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WiD Hackathon

Working website to code and solve problem for women's safety using data. The data will be hosted in the Snowflake environment. The data will be anonymous and will be used solely for the purpose of the hack.

In partnership with Women in Data, UK, non-profit and Impactic Volunteers

impact volenteers wid-logo.png

Hackathon Title: EmpowerHer: WiD - Women's Safety Hackathon

Date and Time:

Start Date: 10am Thursday, March 7th 2024

End Date: 4.30pm Thursday, March 7th 2024

Duration: 6.5 hours

Venue:

  • In-person event
  • InterContinental London - the O2

Registration:

  • Sign up through women in data website
  • 3,000 people for flagship conference, 400 people at the hackathon

5 data roles for people to select when signing up to conference

  • Data Analyst - DA
  • Data Scientist - DS
  • Data Engineer - DE
  • Data SME - DSME
  • Data Product Owner - DPO

Agenda:

Registration 8am Opening Ceremony 9am Hackathon Start 10am Hackathon Finish 4:30am

Team Formation

  • Teams of up 10 people max
  • 1 DPO, 1 DSME, 3 DA, 2 DE, 3 DS

Hacking Period

  • 10am to 4.30pm
  • Lunchtime checkpoint for help and support

Safety Data Requirements

Using the safety survey data, propose exploring the following six categories:

  1. Public Crimes Data: Crimes reported by the police or the MET, broken down by region.

  2. Public Services Data: Data related to travel services and public amenities like hospitals and police stations, broken down by region.

  3. Tribunal Data on Workplace Grievances: Data on public court cases related to workplace grievances.

  4. Public Court Cases on Other Crimes: Data on public court cases related to crimes other than workplace grievances.

  5. Mumsnet Chat Data: Mumsnet is a popular online platform based in the UK that serves as a community and discussion forum for parents.

  6. Socio-demographic and Household Information: Information on socio-demographics and households, broken down by region.

More Metrics data at postcode level and The Ark's data at household level could complement the raw data we have. They can provide aggregated datasets at a higher geographic level.

Key Information from More Metrics - More Metrics Documentation: More Metrics Documentation - The Ark's Household Data: The Ark Household Data - Free Samples on Snowflake: - More Metrics: More Metrics on Snowflake - The Ark: The Ark on Snowflake

The demographic information includes household income, individual income differentiated by sex and age, self-reported health, disability, smoking, obesity, attitudinal indices, and the Index of Multiple Deprivation.

Tasks: Participants are encouraged to:

  1. Explore Datasets: Utilize datasets that pertain to women's safety. This could include information on demographics, medical records, disease prevalence, treatment outcomes, etc.
  2. Analyze and Visualize: Analyze the data to identify trends, patterns, and potential areas for improvement in women's safety. Visualize key insights to better understand the data.
  3. Develop Solutions: Propose innovative solutions, which could be in the form of applications, predictive models, educational tools, or any other technological advancement that addresses specific challenges in women's safety.
  4. Pitch and Demonstrate: Present the findings and developed solutions to a panel of judges, explaining the rationale, methodology, and potential impact of the proposed solution.

Tools and Resources: Participants are encouraged to use open-source tools, libraries, and technologies for data analysis, such as Python (Pandas, NumPy), R, Jupyter Notebooks, machine learning libraries (scikit-learn, TensorFlow), visualization tools (Matplotlib, Seaborn, GeoPandas), and any other open-source resources available.

Note: This hackathon aims to create a collaborative environment where participants can learn, innovate, and contribute to a meaningful cause in women's safety. The aim of the hackathon is not to be a competition but a supportive and caring environment working on sensitive data that can be triggering.