Additional Resources & Further Reading
This section provides additional references, definitions, and support resources for librarians who want to deepen their understanding of data use in public libraries. It includes a glossary of common data terms, research relevant to Wisconsin libraries, recommended readings, and contacts for further assistance.
Understanding basic data terminology can help build confidence when working with datasets, reports, and dashboards. The following definitions focus on terms commonly used in public library data and reporting.
| Term | Definition |
| Aggregated Data | Data that is collected and combined from multiple sources or individuals in order to provide a summary or overview of a larger population or group. Does not contain personally identifiable information. |
| Anonymization | Removing identifying information so data can be safely analyzed or shared (for example, reporting total checkouts without patron names). |
| Benchmarking | Comparing your library’s data to similar libraries, regional averages, or national standards to understand performance and identify areas for improvement. |
| Cohort | A group of items or people that share a common characteristic and are analyzed together, such as libraries of similar population size or patrons in the same age group. |
| Dashboard | A visual display of data, often charts or graphs, that summarizes key metrics in one place. |
| Data | Information collected by the library, such as circulation numbers, program attendance, or survey responses |
| Data Analysis | Examining data to identify patterns, trends, or insights. |
| Data Ecosystem | A connected network of people, tools, technologies, and processes that work together to collect, store, analyze, and share data within an organization or environment. In the case of this toolkit, the data ecosystem includes Wisconsin public librarians and other interested parties involved in this work. |
| Data Governance | Policies and procedures that guide how an organization collects, stores, uses, and protects data. |
| Data Lifecycle | The stages data goes through: collection, storage, use, sharing, and eventual deletion. |
| Data Literacy | The ability to read, understand, analyze, and communicate with data. |
| Data Privacy | Protecting personal information about patrons so it is not shared or misused. |
| Data Quality | The accuracy, completeness, and reliability of data. For example, whether patron records are up to date. |
| Data Security | Tools and practices used to protect data from unauthorized access, such as secure systems and passwords. |
| Datapoint | A single, distinct piece of information or observation within a larger dataset. It represents a specific value, measurement, or characteristic, such as a sensor reading, survey answer, or numerical entry. An example is the average age of your collection. |
| Dataset | A collection of related data, such as a spreadsheet of all checkouts from the past year. |
| Field | The smallest, specific unit of information in a database, spreadsheet, or form, representing a single category of data—such as a “Phone Number” or “First Name”. |
| Filter | A tool used in spreadsheets or dashboards to display only certain data, such as a specific year, library branch, or program type. |
| Inputs | The resources a library invests in services, such as funding, staff time, collections, and facilities. |
| Key Performance Indicator (KPI) | A specific metric used to evaluate progress toward a goal. In libraries, examples might include circulation per capita, program attendance, or number of active cardholders. |
| Metadata | Structured, standardized information used to describe, explain, or locate resources, making them easier to find, access, and manage. In libraries, the most common example is the data in MARC records, which describe books, journals, and other materials in a consistent format for cataloging and discovery. |
| Metrics | Specific measurements used to track performance, such as monthly circulation totals or new library card registrations. |
| Normalization | Adjusting data to allow fair comparisons between different groups, often by using measures such as per-capita rates. |
| Outputs | The direct results of library services, such as circulation numbers, program attendance, or database usage. |
| Peer Libraries | Libraries with similar characteristics—such as population served, budget, or size—used for comparison and benchmarking. |
| Per Capita | The average amount of something per person in a population. It is calculated by dividing a total by the number of people and allows for meaningful comparisons across different population sizes. |
| Personally Identifiable Information (PII) | Information that can identify a specific person, such as name, address, library card number, or email. |
| Raw Data | Often referred to as source or primary data, raw data is data that has not yet been processed, coded, formatted, or analyzed. Best example in public libraries is the Wisconsin Public Library Annual Report data spreadsheet. |
| Table | An arrangement of information or data, typically in rows and columns, or possibly in a more complex structure. |
| Trend Analysis | Examining data over time to identify patterns, increases, decreases, or long-term changes. |
In 2022, the Southwest Wisconsin Library System (SWLS), in partnership with WiLS, conducted an LSTA-funded research project to better understand the current data skills and needs of public library staff across Wisconsin.
The project examined the statewide library data ecosystem—the people, organizations, and resources involved in collecting, using, and supporting library data. The goal was to identify how libraries currently use data, what barriers exist, and what training or tools might help librarians use data more effectively.
The resulting Data Landscape Report, published by the Wisconsin Department of Public Instruction (DPI), provides insights into librarian confidence with data and offers recommendations for improving training, access, and support for data use in Wisconsin public libraries.
The following books, articles, and training materials provide additional guidance on data use, visualization, and storytelling.
Books
Storytelling with Data: A Data Visualization Guide for Business Professionals, Cole Nussbaumer Knaflic (Wiley, 2015)
A widely used guide to creating clear and effective data visualizations and communicating insights through charts and graphics.
Training and Articles
- Public Library Association (PLA) Census Data Literacy training series
- Research Institute for Public Libraries (RIPL) webinars on data planning and evaluation
- Frameworks for Storytelling with Data
These external resources provide worksheets, templates, and learning materials for improving data literacy skills.
Data Literacy Toolkit
https://data-literacy-toolkit.github.io/index.html
There is a wide network of data experts and enthusiasts in the Wisconsin public library community. Below are some suggested places to start if you have questions about primary data sources and need support navigating Wisconsin’s data ecosystem.
Library system staff and data coordinators
Check with your system. Many have staff with expertise in data who can provide guidance and support.
Wisconsin Department of Public Instruction – Bureau of Libraries Data Analyst
The staff directory will list the current Data Analyst/State Data Coordinator who can answer questions about statewide library data.
Wisconsin Library Services (WiLS) – Research and Data Services
WiLS is a nonprofit member organization supporting Wisconsin libraries and cultural organizations. Check out their Research and Data Services page for more information on the data support services they offer.
Wisconsin Public Library Consortium (WPLC)
WPLC develops and underwrites tools and resources to help Wisconsin libraries use data effectively. Examples include this toolkit and the WPLC Data Dashboard. You can also reach out to your system’s WPLC board representative with questions about data services.
Remember to connect with colleagues within your system or from other libraries – sharing knowledge and experiences strengthens data expertise across the community.
Across the country, states are finding new ways to use, share, and explore library data. Discover how other states are analyzing, visualizing, and applying data to enhance their public libraries.
Colorado
Colorado Public Library Statistics and Resources
The Library Research Service (LRS) generates library statistics and research for library and education professionals, public officials, and the media. LRS is an office of the Colorado State Library, which is a unit of the Colorado Department of Education.
Florida
Florida Public Library Data Dashboard – This dashboard is intended to provide an easy way to display data reported in Florida for fiscal year 2018-19 through the most recently published fiscal year. It includes a tutorial video on how to interact with the dashboard.
Illinois
RAILS Data in Libraries
RAILS is a WiLS-like organization serving the northern half of Illinois. Their Data in Libraries page provides resources for their members and supports libraries in understanding, using, and sharing data.
New York
Telling Stories with Library Data – The Met Museum showcases how library data can reveal insights and support storytelling about collections, users, and library services.
Ohio
Ohio Public Libraries by the Numbers provides an interactive dashboard of Ohio’s public library system. Users can explore library locations, staffing, collections, and usage statistics, making it easy to see trends and compare data across the state.
South Carolina
Public Library Infographics – South Carolina’s ‘Library Systems at a Glance’ provides an overview of the state’s public library systems, highlighting service areas, populations served, and key library statistics gathered for the IMLS Public Libraries Survey.
Washington
Library Fact Sheets – Washington State Library’s publications and factsheets offer key data and insights on public libraries, services, and statewide library trends.