Key lessons on access and usage of data for local authorities

A number of key lessons have been identified to ensure that data for local energy projects is accurate, appropriate, and can be efficiently obtained.

Define your goals early.
Understand your data sources.
Start with ready-to-use data.
Ensure data quality and reliability.
Prioritise stakeholder engagement for fast and effective decision-making.

Define your goals

Clearly define goals and objectives.

Answer the “why?” – Why is a particular project needed and why is it important?
Work with stakeholders to define and agree goals and data needs.

Understand what data and the scope of data is needed to help achieve goals.

Does the data align with the goals and objectives?
Do you need data to present the current and potential future scenarios to get buy-in and keep things moving forward?
Do you need data that is a one-time snapshot, or do you need data that’s refreshed on an on-going basis? For example, to measure progress or impact over time.
Do you have access to your own data to combine with commercial data?

Example

You may be looking at ways to decarbonise your vehicle fleet by moving to electric vehicles (EVs). To support this, you may need to increase the number of accessible EV charge points for your fleet. You need to understand where your buildings are, the capacity of the local electricity network, existing public charge point locations, and potential sites suitable for off-street parking or hubs. Can potential sites serve multiple purposes, i.e. the local authority fleets, as well as public charging?

Understand your data sources

Understand the distinctions and applications of open, commercial, and owned data as a single dataset, which can belong to one or multiple of these types:

Open – As outlined in the Open Data Handbook, users can utilise, redistribute, and often modify open data without any licensing fees. Open data has a focus on non-personal data, but considerations should be made when layering data and how this could be used to identify individuals.
Shared (commercial) – Access involves licensing agreements, and users may be required to pay fees for usage rights and should therefore consider what the licence means with respect to what they intend to do with the data.
Shared (restricted) – Access is restricted, and usage may require explicit permission from the data owner or rights holder. For example, you may only be permitted to use data in a specific way or within a specific scope.
Closed – Access is typically governed by your organisation, for example your existing assets, which may include specific usage restrictions such as being able to use it for specific projects.

Ensure data quality and reliability

Differentiate between inferred and dynamic data for informed decisions.

Inferred data is derived or estimated rather than directly measured. When using inferred datasets, look for indications in the dataset documentation that certain values are inferred. Common inferred data includes estimated values, interpolated data, or predictions, which are often necessary due to more detailed data not existing.
Dynamic data is subject to change over time. Assess whether the dataset incorporates dynamic elements, such as real-time updates or periodic refreshes. Determine what this update period is so you know when to expect new data to be available or use an API (Application Programming Interface) to automate this. This is crucial for keeping information current and tracking the impact of interventions or projects over time.

Reach out to data providers for clarification.

They can provide information on whether specific variables are inferred or dynamic and offer insights into the frequency of updates.

Ensure data accuracy and relevancy throughout the project lifecycle.

Verify the origins and accuracy of source data, and ensure sources are trusted and reputable.
- Has data come from providers with relevant experience in the Net Zero domain?
- Has data been used in similar project types and used by other local authorities?
Verify that datasets adopt a common standard such as the UPRN (Unique Property Reference Number). Standardised data formats and structure simplify integration with existing systems and other data sources.
Ensure data units are known and are aligned, e.g. energy KW vs KWh.

Start with ready-to-use data

If the data that drives decisions is of poor quality, difficult to make use of, and is not actionable, it can affect decision-making in time, resource, and confidence. Ready-to-use data can be best described as data that doesn’t need resource- or time-intensive curation to access and use to make decisions. This doesn’t exclude the potential need to merge multiple datasets to build up a more detailed picture to support decision-making.

There are a number of options to obtain ready to use data:

"DIY" – using open data combined with pre-existing datasets within your organisation.
Use custom-made or commissioned datasets that are procured against a specification.
Use trusted data providers.

	Advantages	Barriers
Option 1 – "DIY" – open data. Use open datasets from open data portals.	Free to obtain and use. Available in several formats. Compatible with many GIS tools.	Data may need to be sourced from multiple sources/locations. There may be a lack of standardisation and consistency with other datasets. “Latest and greatest” is not guaranteed as data needs to be maintained and regularly updated. It’s common for open data to stop receiving updates. Data can be withdrawn without notice. Open data requires some level of funding/investment to ensure it’s maintained and remains open. If the investment can’t sustain development, the data can be removed from the open market. Data needs to be downloaded and potentially cleaned whenever there’s an update. This requires resources to collate, process, and validate the data.
Option 2 – Custom-made/commissioned datasets. Use a specialist consultancy to create the required datasets for you.	Made to measure for your project needs/requirements, i.e. you get what you ask for. Available in your required format. Compatibility with your internal tools if specified correctly.	Expensive – Consultants charge high fees to produce each dataset manually and additional fees will be chargeable if the scope of requirements change. Out of date – The data is a snapshot in time and soon becomes out of date and unusable in future when performing re-analysis or repurposing. Untested – Methodologies are isolated and there is limited opportunity to improve them through shared learning and testing. Black box – The data is often delivered without an audit trail which makes understanding where the source data came from impossible.
Option 3 – Use trusted data providers. Use a trusted data provider to ensure the accuracy, consistency, and lifecycle of the data.	Cost-effective. Simple purchase journey. Multiple formats ensuring compatibility with common tools. Standardisation across all datasets (schemas, fields, e.g. UPRN). Datasets have been used and therefore validated in the real-world. Documented methodologies and sources. Regular updates and maintenance.	Data might be limited to a specific region. Datasets could be tailored to specific use cases making wider usage difficult. Support/assistance might not be available.

Engage with your data stakeholders

Ensure data is treated as an asset and used effectively within your local authority to support decision-making. It is therefore important to ensure stakeholders are aligned on recommendations and decisions made with respect to data that’s needed and used to drive projects forward and to define the purpose of the data beyond project delivery.

Secure buy-in and understand needs at all levels, both technical and non-technical.
Identify key stakeholders impacted by your data needs – these might include representatives from the GIS team, energy department, local community, business leaders, and decision-makers.
Collaborate for the validation of locational information.
Conduct workshops to align and empower stakeholders on project goals, priorities, and outcomes so they understand the implications of different locational strategies.
Highlight the impact of action versus inaction for effective stakeholder engagement.
Clearly articulate the consequences of taking action vs not taking action on Net Zero initiatives, specifically projects identified. Demonstrate the potential benefits of achieving Net Zero goals and the risks associated with maintaining the status quo.