Considerations when choosing data sources for energy projects - Net Zero Go
Resource

Considerations when choosing data sources for energy projects

A list of factors to consider when choosing what data sources to use for your energy projects. These considerations can ensure the quality, accuracy, and suitability of the data you decide to use.

Checklist

Provided by: Net Zero Data

This resource is part of a collection

Print Email Share URL LinkedIn

Topics

Finding, gathering, and using data Managing data

In order for you to use data, you need confidence in the accuracy and validity of the data for the scope you have chosen. There are a number of things you should consider.

 

Discovery and access

  • Data is easy to discover through search and use cases.
  • The data is cost-effective, and pricing is clear.
  • Purchase and download is simple.

Suitability

  • Data available for specifically your area.
  • Includes all required data for use case.
  • The data enables you to make decisions quickly with minimal resources.
  • The data has a clear track record i.e., where and how it’s been used in practice.

Compatibility

  • The data is available in file formats your tools support.
  • Standard fields, schemas, and units are used (e.g. UPRN).

Quality

  • The data has been quality checked and validated, and is therefore accurate.
  • The data has been created using domain expertise and knowledge.
  • Methodologies are documented and available to audit.

Maintainability

  • The data lifecycle and update frequency is documented.
  • Regular updates are easy to obtain and integrate.
  • Data is in a single location for ease of use.

Reusability

  • Support tools and use cases are available.
  • Transformation tools are available.

 

Do it yourself

Open source and closed data from the organisation.

Use custom-made/commissioned datasets

Use a specialist consultancy to create the required datasets for you.

 

Use trusted data providers

Use a trusted data provider to ensure the accuracy, consistency, and lifecycle of the data.

Discovery and access
Data is easy to discover through search and use cases. Data tends to be presented as datasets if you know what you need. Data is provided as specified. Data providers will bundle datasets targeting specific use cases.
The data is cost-effective, and pricing is clear. Cost free. Data is single use, and pricing depends on contracts and specification. Data providers will usually provide a clear pricing list or various datasets and collections.
Purchase and download is simple. Usually simple download available. Procurement of external consultation can be difficult and time consuming. Data providers will provide an easy way of purchasing and assessing purchased data.

Suitability
Data available for specifically your area. Data may cover your area or may need to be extracted from a larger dataset. Data will be as specified. Data should be available tailored to your area.
Includes all required data for use case. Dataset will need to be chosen and managed. Data will be as specified. Data collections may include all the data required for specific use case.
The data enables to you make decisions quickly with minimal resources. Work will be needed to transform data into appropriate datasets to make decisions. Should be specified for the exact use case and decision to be made. Should be use-case led.
The data has a clear track record i.e., where and how it’s been used in practice. Occasionally a community may share experiences. Unlikely. Data provider may provide usage examples and testimonials.

Compatibility
The data is available in file formats your tools support. May provide multiple download and access options. Will provide what is specified. May provide multiple download and access options.
Standard fields, schemas, and units are used (e.g. UPRN). In some cases. Depending on specification. Should provide standard fields.
Transformation tools are available. Often a community will maintain tools around open datasets. Only if explicitly specified. May require extra cost. A good data provider will provide a suite of useful tools alongside the datasets.

Quality
The data has been quality checked and validated, and is therefore accurate. Data may be from validated sources, but may not be validated itself. Caution is required. Depends on specification. A good data provider will provide validated and accredited data.
The data has been created using domain expertise and knowledge. May be the case. Caution is required. If a good contractor is selected with experience in the domain. Data providers tend to be domain specific and will have access to expertise to create data.
Methodologies are documented and available to audit. In some cases. Depends on specification. Good data providers will provide methodologies and upstream data sources.

Maintainability
The data lifecycle and update frequency is documented. In some cases this may be the case. Dataset ends up being a one-off. A good data provider will update and maintain datasets over a long lifecycle.
Regular updates are easy to obtain and integrate. Depending on the supporting community. Dataset ends up being a one-off. Data is often available as a subscription service.
Data is in single location for use of use. Open data may be on multiple platforms. Single data package may be provided as deliverable of contract. Data is all in place and provided repeatedly.

Reusability
Support tools and use cases are available. There may be a community that builds tools around the data.  Depends on specification. A data provider should provide additional support, tools, and examples of data use.
 
 

 

Register to access the full article

Designed to aid Local Authorities in developing robust, evidence-based plans to enable Net Zero.

Register now

Already have an account? Login

Free UK Local Authority access

Register now
  • Guest preview of selected publicly available resources
  • Full library of 1,000+ articles
  • CPD accredited e-learning courses
  • Case studies
  • Discussion forum