Day 1 Love Data Week 2026

  • FAIR data and how to check fairness of your data

    In this webinar Hannah Mihai (DeiC) introduces you to the FAIR principles and its importance to make data reproducible and aligned with research code of conduct(s). You will also learn how to define the FAIRification rationale for your data by using self evaluation tools such as (e.g. F-UJI or FAIR evaluator) and get practical tips on how to get started to enhance it’s FAIRness.

  • Where will my data end up?

    In this webinar Rosa Lönneborg (KTH) introduces a few of the numerous data repositories where you can deposit research data. In this session you will learn more on how to select a good repository. And instroduce factors to consider when selecting a suitable repository to deposit data as a part of a trustworthy research practice - and to increase the impact of your research as well. Some examples of research data from KTH data repository , Zenodo and the Swedish researchdata.se portal will be shown.

  • WA quick introduction to Data Management Plans

    In this webinar Jeremy Azzopardi (Chalmers) introduces Data Management Plans (DMPs) and their usefulness as a tool for keeping track of resaerch data and potential issues which may arise during the research process.

Day 2 Love Data Week 2026

  • Visualize Research and Data

    In this webinar Mattias Vesterlund (KTH) introduces you to how to visualize different types of research data in various contexts. A picture is worth a thousand words, but how do you best communicate your results visually?The webinar goes through what to consider when visualizing data and research results, both graphical aspects of data visualization and how to reason about colour choice, layout and choice of charts and graphs.

  • BRIGHT Data Catalog - Developing A Research Data Management Infrastructure

    In this webinar Ding He (BRIGHT, DTU) shares his experiences and opinions to solutions that turn scattered research data into a coherent and well-governed assets. He shares strategies for integrations of lab data, computational analyses, lab data and DMP. This presentation aims to stimulate discussions for architectural choices, lessons learned, and common pitfalls when building an end-to-end research data management infrastructure.

Day 3 Love Data Week 2026

  • Searching for research data

    The aim of FAIR data is to have, where possible, research data open and accessible to review and reuse. The present reality complicates data’s findability in a myriad of ways not least of which is the decentralised nature of research data repositories and indexes that characterise the data publishing landscape. In this presentation Sacha Zurcher (Royal Danish Library) discuss how a network of library research support staff in Denmark, have developed a workshop designed to enhance the competencies of researchers to search for published data.

  • Introduction to OpenRefine

    OpenRefine is a powerful free, open source application for cleaning up messy data and transform the dataset into other formats. This webinar given by Jeannette Ekstrøm aims to inspire you to get started with OpenRefine.

Some talks from Love Data Week 2025

  • This talk “Whose Data Is It, By the Way?”, hosted by Siamak Nakhaie, will provide a simple and clear overview of researchers’ rights to the data they create, licensing options, and effective ways to share data.

  • Discover how to locate reliable open datasets for academic or professional projects, and learn about key resources, search strategies, and tips for evaluating data. Facilitated by Ahmad Pratama, PhD.

Project presentations from previous Love Data Week events

  • Brought to you by the CAAL-CBPA Research Data Management Committee for Love Data Week

    Presenters: Elizabeth Stregger, Data and Digital Services Librarian, Mount Allison University; Sabrina Sandy, Upper-Year Cognitive Science Student, Mount Allison University

    Description: Data-related AI tools and assistants are permeating the Internet. Will these out-of-the-box tools help students and researchers organize their data? How do they compare to traditional tools like Excel, OpenRefine, and R? In this session, we will organize a dataset for future users by using a variety of tools. We will then discuss factors to consider when selecting software, such as the learning curve, documentation, cost, and reproducibility

  • Professor Bettina Migge, UCD School of Languages, Cultures and Linguistics, talks about her use of research data during Love Data Week (February 13, 2018) in UCD Library.