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Kind Data Science, with Emma Prest from DataKind – 29m Kind Data Science, with Emma Prest from DataKind – 29m
Bio Emma handles the day-to-day operations of DataKind UK, supporting the influx of volunteers and building understanding about what data science can do in... Kind Data Science, with Emma Prest from DataKind – 29m

Bio

Emma handles the day-to-day operations of DataKind UK, supporting the influx of volunteers and building understanding about what data science can do in the charitable sector. Emma sits on the Editorial Advisory Committee at the Bureau of Investigative Journalism. She was previously a programme coordinator at Tactical Tech, providing hands-on help for activists using data in evidence-based campaigns. Emma holds an MA in Public Policy with a specialism in Media, Information & Communications from Central European University in Hungary and a degree in Politics and Geography from the University of Edinburgh, Scotland.

Summary

How data science can be used for good. From charities, third sector, NGOs, social enterprises, public policies, transparency, accountability, global issues. Not only big companies for profit can benefit from data analysis; there are projects, people, and organizations driven to use data to improve people’s lives.

Objectives

  • Let the data science community know about this type of efforts and that they can make a difference.
  • To encourage participation of Data Scientists to work pro bono/ad honorem in this problems.
  • To encourage companies to fund events like hackathons or datathons.

Timeline

  • 0:40 – What is DataKind and what DataKind does?
  • 1:53 – What types of organizations DataKind works with?
  • 3:30 – How many people and organizations is or has been involved with DataKind?
  • 4:47 – How can people get involved with DataKindUK?
  • 6:15 – Who runs the long-term projects at DataKindUK?
  • 6:56 – How charities and organizations can get in touch to work with DataKindUK?
  • 7:29 – Examples of projects done by DataKind.
  • 9:57 – What are the required skills to work with DataKind?
  • 10:59 – What are the key factors for a successful data science project with the third sector?
  • 12:30 – How is the following up of the projects?
  • 14:33 – How Data Science projects have evolved along the years?
  • 15:36 – What is the future of Data Science for Social Good?
  • 17:29 – What is required to involve more people to work on Data Science for Social Good?
  • 18:50 – What would be useful to change in the processes of Data Science for Social Good.
  • 20:33 – What are the sectors of the organizations DataKindUK works with?
  • 22:22 – Is DataKindUK working with charities outside the UK?
  • 23:08 – Comments around the hype of data science and artificial intelligence.
  • 24:31 – Comments on the data maturity model for the social sector.
  • 25:45 – What are some recommended changes to social organizations around data?
  • 27:07 – The one word to define Emma’s job.
  • 27:56 – Closing words.

©ODSC2017

Diego Arenas

Diego Arenas, ODSC

I've worked in BI, DWH, and Data Mining. MSc in Data Science. Experience in multiple BI and Data Science tools always thinking how to solve information needs and add value to organisations from the data available. Experience with Business Objects, Pentaho, Informatica Power Center, SSAS, SSIS, SSRS, MS SQL Server from 2000 to 2017, and other DBMS, Tableau, Hadoop, Python, R, SQL. Predicting modelling. My interest are in Information Systems, Data Modeling, Predictive and Descriptive Analysis, Machine Learning, Data Visualization, Open Data. Specialties: Data modeling, data warehousing, data mining, performance management, business intelligence.

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