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Research Data Services

Data services at UNO Libraries.

What is Data Services?

The Data Services Team at UNO Libraries helps you find and access data. We make selected software available, acquire data sets, and hold workshops on data topics. Data Services is not a statistical computing service and does not perform analysis for you, but we can help you get to the data you're after. We offer consultation services throughout a data lifecycle and offer help on data acquisition and management. 

Consultation Services

  • Data management plans
  • Data documentation / metadata guidance
  • Data management tools 
  • Reproducible research

Research Data Services Team

Data Management Tools

Quick start your data management with these tools:

  • DMPTool: Guidance and templates for creating data management plans
  • Open Science Framework: Manage and collaborate on research projects. Offers integration with Box, Dropbox, GitHub, and Google Drive.
  • Digital Commons@UNO: The digital repository for the University of Nebraska at Omaha. 


Spring 2020 Schedule

Additional workshops on High Performance Computing are offered by the Holland Computing Center.  See their calendar for more information.

BootcampR: Orientation and Setup (February 11)

Never used R before? Don't have RStudio installed? Need to know how to install libraries in R? Stop by this orientation session to learn the very basics of the software, tools, and methods in R that we'll be using this semester.

BootcampR: R Basics / Intro to the Tidyverse (February 18)

Come learn the basics of base R and methods of the Tidyverse library. This workshop introduces general concepts of the R language how to do basic operations in R, as well as a quick introduction to the tidyverse library that will be used for the remainder of the workshop series.

BootcampR: Spark Joy with Data (February 25)

Do you work with data that often needs cleaning up? Do you have a need to summarize or aggregate data within one source, or among multiple sources? This workshop introduces the dplyr and tidyr methods from the Tidyverse library.

BootcampR: Making Graphs (March 3)

The visualization of data allows us to communicate effectively, spot patterns in large datasets, or simply look for issues with the underlying data. This workshop introduces best practices and principles for data visualization, and works hands-on with the ggplot library from the tidyverse.

BootcampR: Visualizing Networks (March 10)

This workshop introduces methods for building network graphs and conducting social network analysis in R. Attendees will work hands-on with the ggraph, network, and ggplot libraries for creating, analyzing, and visualizing networks.

BootcampR: Making Maps (March 17)

This workshop introduces methods for making maps in R. Leave ArcGIS behind and learn how you can use the sp, ggplot, ggmaps, and related libraries for doing spatial analysis and visualization with R.

BootcampR: Clustering and Classifying (March 31)

Do you need ways of summarizing or aggregating data, or have an interest in machine learning methods for the classification of data? This workshop introduces statistical methods for classifying and clustering data in R.

Research Data Matters