story basis. As mentioned previously, we are requesting an ethical review on this review process itself.

The Turing Data Stories ethical review process is designed to ensure that the stories produced our project adhere to our [ethical framework, code of conduct](https://github.com/alan-turing-institute/TuringDataStories/blob/master/CODE_OF_CONDUCT.md) and [contributing guidelines](https://github.com/alan-turing-institute/TuringDataStories/blob/master/CONTRIBUTING.md), including the [SUM values](https://www.gov.uk/guidance/understanding-artificial-intelligence-ethics-and-safety), developed at the Turing. These have been directly shaped by our expereince being mentored by the Open Life Science-2 (OLS-2) programme and influenced heavily by the best practices of The Turing Way project.

Our submission process consists of two stages of review. The first is a self-review by story authors upon the proposal of a new story idea. This is designed to ensure authors know what to expect when writing their story and reinforces the positives of responsible research and communication. The second is a peer review process that happens just before story publication.

The guidelines for submiting and reviewing a Turing Data Story are described [here](https://github.com/alan-turing-institute/TuringDataStories/blob/master/SUBMISSION_REVIEW_GUIDELINE.md). We welcome any input from the EAG on this document, as part of the current Turing ethical approval process.

These guidelines are designed to ensure that the authors and the reviewers of the stories reflect on the ethical implications of the outputs produced and stories are only published if the meet all the exaustive review criteria.

## II. Please answer the questions in the following section which will enable the EAG to assess the ethical implication of your research.

*Consent*
### 3. Please comment on any issues around securing consent raised by your research.

Our ethical review process has three requirements around the data that is in use and/or linked:
- Any data used are open and have an explicit licence, provenance and attribution.
- Any data used are not personal data (i.e. the data is anonymous or anonymised).
- Is any linkage of datasets in story unlikely to lead to an increased risk of the personal identification of individuals?

Given these requirements, we do not expect there to be any issues around consent and the use of personal data, as personal data will not be collected.

*Privacy and Security*
### 4. Please comment on any issues of privacy and security raised by your research.

Our ethical review process has three requirements around the data that is in use and/or linked:
- Any data used are open and have an explicit licence, provenance and attribution.
- Any data used are not personal data (i.e. the data is anonymous or anonymised).
- Is any linkage of datasets in story unlikely to lead to an increased risk of the personal identification of individuals?

Given these requirements, we do not expect there to be any issues around consent and the use of personal data, as it will not be happening. There is no requirement to keep data secure, as stories will be based upon openly published data and the stories themselves are destined to be openly published.

*Other Harms*
### 5. Please comment on the potential for individual, societal or ecological harms to arise from your research, beyond what is described above.

Our ethical review process has two requirements that are designed to prevent our project creating societal harms:
- The Story must be truthful and clear about any limitations of analysis (and potential biases in data).
- The Story will not lead to negative individual, societal or ecological outcomes, such as (but not limited to) increasing discrimination, injustice or providing a platform for damaging speech or views towards others.

There may be some (proposed) story topics which those involved (submitting, reviewing etc.) may find triggering. We would not wish anybody to work on content they do not wish to do so, and encourage them to step back.

Our Code of Conduct explains the community values we uphold, making the community and spaces we manage as safe as possible. It is still possible for the author of a story to recieve negative or attacking comments from readers of their story, for example on Twitter. While we achnowledge this as a possibility for a negative individual outcome, our story review process should prevent stories being published that inspire toxicity. We do not, therefore, expect this be a common occurence.

Furthermore, as per our contributing guidelines, contributors can retract their stories from our public platform at any point.

*Attach additional information here.*

We include our [Code of conduct](https://github.com/alan-turing-institute/TuringDataStories/blob/master/CODE_OF_CONDUCT.md) and [contributing guidelines](https://github.com/alan-turing-institute/TuringDataStories/blob/master/CONTRIBUTING.md) and [Story Review guidelines](https://github.com/alan-turing-institute/TuringDataStories/blob/master/SUBMISSION_REVIEW_GUIDELINE.md) as supporting material to this application.

## III. FINAL DECLARATIONS

In light of the risks that you have identified in this application, do you think the level of safeguards you have implemented in your research plan sufficiently mitigate ethical risks?
- Yes

In light of the risks you have identified and the level of detail about the project that you have provided in this application, do you think reviewers have sufficient information to judge whether your planned project offers sufficient safeguards?
- Yes