Monday, August 13 Tuesday, August 14 Workshop Details

Center for British and Irish Studies, Norlin Library, University of Colorado Boulder
1720 Pleasant Street
Boulder, Colorado 80309

Below is the schedule for the 2018 symposium. The schedule will be finalized by early August with unconference topics listed.

Slides available on the OSF

Monday, August 13

Time Description
8:30 • Registration desk opens
9:00 - 9:30 • Welcome
• Coffee & tea
9:30 - 11:00 • Workshop 1: Data Lit through Data Viz
11:00 - 11:15 • Break & Networking
11:15 - 12:15 • Unconference session 1: Data Visualization
12:15 - 1:15 • Lunch
• Birds-of-a-feather discussions
1:15 - 1:25 • Break & Networking
1:25 - 2:25 • Unconference session 2: Data Curation
2:25 - 2:50 • Day 1 Wrap Up
2:50 - 3:30 • Travel to LASP on CU East Campus
3:30 - 4:30 LASP tour (optional)
6:15 / 6:30 Dine arounds

Tuesday, August 14

Time Description
9:00 - 9:20 • Coffee & tea
9:00 - 9:20 • Welcome • Robert McDonald, Dean, University of Colorado Boulder Libraries
9:20 - 10:30 • Workshop 2: Pseudoreplication and Its Relationship to Irreproducible Results
10:30 - 10:45 • Break & Networking
10:45 - 12:00 • Workshop 3: Delivering Data Instruction: Tools, Tips, and Tricks
12:00 - 1:00 • Lunch
• Birds-of-a-feather discussions
1:00 - 2:00 • Lighting Talks
2:00 - 2:15 • Break & Networking
2:15 - 3:15 • Unconference session 3: Data Citation
3:15 - 3:30 • Break & Networking
3:30 - 4:30 • Unconference session 4: Topic to be proposed on day 1
4:30 - 5:00 • Wrap-up


Workshop 1: Data Lit through Data Viz
Presenter: Russ White

Working as a ‘Data’ specialist within an academic library, many librarians interact with students and faculty with wide-ranging skill levels and disciplinary practice regarding data. By cultivating the fundamental skills of visualization, specialists can remain equipped to address common challenges that arise when working with data, throughout the research data lifecycle. In this hands-on workshop, participants will engage with instructional material designed for teaching data literacy concepts to undergraduate students, though the practice of visualization. Material includes principles of graphical excellence as a means for evaluating and critiquing visualizations, strategies for finding data and visuals, choosing and applying chart types, and preparing to share a finished visualization. Using the data visualization software Tableau, users can explore datasets and create visualizations by iterating several visual forms. Teaching with Tableau provides the advantage of focusing on the visual versus the data structure, as in spreadsheets. Finally, while Tableau is a valuable general-purpose tool for exploring and sharing data, participants will benefit from identifying the range of visualization practices used within different communities. Contrasts between common spreadsheet applications, infographic templates, interactive dashboards, and plotting libraries (eg Plotly) as applied in RStudio or Jupyter Notebooks will also be introduced. Visualization is a common and vital practice that can be used to strengthen aspects of data literacy needed throughout the research process.

Workshop 2: Pseudoreplication and Its Relationship to Irreproducible Results
Presenter: Meg Eastwood

Ecological studies were transformed by Hurlbert’s 1984 article that introduced the concept of pseudoreplication, or “the use of inferential statistics to test for treatment effects with data from experiments where either treatments are not replicated (though samples may be) or replicates are not statistically independent.” While many ecology students encounter the idea of pseudoreplication as an undergraduate, and hopefully receive instruction in how to avoid it in their own research, the concept has not yet spread to all fields. In this session, you’ll participate in a hands-on activity that helps illustrate the concept of pseudoreplication, discuss a literature review that explores which fields have had a discourse about pseudoreplication, and leave with a template for an activity to teach pseudoreplication to students and researchers in any field. Understanding pseudoreplication and learning to avoid it in your own studies can be a powerful tool to promote research reproducibility.

Workshop 3: Delivering Data Instruction: Tools, Tips, and Tricks
Presenters: Elena Azadbakht, Teresa Schultz and Rayla Tokarz

Data librarians and others who support data services are often eager to teach users about data management best practices, but deciding the best way to teach data management can be difficult. Using scenarios of patrons seeking help, this workshop will guide attendees through the process of deciding what a group’s needs are and identifying the necessary data information literacy concepts connected to those needs. We will then work on brainstorming ideas on effective methods to teach different data information literacy competencies using example teaching scenarios. This workshop will approach teaching data information literacy from both a research data management and an instructional design standpoint.