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A new decade and new emerging approaches to evolving geospatial data infrastructures across government

Making data easier not harder to work with

In my last blog post in December 2019 I talked about how 1Spatial’s solutions for government geospatial data infrastructures can make data easier, not harder, to work with by data collaboration, automation, transformation and visualisation capabilities across your geospatial estate. Solve each problem in a way that makes solving the next problem easier.

The emerging role; Chief Data Officers

In a new decade championing making data easier to use is the emerging role of Chief Data Officer’s (CDO) across government. The role of CDO’s is evolving and gaining significant traction. CDO’s are the voice of data within an organisation and represent data as a strategic enterprise asset. At the start of a new decade the success of CDO’s is imperative to driving growth and innovation for government organisations using data. As the rate of digitalisation increases, organisations are looking at CDO’s to lead the evolution of geospatial data infrastructures.

Evolving data strategies

Underpinning data infrastructures are data strategies, helping organisations to clarify the primary purposes of their data and guiding organisations with strategic data management. In a new decade CDO’s must make considered trade-off’s between traditional defensive (controlling) data strategies and emerging needs for progressive offensive (flexible) data strategies.

Defensive and offensive approaches

Every government organisation needs both defensive and offensive approaches to managing geospatial data infrastructures but getting the balance right is tricky in support of an organisations overall strategy. Decisions about trade-offs between defensive and offensive approaches are rooted in the fundamental dichotomy between standardising geospatial data and keeping it more flexible. The more uniform data is, the easier it becomes to execute defensive approaches, such as complying with legislation or policy requirements and implementing data-access controls. The more flexible data is, the more readily it can be transformed or interpreted to meet specific business needs—the more useful it is in offense. In a new decade balancing defence and offence requires balancing data control and data flexibility.

The growth of DataOps

DataOps is an automated and process led approach used by data teams to improve the use of data as information through better data quality, shorter cycle time and effective data management. DataOps applies to the entire data lifecycle from data preparation to reporting. DataOps promotes collaboration, orchestration, quality, security, access and ease of use. In a new decade DataOps approaches will be critical to evolving geospatial data infrastructures across government.

Experiences across government

In the last decade 1Spatial has experienced many government organisations developing highly centralised, control-oriented approaches to geospatial data infrastructures. These approaches have been effective for standardising enterprise geospatial data, governing structured data formats for connecting geospatial data with the business processes that consume it. However, changing demands and expectations for data mean that these approaches could restrict flexibility, making it harder to customise data or transform data into information. In a new decade 1Spatial think that government organisations will need to adopt more flexible DataOps approaches to geospatial data infrastructures, governing processes and rules that convert data into useful information. This will mean involving both a single source of truth (SSOT) and multiple versions of the truth (MVOTs). SSOT works at the data level, whilst MVOTs support the management of information.

Working with government organisations in a new decade

A sound data strategy requires that the geospatial data contained in an organisations SSOT geospatial data infrastructure is of high quality, granular, and standardised, and that multiple versions of the truth (MVOTs) are carefully controlled and derived from the same SSOT. 1Spatial is working with different government organisations to continually improve their DataOps defensive and robust SSOT approaches and develop new offensive and flexible MVOT approaches for geospatial data infrastructures through data collaboration, data automation, data orchestration, data transformation and data visualisation.

The trade-off between both defensive and emerging offensive DataOps approaches to evolving geospatial data infrastructures by government organisations will grow in the next decade.

How is your organisation adopting new approaches to evolving geospatial data infrastructures?

Author Matthew White, 1Spatial   

Get in touch, if you would like to discuss this further with our government team or take a look at upcoming events we are attending.