Data and donuts

Multiple sessions held on: 3/8/17, 5/16/17.So you've taken the R basics session and you're ready to make publication quality graphs using R. This month's Data and Donuts will show you how to use the ggplot package in R. After this session, you will be able to create a variety of plot types, alter their aesthetics, and use facets to automate the creation of several graphs at once. Some experience with R is recommended but not required

Data and donuts

One element of good data management is knowing what you have and where it is. This month's Data and Donuts will discuss best practices for data organization. The session will discuss how to organize tabular data within spreadsheets

Data and donuts

Multiple sessions held on: 5/10/17, 7/25/17, 5/15/18.This month's Data and Donuts will cover best practices for preparing your data for archiving. We will discuss how to properly describe your data so that others, or you from 5 years from now, will know what it is and how to use it, as well as appropriate places to store it. We'll also discuss options for repositories that will allow others to access your research data, including CSU's digital repository

Why Can’t I just use Dropbox? A comparison of cloud file storage platforms used for research

Objective: Many researchers use cloud file storage platforms such as Box and Google Drive as the sole data management platform for all of their research data throughout the course of their projects. Researchers have lost access to their preferred platforms due to changes in licensing agreements and cost to their institutions, leaving researchers to figure out a new system on their own. This paper describes differences between these platforms that affect research data workflows. Methods: We selected four commonly used cloud file storage vendors (Box, Dropbox, Google Drive, and Microsoft SharePoint/OneDrive) to assess. The authors read public user documentation for the platforms and identified several differences, such as maximum file size, that could affect research data workflows. For each difference, we recorded the specifics of each platform then narrowed the scope to features that vary across the platforms. Results: We identified three areas where cloud platforms differed in ways that affect data management: data stewardship, storage capacity, and file organization. Data stewardship is affected by variations in the platforms’ approaches to individual vs. group ownership of files and how user roles are defined and assigned. The platforms also differ in limits on total capacity, individual file size, total number of files, and the amount of data that can be moved in and out of the platform. Some of these limits vary by access method (e.g. API vs web interfaces). Finally many differences affect how data can be organized, such as number of files per folder, synchronization, and file sharing restrictions. Conclusions: Some research data workflows may be negatively affected by moving between cloud file storage platforms. Researchers will need assistance identifying differences between the platforms and modifying disrupted data workflows.&nbsp

Data and donuts

This presentation describes best practices for how to write a data management plan for your research data. Additionally, it provides information about finding funder requirements, metadata standards, and repositories

Data and donuts

One element of good data management is knowing what you have and where it is. This month's Data and Donuts will discuss best practices for data organization. The session will discuss topics like efficient folder structures, proper file naming and how to organize tabular data within spreadsheets

Data and donuts

Our access to the web makes collaborating with colleagues at other institutions easier, but it is not without its challenges. In this Data and Donuts, we will cover a tool. After this session you'll be able to how to to store files, easily collaborate with people outside your institution, and link accounts like Google Drive and Dropbox

Data and donuts

One element of good data management is knowing what you have and where it is. This month's Data and Donuts will discuss best practices for data organization. The session will discuss topics like efficient folder structures, proper file naming and how to organize tabular data within spreadsheets

Coding and cookies

The process of generating data can be messy, especially when data are hand collected by multiple people. This month's Coding and Cookies will discuss how to wrangle messy tabular data using R. After this session, you will be able to import tabular data into R, convert data to an appropriate type, recode categorical variables, convert dates, manipulate strings, detect and fix errors in your data. A basic working knowledge of R and R studio would be helpful for you to get the most out of this session