Finding the Right Data at the Scholarly Commons

As you probably know, February 13-17th is Love Your Data Week, an annual event that aims to help researchers take better care of their data. The theme for today — Thursday, February 16th — is finding the right data, a problem that almost all researchers will run into while doing their work at some point or another. And the Scholarly Commons is here to help you out! Here are a few ways that you can “find the right data” through the services we provide here at the Scholarly Commons.

Online resources

The University of Illinois subscribes to an almost countless number of online resources that you can find datasets and data files on. While it can be hard to figure out where to start, oftentimes, there will be a LibGuide that can help point you towards a few sources that you will find helpful. The Finding Numeric Data LibGuide specializes in data for the world, United States, and Illinois, and can generally be used for projects in the social sciences. If you’re looking for GIS data, you can head to the Geographic Information Systems (GIS) LibGuide. We even have an area where you can browse all of the Library’s LibGuides and see which guide will be of the most use to you.

Purchasing data

If you’ve found a dataset that you truly need, but cannot get it through one of the services UIUC subscribes to, you may be eligible for the 2017 Data Purchase Program. Researchers can submit an application which outlines their data needs, and the University Library may choose to purchase the data, and make it available for general use by the campus community. For more information, see the Data Purchase Program website, linked above.

Attending a Savvy Researcher workshop

Throughout the semester, the Scholarly Commons and other Library departments run Savvy Researcher workshops, which teach attendees various skills that will help them be better researchers. While many deal with finding or organizing data, here is a sampling of a few upcoming workshops that will deal directly with finding data: Finding and Organizing Primary Source Materials in DPLA, Advanced Text Mining Techniques with Python and HathiTrust Data, and GIS for Research II: GIS Research, Data Management, and Visualization. For the full schedule of Savvy Researcher workshops, head to the Savvy Researcher calendar. You can also get an idea of what’s going on with the Savvy Researcher workshops by looking at the #savvyresearcher on Twitter!

Making an appointment with an expert

A central part of the Scholarly Commons’ mission is to connect you to the people you need to get the help you need. If you’re looking for data help, take a gander at our Scholarly Commons Experts page and see if there is someone on staff who can help you find what you need. If you’re still not sure, don’t worry! You can always fill out a consultation request form, or email us, and we’ll help you get in touch with someone who can guide you.

Love Your Data Week 2017

The Scholarly Commons is excited to announce our participation in Love Your Data Week 2017. Taking place from February 13-17th, Love Your Data is an annual event that aims to “build a community to engage on topics related to research data management, sharing, preservation, reuse, and library-based research data services.” The 2017 theme is data quality.

Love Your Data Week takes place online, and you’ll find us posting content both on this blog (look out for our post on February 16th) and at our Twitter, @ScholCommons. We’ll be posting new content for each day of Love Your Data Week, so stay tuned! You can follow the wider conversation by looking at the hashtags #LYD17 and #loveyourdata on Twitter and elsewhere. You can also check out the University of Illinois Research Data Service’s Twitter @ILresearchdata for their Love Your Data Week content!

Each day of Love Your Data Week has a different theme. This year the themes are as follows:

  • Monday: Defining Data Quality
  • Tuesday: Documenting, Describing, Defining
  • Wednesday: Good Data Examples
  • Thursday: Finding the Right Data
  • Friday: Rescuing Unloved Data

Got something to say about data? Or just want to be a part of the action? Tweet @scholcommons or comment on this article!