This section provides guidance about how to consider user needs in a more systematic way
Frustrations for data users
Our research with data users highlighted that many felt open data was still sometimes challenging to access and make use of. Although data may be freely available online, some data users described difficulties actually finding and extracting the specific data they required. This was due to issues with the templates or formats, time periods and geographic regions that didn’t quite fit their requirements or other (perhaps unintended) limitations.
Problem examples
Data is not explained
No description of metric
Unclear unit of measurement or time frame
Unclear distinction between whether figures given represent actual counts, or percentages or proportions
Minimal supporting text or context for data
Charts with unclear labels, colours or keys
Data is not accessible
Raw data in large spreadsheets not easily downloaded or able to view on screen
Static PDF documents that can’t be edited or text can’t be selected
There is no feedback loop
Users cannot review or comment at point of access/no identifiable contact information
No outlet for group feedback or peer support
Quick Fixes: Common Publishing Errors
Be careful to address the following common publishing errors as these are often aspects of data that can easily be cleaned up, and help to create a simpler and more accessible experience for data users.
Dates. Mixed date formats or British versus American dates used simultaneously.ACTION: be consistent with date formats within documents and across different publications if possible. Where necessary add a label that indicates which date format is being used.
Multiple representations. Abbreviations and expanded forms i.e. Vice-President or VP or vice-pres. ACTION: Try not to use abbreviations; clarity is better. If they are unavoidable, create a key or glossary to explain them in full and be consistent in how they appear.
Duplicate record detection. When searching for a term, items are duplicated to speed up searches across multiple domains. ACTION: if there is no technical solution for this within the platform you are using to publish, then be clear with a warning that tells data users that there may be duplicate records.
Summation records. Data containing notes, sums or formula instead of expected numerical data. ACTION: this is 'data noise' that you may want to remove from your data. However, where necessary you can colour code summation data to indicate that is should not be included in analysis.
Redundant data. Unrelated data in data sets, such as administration codes, thats data users do not require. ACTION: this is 'data noise' that you may want to remove from your data. However, where necessary you can colour code summation data to indicate that is should not be included in analysis.
Numeric ranges. Often used to anonymise data by grouping individual data points together, but can make searching difficult. ACTION: Where possible, allow data users the functionality to create their own more meaningful numeric ranges.
Spelling errors. Can lead to limitations when querying and search data; also impacts automated visuals that rely on text. ACTION: Thorough proofreading is required and should be past of a Quality Assurance Process before data is published.
Data users may get frustrated with common publishing errors, but these can often be easily fixed.
Mapping the user journey
A user journey map is a visualisation of the process that a person goes through in order to accomplish a goal. User journeys are used to:
Understand user needs and motivations
Create useful customer insights and validate what we know
Develop consistency and clarity of thought across an organisation or project
Invite collaboration and constructive dialogue to determine how best to meet user needs
Create actionable intelligence to create and develop a user-centric service and product portfolio
Mapping user motivations and touchpoints at different stages of their journey is another way to ensure the data offer is user-centric. There are various user needs at different stages of engagement. The mapping tool below could be used to help break the user journey into simple stages and document these needs. Or it could be generated in a data user workshop, for example.
Are there aspects of the user journey you are concerned about? Can the tool below help you to pinpoint specific issues?
TOOL: Reviewing touchpoints along the user journey
