Call for Chapters: Data Visualization: A Guide to Visual Storytelling for Librarians
Proposals Submission Deadline: April 30, 2015
Full Chapters Due: August 1, 2015
Editor: Lauren Magnuson (California State University, Northridge, Los Angeles, United States)
Series: LITA Guides
Publisher: Rowman & Littlefield Publishers, Inc.
Introduction
Skills in data visualization are increasingly crucial for librarians and information professionals who work in libraries. Data and information visualization involves expressing information to tell meaningful stories with datasets. It is critical for libraries to communicate their value to their stakeholders, and data visualization tools and technologies can enable libraries to tell the story of their value in a way that is dynamic, engaging, and easy for viewers to understand. Libraries can also utilize data visualization technologies to assist researchers in interpreting public open data sets.
Objectives
This book will include three sections: 1) Choosing and interpreting datasets for visualization, 2) Tools and technologies for creating meaningful visualizations, and 3) Case studies of information visualization projects or applications in libraries. While many resources exist that focus on the tools and technologies of information visualization, this book’s emphasis on visualizing the unique data points important to libraries, such as electronic resource usage metrics, will be of direct use to library professionals and will be a distinctive feature of this book.
Target Audience
This book is of interest to public, academic, and special libraries, as many types of educational and information agencies seek to document and relate their value to their communities. Moreover, creating and interpreting data visualizations is an essential skill for library and information professionals seeking to make informed decisions based upon large and complex datasets about user behavior.
Recommended Topics
Recommended topics include, but are not limited to:
Choosing, interpreting, and designing visualizations from datasets, such as:
- How to identify data for use in visualizations
- Data presentation architecture
- Principles/best practices of visual storytelling with library data
- Visualizing data from a variety of sources, such as:
- Electronic resource (journal, database, e-book) usage
- Discovery and user behavior metrics and analytics
- Integrated Library System (ILS) / Library Services Platform (LSP) data
- Physical space utilization visualization
- Learning outcomes / instructional effectiveness metrics
- Institutional repository usage and inventory metrics
- Geographic and/or demographic data about library users or collections
- Visualizing workflows and processes
- Data mashups (combining data from multiple sources)
Tools, technologies, and architecture for creating meaningful visualizations, such as:
- JavaScript visualization libraries such as D3, Highcharts, Leaflet, Tabletop, or others
- Google Visualization API / Google Charts
- Creating visualizations with data from Business Intelligence (BI) tools such as Pentaho, Jaspersoft, or Tableau
- GIS tools for visualizing spatial or geographic data
- Tools for visualizing workflows and processes
Case studies of information visualization projects or applications in libraries, such as:
- Creating library usage and analytics dashboards
- Visualizing library collection usage
- Visualizations for data-driven decision making
- Visualizing processes or workflows for training and identifying efficiencies
- Using data visualizations in discovery interfaces
- Using data mashups (data combined from multiple sources) for visualizations
- Integrating data and spatial literacy into information literacy instruction
- Data visualization challenges and emerging trends in libraries
Submission Procedure
Please send a proposed title, 500-word abstract, and 100-word author bio to lauren.magnuson[at]csun.edu on or before April 30, 2015. Authors will be notified by May 5, 2015 about the status of their proposals.
Full chapters, 7,000-10,000 words each, are expected to be submitted by August 1, 2015. Full chapters can contain up to 8 color graphics/images. Chapters collaboratively written by multiple authors are welcome and encouraged. No previously published or simultaneously submitted material, please.
Full chapters should generally be organized with the following sections, with a maximum number of 8 color images per chapter:
- Introduction (500 words)
- Background (1000 words)
- History of your topic or visualization technology
- Explanation of unfamiliar terms
- The problem data visualization addresses
- Example Project or Case Study (4000-5000 words)
- Use case(s)
- Design
- Resources and tools used (e.g., server, development environment, software)
- Development
- Implementation
- Discussion, Outcomes and/or Assessment (1000 words)
- Assessing the impact of your data visualization project / case study
- Challenges and limitations
- Report case study outcomes (if applicable)
- Conclusions and Future Directions (500 words)
Important Dates
April 30, 2015: Proposal Submission Deadline
May 5, 2015: Notification of Acceptance
August 1, 2015: Full Chapter Submission Deadline
September 1, 2015: Required Revisions Deadline
September 15, 2015: Final Acceptance Notification
Inquiries can be sent to:
Lauren Magnuson
Systems & Emerging Technologies Librarian
Oviatt Library
California State University, Northridge
18111 Nordhoff Street
Northridge, CA 91330-8328
TEL: 818-677-2281
Twitter: @lpmagnuson
Email: lauren.magnuson[at]csun.edu
