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www.openup.org.za

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SANEF Elections Data Training

April 2024

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Backbone of open data

Who is OpenUp?

  • Government
  • Journalism
  • Civil Society

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Elections stories are data stories

Tuning up your spreadsheets

You can’t tell the story of an election without looking at the data.

  • Turnout
  • Votes cast
  • Seats won
  • Area demographics & themes
  • Swing! https://www.youtube.com/watch?v=2CBB0_EoCWk

Journalists need accurate, reliable and accessible data

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The Parliament Chart even has its own name: The easiest way to visualise the make-up of any assembly (this is the current National Assembly).

https://bit.ly/sa_parly_chart

https://bit.ly/sa_prov_2019

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Elections Dashboard�

Working with SANEF

https://bit.ly/sanef_elections_dash

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How to navigate the Dashboard

See it in action

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Current view level (click to go up a level)

Click in the map to zoom in

Search by place name (note changed names may not appear)

These three icons switch between the primary view types: region maps, point maps, and contextual rich data

In Data Mapper and Point Data views, you can select the indicators shown here

Expand this box to see more information about the current indicator (including source)

Electoral boundaries change over time, you can choose historical ones here

In the Rich Data view, you can download chart data by clicking here

There is a lot of data in the Rich Data view, and it can be quite overwhelming. You can move quickly between charts using this menu.

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What data do we have

Looking deeper

Independent Election Commission

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What questions might we ask of elections data at this stage of the campaign?

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Some questions we might ask of elections data now

  • Which voting areas had the highest/lowest registration/turnout at the last national elections?
  • And at the last municipals?
  • Same questions for registered voters as % of eligible population…
  • Which voting areas saw the highest proportion of votes cast for the governing party?
  • Which voting area has the highest population of voters (and the lowest)?
  • Which provincial governments have the best outcomes/least worst AG reports and how did people vote there?
  • How did the youngest area vote? And the eldest? (based on age of registered voters)

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What scale can the questions be answered at? National - Provincial - Local�Each requires different techniques

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National

https://bit.ly/elections_2019_data

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Where is there high voter registration?

Start with a question

  • Is it different to historical activity?
  • Are there specific local issues �motivating people?
  • Is it because of party activity during registration or fraud?
  • What do odd numbers mean (eg. more than 100%)?
  • We’ll be posting these kinds of questions to the SANEF site

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Data stories in Port St Johns

Local questions

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Mine other resources for stories

Don’t limit yourself to one data point!

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The candidate lists?

What can we tell from…

  • How does the election work?
  • Who is fielding the most candidates?
  • Who is fielding repeat candidates?
  • Who is fielding the oldest/youngest candidate?

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Does it matter?

Not just a bit of fun

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Tabula and PDF table extraction

How did we do that?

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Making data accessible

Why the SANEF portal?

  • Historical snapshots
  • Merged with other data
  • Rich data and point data
  • Linked to other projects…

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More data projects you should try…

Take a look

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How not to do it

A final thought

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Any questions?

adam@openup.org.za

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