Join us at the Research Data and Digital Skills Summer School and unlock the potential of digital scholarship and data literacy within the inspiring environment of the Glucksman Library. Expand your horizons, connect with like-minded individuals, and embark on a transformative journey towards becoming a proficient digital scholar. 

The  Summer School will run the whole week from 19th – 23rd June in the Glucksman Library building and will provide hands-on instructions on a range of digital tools to improve digital skills and data literacy of UL PhD students and researchers. 

The summer school does not assume previous knowledge of the tools covered, but participants with experience in some of the topics are most welcome to join and help their peers master new skills during the week. The tools covered will be beneficial to researchers from all disciplines. Participants are expected to attend all sessions. 

 

Schedule

Monday

10am-10:30 am:   Introduction (Data Visualisation Lab, GL1-029)

10:30am - 1pm:    Maximising the impact of research data (Data Visualisation Lab, GL1-029)

2pm-5pm:             Introduction to computational methods: Tidy Data & Regular Expressions (The Edge GL1-025)

 

Tuesday

10am-1pm:    Special Collections and Archives as datasets (Special Collections Reading room)

2pm-5pm:     Data visualisation and exhibition tools (The Edge GL1-025)

 

Wednesday

10am-1pm:    Data cleaning and enrichment with OpenRefine  (The Edge GL1-025)

2pm-4pm:      Programming with R -Basics  (The Edge GL1-025)

 

Thursday

10am-1pm:    Programming with R – Data Analysis and Visualisation  (The Edge GL1-025)

2pm-5pm:     Open access publishing and measuring research impact  (TBC)

 

Friday             

10am-1pm:   Beginner’s guide to the Library Makerspace  (The Edge GL1-025 and Makerspace GL1-03)

2pm-5pm:     Show and Tell (Data Visualisation Lab, GL1-029)

 

 

 

Session: Maximising the impact of research data 

Instructor: Armin Straube 

Description: The availability of data that is findable, accessible, interoperable, and reusable (FAIR) is improving research in all disciplines but requires data management throughout the research process. This session will enable the participants to plan their own research data journey from the start of their research projects through to publishing datasets.  The hands-on planning exercise will be based on the research projects of the participants.  

 

Session: Introduction to computational methods: Tidy Data and Regular Expressions 

Instructor: Armin Straube 

Description: The first part of the session will look at what makes data “tidy”, that is machine-readable and understandable by multiple software packages and programming languages. Demonstrations and explanations will be alternating with small hands-on exercises done by the participants with an example data set. The second part will look at Regular Expressions, a powerful way of finding, extracting, structuring, and cleaning data originating from textual resources that is supported by many software packages and programming languages. The session provides a good basis for learning to programm with R later in the week. 

 

Session: Special Collections and Archives as datasets 

Instructor: Dr Kirsten Mulrennan & Sinéad Keogh 

Description: This session will introduce a variety of Special Collections and Archives held in the Glucksman Library. It will explore the different types of records and data contained in heritage collections, and investigate a number of methods for analysing this data, including transcription, geoparsing, text analysis and crowdsourcing. 

 

Session: Data visualisation and exhibition tools 

Instructor: Sinéad Keogh & Caleb Derven 

Description: Using the data analysis methods explored in relation to Special Collections and Archives held in the Glucksman Library, this session will look at data visualisation tools and how researchers can use geographic, temporal and linked data to present datasets in new ways. 

 

Session: Data cleaning and enrichment with OpenRefine 

Instructors: Sinéad Keogh & Armin Straube  

Description: OpenRefine as a free tool to effectively clean, structure, enrich and format (tabular) data. Practical exercises will highlight the potential to save endless hours of manual data correction and to effectively use large datasets from various sources. 

 

Sessions: Programming with R  

Instructor: Armin Straube 

Description: R is a programming language for statistical computing, data analysis and visualisation. Open source and supported by a large community it can be adapted and extended with a wide range of 3rd party packages.  These two sessions are aimed at researchers with no previous programming experience and will make participants familiar with the underlying concepts and principles, enable them to write basic scripts themselves and understand and re-use scripts written by others, and make a start in using packages for data analysis and visualisation. Finally, it will lay the foundations for further self-guided engagement with programming.     

 

Session:  Open access publishing and measuring research impact 

Instructor: Ashling Hayes 

Description: Publishing your research outputs is a key component of academia. In this session we will give an overview of publishing Open Access and looks at ways to measure the impact of those publications. It is extremely difficult to “measure” the impact of an individual researcher or a research group on the discipline or society. Bibliometrics can help to broadly inform evaluation alongside qualitative, expert assessment and review. However, it is important that research metrics are used responsibly, in a fair, transparent and robust way. 

 

Session: Beginner’s guide to the Library Makerspace 

Instructors: Library Makerspace staff 

Description: The Glucksman Library Makerspace will offer an introduction to 3D Printing, Laser Cutting and T-Shirt refashioning - participants will then be invited to choose one of the following hands-on activities: 

• design and 3D print a small 3D model 

• create a ‘heat-transfer vinyl’ design to heat-press on to your own T-shirt or canvas bag 

• engrave or cut out a basic design on the Laser Cutter 

All materials except t-shirts / canvas bags, are supplied. Basic computer skills are desirable. 

 

Session: Show and Tell 

Description: In this session, we invite you to bring your own projects and data. There will be room to show successful utilization of the tools presented throughout the week as well as to discuss ideas and work in progress.