Research Data: Services

I am happy to talk about all  research data related topics: armin.straube@ul.ie.

Some funders require a Data Management Plan for funding applications or after you have been awarded funding. I can review your DMP and give feedback. Please do allow at least 5 working days before any funding deadline for this.

The Glucksman library runs many workshops and trainings, Research Data Management being one of the topics covered. Below is a list of workshops regularly held at the library. Upcoming sessions are scheduled in the Library Calendar.

I am also happy to organise training sessions for specific groups of researchers in your department. Please do get in touch: armin.straube@ul.ie.  

Training: Research Data Management

The availability of data that is findable, accessible, interoperable, and reusable (FAIR) is improving research processes in all disciplines. Publishing data sets enables data re-use and the validation of research results and can bring attribution and citations.  Producing high-quality data sets however requires data management throughout the research process.

To set researchers towards a course to best practice data management, this half-day online training will: 

• explain the FAIR data principles,
• have a look at Data Management Plans and the topics covered in them,
• feature a hands-on planning exercise based on the research projects of the participants, 
• demonstrate how data sets published by others can be found,
• walk the participants through the steps for publishing their own data and
• discuss the data support services available at the University of Limerick.

The workshop will enable the participants to plan their data management from the start of their research projects and will be particularly (but not exclusively) useful to researchers required to hand in a Data Management Plan with their funding agency.

Booking via the Library Calendar.

Training: Tidy Data in Spreadsheets

Good data organization is the foundation of any research project. Spreadsheets programmes like Excel can be used to structure data but give a lot of freedom to do it inefficiently.

This workshop will teach “tidy” data practices, structuring data in a machine-readable way to maximize the utility of the data. The aim is to create data sets that are interoperable with each other and could be used in a multitude of software applications or in programming languages like R or Python.

This half-day training covers:

• good data entry practices and formatting of data tables,
• how to avoid common formatting mistakes,
• approaches for handling dates as data,
• basic quality control and data manipulation in spreadsheets and
• exporting data from spreadsheets.

This workshop is not about data analysis or visualization with spreadsheets.

Demonstrations and explanations will be alternating with small hands-on exercises done by the participants on their own machines with an example data set. This workshop will be useful for any researcher working with data in spreadsheets and is based on Data Carpentry lessons.

Booking via the Library Calendar.

Training: Data Cleaning with OpenRefine

OpenRefine is a powerful free and open-source tool specifically designed to effectively clean, structure, enrich, and format (tabular) data. It has the potential to save endless hours of manual data correction and its functionality to track and record all changes can help with the reproducibility of research.  

This half-day training will:

• introduce the basic functions of OpenRefine like filtering and sorting,
• show ways to identify and corrected errors in data sets,
• teach how to format data in a consistent and machine-readable way,
• show how to import and export data and the attached processing steps.

Participants will need to install OpenRefine before the workshop (guidance will be provided) and demonstrations and explanations will be alternating with small hands-on exercises done by the participants on their own machines with an example data set.

This workshop will be useful for any researcher working with large tabular data sets. Some familiarity with managing data in spreadsheets is assumed. The workshop is based on Data Carpentry lessons.

Booking via the Library Calendar.

Training: Python Introduction

Python is a general-purpose programming language widely used in 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. It is a good language for new programmers to learn due to its straightforward, object-oriented style and its readability.   

This training is aimed at researchers with no previous programming experience. The workshop will make participants familiar with the underlying concepts and principles, enable them to write basic scripts, and understand and re-use scripts written by others. Finally, it will lay the foundations for further self-guided engagement with programming.    

Participants will need to install Anaconda before the workshop (guidance will be provided) and demonstrations and explanations will be alternating with small hands-on exercises done by the participants on their own machines during the workshop.

The workshop is based on Data Carpentry lessons.

Booking via the Library Calendar.

Armin Straube, Research Data Manager (armin.straube@ul.ie)

Please do get in touch for all things research data.