Data Visualization Services Toolkit for Libraries

This toolkit is intended for librarians and libraries embarking on a new data visualization service, but could also be used to refresh skills, develop lesson plans for a data visualization course, or as a starter for anyone with an interest in the topic.

Conduct Research on Data Visualization Services in Libraries

Begin by reading about the history of data visualization services in libraries. Consider types of services offered (workshops, consultations, etc.) and staff necessary (graphic designer, data librarian, etc.) for development and implementation of data visualization services, paying special attention to challenges and solutions. 

Perform a Data Visualization Needs Assessment

Consider performing a data visualization needs assessment to tailor your services to users’ needs. Model your needs assessment after existing examples and diversify your data collection methods. Think about the various stakeholders whose input would offer valuable insight.

Look for Data Visualization Learning Opportunities

If your library does not have the resources to hire a graphic designer, data visualization specialist, data analyst, or statistician, you may need to educate yourself in order to offer a data visualization service. Look for in-person workshops, online opportunities, and institutional presentations and course auditing opportunities. The focus of data visualization trainings varies (tools, strategies, disciplines, etc.) - if possible, diversify the types of trainings you take.

Review Open Source Data Visualization Materials from Other Libraries

One of the best resources for developing a data visualization service may be the workshop materials made publicly available by other libraries. These can be great sources for developing your own suite of services or initial outline for a data visualization program or workshop.

Incorporate Ethics & Accessibility Guidelines into Services

Data visualization services should educate about ethical considerations and accessibility guidelines, ensuring that visualizations benefit as many users as possible.

Develop Data Visualization Use Cases

Whether participants in your programming have a specific dataset that they are working with or not, it is a good idea to have a few prepared datasets for instruction and practice. You may create your own or utilize those provided by data visualization tools such as Tableau. Below are a few sources of freely available data.

Evaluate Data Visualization Services

The final step is to evaluate whatever data visualization services you offer to better them over time. You might evaluate content, curriculum flow, examples provided, interactivity, marketing strategies, and more. There is a gap in the evaluation literature where data visualization services are concerned; this is an opportunity for professional advancement.

Last Updated: Jul 6, 2023 4:21 PM