Building a strong data culture

In this section:

 

The proactive and systemic sharing and release of usable and up-to-date government data can have far reaching community, social and economic benefits, and can enable government to deliver better services.

To make data sharing and release systematic, agencies should adopt the following best practices:

Agency leadership should:

  • Have strong, explicit and ongoing data commitment from all levels of leadership
  • Support and enable agency data sharing and open data release
  • Build data use and analytics into organisational strategies
  • Include data activities on business unit plans
  • Build data metrics and goals into corporate plans and into public reporting
  • Resource and monitor data programs
  • Build progress on data into corporate reporting
  • Encourage data skills and awareness across all levels in the organisation

Agency policy should:                                                

  • Openly commit to regularly and routinely sharing datasets and updates, or to the creation of APIs for high value and frequently updated datasets.
  • Ensure any relevant tenders include reference to data and enable data to be owned, used and shared released as a BAU component of business or project delivery.
  • When providing grants to any public or private sector organisations, include requirements to share and publish data as part of the service delivery agreement.
  • Build streamlined data extract, ‘privacy by design’ and ‘open data by default’ into business processes and system reviews, as well as procurement, outsourcing or service arrangements.

Agency culture and collaboration should:

  • Encourage data champions and sharing their knowledge across the organisation
  • Allow agency communication and social media channels to engage with the community and industry, to identify open data needs
  • Share stories of how agency data is being utilised by the community, industry and government sector
  • Actively encourage staff to identify data that should be shared and released
  • Actively encourage the sharing of data and knowledge internally
  • Conduct privacy training for all parties working with data, including decision-makers
  • Encourage staff to think about how they generate, store and use information internally, and how data processes can be streamlined to improve data minimisation and ease of data release
  • Encourage feedback from users of corporate data to help improve and maintain data quality and act on this feedback
  • Engage with other agencies and industries to share experiences, ideas and lessons learned
  • Communicate and share identified risks and mitigation strategies with other agencies
  • Work to increase engagement with the community about data

Agency operational processes should:

  • Establish routine data sharing and release
  • Routinely assess datasets during their life-cycle to manage sensitive information
  • Apply data minimisation principles to business processes that involve the capture and management of personally identified data. Data minimisation approaches enable you to only collect, use, retain, and disclose the personal information necessary to achieve your specified goals or purposes
  • Identify data that should not be released as open data, and data that needs to be  de-identified prior to publication
  • Develop appropriate de-identification and de-sensitisation processes for data planned for sharing or open data release, and ensure anonymisation and de-sensitisation performed and validated by trained personnel.
  • Define a privacy breach response protocol
  • Improve data governance processes and identify and monitor processes or systems where governance may need to be improved
  • Start using standards, common identifiers, standard classifications or terms in datasets to foster alignment with other datasets across government
  • Routinely adopt applicable open standards
  • Monitor the evolving data landscape to identify emerging risks and opportunities
  • Routinely release high quality metadata and documentation for all datasets
  • Develop procedures that streamline the approval and release of data
  • Apply creative commons licensing (default CC-BY) to facilitate the reuse of open data
  • Regularly monitor data programs to ensure they are managing all risks, and meeting community needs

Last updated: 19 June 2019