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Building a Strong Data Culture

In this section, we outline the key pillars to supporting a strong data culture within NSW Government. 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 enables government to deliver better services. 

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

Agency Leadership

  • Have strong, explicit and ongoing data commitment from all levels 
  • 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 public reporting 
  • Resource and monitor data programs 
  • Build progress on data into corporate reporting 
  • Encourage data skills and awareness across all levels of the organisation 

Agency Policy

  • Openly commit to 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, shared and released
  • When providing grants, 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

  • Encourage data champions and the sharing of knowledge
  • 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 
  • 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 data users of to help improve and maintain data quality
  • Engage with other agencies and industries to share experiences, ideas and lessons learned 

Agency Operational Processes

  • 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 personal data, so as to only collect, use, retain, and disclose the information necessary to achieve your specified goal
  • 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 these processes are performed and validated by trained personnel
  • Define a privacy breach response protocol 
  • Monitor processes and systems and make improvements to governance as required
  • Start using standards, common identifiers, and standard classifications or terms in datasets to foster alignment with other datasets across government 
  • Adopt applicable open standards 
  • Monitor the evolving data landscape to identify emerging risks and opportunities 
  • 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