Managing the Challenges to Open Data
- 1. Open Data Challenges Paul Stone, NZ Open Government Data Programme, Data Leadership and Capability, Stats NZ. IPANZ Conference 2019
- 2. Quality Some data is better than no data… 1. Good context • Purpose of collection • Method of collection • Known strengths and weaknesses 2. Opportunity for feedback 3. Creative Commons Licence Image: Quality by Nick Youngson CC BY-SA 3.0 Alpha Stock Images
- 3. Creative Commons Licence – not liable for quality THE LICENSOR OFFERS THE LICENSED MATERIAL AS-IS AND AS-AVAILABLE, AND MAKES NO REPRESENTATIONS OR WARRANTIES OF ANY KIND CONCERNING THE LICENSED MATERIAL… THIS INCLUDES… FITNESS FOR A PARTICULAR PURPOSE…
- 4. Creative Commons Licence – not liable for reuse (misuse) …IN NO EVENT WILL THE LICENSOR BE LIABLE TO YOU ON …DAMAGES ARISING OUT OF THIS PUBLIC LICENSE OR USE OF THE LICENSED MATERIAL…
- 5. Accurac y • Context – inform how data is collected and for what purpose. • Be upfront about limitations in the data or risk of human error • Create a feedback loop - invite data users to contribute and help lift the accuracy of the data
- 6. Ignorant misuse Context, context, context. • Describe the collection method and purpose • Describe well the variables in the data and what they mean • Don’t assume everyone is ignorant.
- 7. Malicious misuse Don’t let one bad potential use prevent the opportunity for many good uses - Aforementioned clause on liability in CC licence.
- 8. Reputation • Transparency builds trust • Good context reduces misunderstanding • An opportunity to contribute to data quality is an opportunity to engage and build relationships All good reasons to release the data – with good context.
- 9. Lack of resources • Open by design • Prioritise o Alignment to organisational strategy o demand • Don’t re-invent the wheel • Start small
- 10. Lack of technology • Keep it simple • Start small • Every agency has a website • Most agencies have API capability but just don’t use it
- 11. Privacy Critical for maintaining trust. Toolbox: • Privacy Impact Assessment • Confidentialisation • Reference Scenarios (coming)
- 12. Culture Probably the biggest challenge. Shifting the mindset of the whole organisation to open by default. Challenges are manageable, not insurmountable
- 13. Doesn’t AI make too much data dangerous?
- 14. Data considerations Provenance and context Indigenous Data Sovereignty Data EthicsData Bias Licensing attribution Don’t spray and walk away…