Research Guides: Data Visualization: Tools to Help You Build

General Tools

Many tools can help you to build your visualization once your plan is fleshed out. The following resources contain more links than we can highlight here, so take your time finding the one that's right for you:

Visualizing Data Resources
Awesome dataviz frameworks, libraries and software on GitHub

In addition, some more popular tools include:

Excel: Visualizations are easy to create with Microsoft Office's spreadsheet application (available through TERPware). However, some of Excel's visualizations--including 3-dimensional bar and pie charts--may be misleading.
Tableau: With a wide variety of visual representations available, including maps, Tableau allows users to create interactive visualizations and dashboards. The Public version of Tableau is available for free ask a desktop application; most functions are enabled, but all files need to be saved online. The Desktop version of Tableau allows users more flexibility importing data and exporting visualizations, and can be obtained free of charge by many students and teachers (see https://www.tableau.com/academic/teaching or https://www.tableau.com/academic/students).
A dobe Creative Cloud: Adobe's Creative suite is the industry standard for creating and editing of static images. Photoshop is primarily used to edit raster images, while Illustrator handles vector images. Available for students, faculty, and staff through TERPware.

Most software platforms contain libraries to support data visualization. Some of the most popular include:

In R: Ggplot2, ggvis, and rgl are the most popular visualization libraries in R. The team at RStudio recently compiled a full list of recommended libraries for data manipulation, analysis, and visualization.
In Python: Matplotlib, plotly, bokeh and ggplot (adapted from R) are the most commonly used visualization libraries in Python. There are dozens of options, though. This post from James Bednar at Anaconda gives a sense of the diverse landscape.
With D3.js: A popular series of JavaScript libraries used to create dynamic online visualizations.

Map Tools

If you are trying to create a map visualization, there are two tools that are both powerful and effective. However, mapping data often comes with it own suite of potential concerns. If you need help visualizing data on a map, please reach out to our GIS Librarian in the Research Commons.

QGIS
An open source, free mapping service.
ArcGIS
A proprietary mapping software that requires a licensee for the desktop version. UMD offers a limited number of licenses available to some faculty; contact our GIS Librarian for more information.
ColorBrewer 2.0
A color picker for choosing colors specifically for maps.

Specialized Tools

Network and graph analysis tools can help explore and communicate information about relationships within data. These tools are commonly used for analysis of biological networks, but also have expanded into social (media) network analysis, business analytics, health sciences and other disciplines. Some of the most popular tools and handbooks for their use are featured below.

Gephi
Gephi is a free, open source network and graph visualization tool. It is focused on pattern and network analysis, but offers other features such as Exploratory Data Analysis and poster creation.

Network Graph Analysis and Visualization with Gephi by Ken Cherven
ISBN: 9781783280148
Publication Date: 2013
"A practical, hands-on guide, that provides you with all the tools you need to visualize and analyze your data using network graphs with Gephi.This book is for data analysts who want to intuitively reveal patterns and trends, highlight outliers, and tell stories with their data using Gephi. It is great for anyone looking to explore interactions within network datasets, whether the data comes from social media or elsewhere. It is also a valuable resource for those seeking to learn more about Gephi without being overwhelmed by technical details." From publisher
Mastering Gephi Network Visualization by Ken Cherven
ISBN: 9781783987351
Publication Date: 2015
"This book is intended for anyone interested in advanced network analysis. If you wish to master the skills of analyzing and presenting network graphs effectively, then this is the book for you. No coding experience is required to use this book, although some familiarity with the Gephi user interface will be helpful." From publisher
Gephi Cookbook by Devangana Khokhar
ISBN: 9781783987405
Publication Date: 2015
"Gephi Cookbook is a guide to learn about interactive network exploration and visualization accompanied by the graph theory concepts that drive them. It helps you to understand about the nuances of network visualization, not only from a conceptual, but also from an implementation perspective. This book is an invaluable resource if you are looking forward to getting a deep-dive into the network analysis domain without having to learn how to code." From publisher

Cytoscape
"Cytoscape is an open source software platform for visualizing molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data. Although Cytoscape was originally designed for biological research, now it is a general platform for complex network analysis and visualization."

Graph Analysis and Visualization by Richard Brath; David Jonker
ISBN: 9781118845691
Publication Date: 2015
Graph Analysis and Visualization brings graph theory out of the lab and into the real world. Using sophisticated methods and tools that span analysis functions, this guide shows you how to exploit graph and network analytic techniques to enable the discovery of new business insights and opportunities. Published in full color, the book describes the process of creating powerful visualizations using a rich and engaging set of examples from sports, finance, marketing, security, social media, and more. You will find practical guidance toward pattern identification and using various data sources, including Big Data, plus clear instruction on the use of software and programming. The companion website offers data sets, full code examples in Python, and links to all the tools covered in the book. Cytoscape is introduced and featured heavily throughout.
Computational Systems Biology Approaches in Cancer Research by Inna Kuperstein (Editor); Emmanuel Barillot (Editor)
Call Number: ebook
ISBN: 9781000682564
Publication Date: 2019
This book focuses on computational systems biology approaches, with a particular lens on tackling one of the most challenging diseases - cancer. Chapter 3: Multi-Level Data Analysis in Cancer: Tools and Approaches covers the use of Cytoscape for analysis of molecular interaction networks in cancer research, with broad applicability to systems biology and other network analysis fields.