LibGuides: Digital Scholarship: Manage and visualize data

Why manage and visualize data?

Organized data is much easier to work with and usually a prerequisite to accomplishing other parts of a project. There are many, many ways to organize data but if you are having trouble, take a look at the suggestions below. Each tool works well with specific kinds of data and for specific applications.

Data visualization is the graphical representation of data. There are simple representations such as scatterplots and histograms or very complex visualizations such as chloropeths and Sankey diagrams. Data visualizations, when done well, can quickly convey a vast amount of data in a way that people comprehend quickly. There are a number of useful tools and resources in the Duane G. Meyer Library building that can assist you in creating visualizations.

Visualization examples

Amazing historical visualizations:

Mortality in the Crimean War (Florence Nightengale)

Napoleon's Russian campaign (Charles Minard)

London Cholera Maps (John Snow)

Modern visualizations:

Solar eclipses (Washington Post)

Universcale (Nikon)

100 Years of Rock (Concerthotels.com)

Data Management Tools

The following tools are listed with faculty and student research projects in mind. Most, but not all, are readily available as open source or campus resources.

Microsoft Excel
MS Excel is a good first tool to learn for many data management projects. By using Power Query and pivot tables you can quickly manipulate moderate amounts of data.
OpenRefine
OpenRefine is a powerful tool for working with messy data: cleaning it; transforming it from one format into another; and extending it with web services and external data.
SQLite
A small, fast, serverless, yet full featured SQL database engine. This is a great tool for student and faculty projects.
NVIVO
Powerful qualitative and mixed methods data analysis tool. (not free)
SPSS
Prevalent statistics software for academia. (available in computer labs on campus)

Learn about Visualization

The following resources provide information about how and why to create and use visualizations.

Websites/Blogs:

The Data Visualization Catalogue - Examples and explanations of many visualization types.
Flowingdata - A regular blog providing examples of good explanations and explaining them.

Books:

Few, S. (2006). Information dashboard design: The effective visual communication of data (First edition). O’Reilly.
Steele, J., & Iliinsky, N. P. N. (Eds.). (2010). Beautiful visualization: Looking at data through the eyes of experts (First edition). O’Reilly.
Tufte, E. R. (1983). The Visual display of quantitative information. Graphics Press.
Yau, N. (2011). Visualize this: The FlowingData guide to design, visualization, and statistics. Wiley Pub.

Articles:

2013 Stéfan Sinclair, Stan Ruecker, and Milena Radzikowska, “Information Visualization for Humanities Scholars” | Literary Studies in the Digital Age. (2013). In Literary Studies in the Digital Age: An Evolving Anthology. MLA Commons.

Visualization Tools

ArcGIS is a mapping and data analysis application.
D3.js - is a javascript library for visualization and data processing.
Draw.io is an extension in Google Drive or Microsoft Office 365. It can create many types of diagrams, flow charts, and other visualizations.
Highcharts provides javascript charts to include on web pages.
Microsoft Excel provides a foundation for working with data and visualizing it. It can connect to external data sources, or export data to external visualization software.
Microsoft Power BI can create dynamic dashboards and connect to data from single files or external data sources.
R Project is free software environment for statistical computing and graphics.
Tableau is an easier to learn but still sophisticated visualization software