Purpose & Goals

This poster will explain how the process of writing and implementing a data visualization style guide has cascaded into programmatic improvements for my library’s approach to data analytics. Over the past decade, my organization has gone from one-off experiments with Tableau to a full analytics program with multiple visualization designers, data manipulators and audiences. I found myself with a cluttered suite of visualizations that served as a visual representation of my team’s increasing Tableau skills throughout the years rather than a cohesive set of informative tools. Through the process of designing, writing, and implementing a Tableau style guide, I made other incremental improvements to my organization’s data analytics approach including a documented dashboard design process, a data quality assurance checklist, and a standardized approach to publishing and retiring visualizations. I hope to provide guidance and reassurance to librarians who may be at the beginning of their data visualization journeys by sharing lessons I have learned throughout the process.

Design & Methodology

To create a Tableau style guide, I found examples from news organizations, institutional research offices, and businesses. I also researched best practices in data storytelling, visual design, and accessibility. I designed templates to be used for creating new dashboards with set fonts, sizes, and color schemes. I wrote an accompanying document detailing instructions and best practices. My team is currently undertaking a project to retrofit all of our current dashboards to the new style guide and template, improving the usability and accessibility of our visualizations.

Findings

We have found that implementing the style guide is leading to improvements in our entire approach to data analytics, from design to accessibility to data quality.

Action & Impact

I plan to continue implementing the style guide until we have a stylistically cohesive set of dashboards that are more trustworthy and usable than what we previously offered.

Practical Implications & Value

I hope to help others starting out in data visualization learn from my mistakes and take the time to set standards and styles at the outset. This poster will contribute one approach to ensuring that we make our library data maximally impactful for our colleagues.

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