Data transformation framework: data personas report

2 Background research findings

Personas and project scope

Personas are fictional composite characters that are used to represent the different user types that might use a product or service. They help to bring to life the different user's needs, behaviours and goals. As archetypical models of groups of individuals, different personas will aim to have distinct needs, behaviours and goals which aid future service design.

Once complete, personas are often documented as:

• Who they are, including what they are likely to say;
• What motivates them – their goals;
• What they want – their needs;
• Their behaviours and preferences including what they like and don't like.

This project looked at data personas, or personas with a focus on how the character interacts with data in their existing roles. This covers the end-to-end lifecycle of data within public sector organisations from data creation to storage, governance, management, analytics, communication, and insights. This broad scope meant that there was an expectation that a number of personas may be required to ensure completeness.

Existing data persona sets

The project commenced with a review of existing data personas that are in use both within and outwith the public sector. The sets of personas that were reviewed and documented in detail were:

• Digital Scotland: These were developed in 2018 by the Digital Transformation Service to understand their service users and their analytical needs
• Archetypes: These were developed as part of a UK Geospatial Commission project to understand the users of spatial data
• ONS website (https://style.ons.gov.uk/category/writing-for-the-web/personas/): a set of personas identifying the characteristics of their website users
• Datacamp (https://www.datacamp.com/community/blog/persona-driven-learning): the four most common personas they encounter, though they have a full list of 11 (see below).
• Data Skills for Work (https://dataskillsforwork.com/what-is-data-literacy): this is a framework developed by EKOS and SDS to help to develop data skills pathways
• Draft DTF personas: initial work done within this broader project to identify the motivations and needs of the Data Transformation Framework

The following personas were also visited, but their characteristics were not documented in a detailed manner since there was considerable alignment with those already reviewed:

• Monte Carlo Data (https://www.montecarlodata.com/which-of-the-six-major-data-personas-are-you/): a blog covering the major types of data user in organisations
• Aryng data literacy (https://aryng.com/blog/data-literacy-personas/): a blog covering the skills and data literacy levels within an organisation
• Qlik data literacy (https://www.qlik.com/us/-/media/files/training/global-us/qlik-education-data-literacy-program-strategy-and-framework.pdf): a framework to identify different data literacy levels and therefore training needs within an organisation
• Sustainable Development Goals personas (https://sdgdata.gov.uk/user-personas/): a set of personas designed to understand the website users.
• Data Quality Hub: a set of personas developed by the Data Quality Hub within the Office of National Statistics around the types of individuals they engage with.

Documenting the existing personas

The high-level areas that were investigated for each existing data persona set were:

• Their needs when working with data
• Their skills
• The tools, systems and devices they use
• The data types and formats they access
• Their current knowledge around data and data management

The high-level areas were then broken down into more detailed topics with a set of standard category responses. The standard categories were developed from existing frameworks and lists of standard characteristics for data users. The use of standard categories allowed different sets of personas to be documented in a similar manner and similarities across each to be identified. This allowed a superset of draft high-level personas to be identified.

Draft persona identification

The draft high level personas are documented below with a draft name and summary that describes their motivations and interactions with data.

Through existing experience working in the world of data there were additional personas that were expected to be identified but weren't included within the persona sets reviewed for the background research. We have called these inferred personas. Some of these have been documented by Datacamp in their Data Science Industry infographic. The reason these have not been identified within the reviewed persona sets is that the data persona sets used have had a focus on data usage rather than data management, governance, system integration or security.