Why Searching for Research Data Deserves More Attention

In the era of Open Science, sharing research data has become increasingly common – to a large degree driven by funder requirements but often made possible by services and infrastructure offered by universities and Non-Profit Organizations, such as OpenAIRE. However, while more data are available than ever, finding it remains a challenge. Researchers often face dead ends, vague metadata, and scattered repositories. The FAIR principles —Findable, Accessible, Interoperable, and Reusable— describe a set of properties of the data, metadata, and repositories in which they reside. Applying the FAIR principles is a prerequisite for findability, but they do not address the ability of researchers to search for data. This skill exists independently of the data and supporting infrastructure.

Another challenge is that researchers often need data that are not necessarily created through a research project but by public authorities, Non-Governmental Organizations, and other institutions. These datasets may very well be appropriate for research but are often not made public in accordance with the FAIR principles.

At the Royal Danish Library, we have seen firsthand the difficulty in locating relevant datasets. This inspired us to create a workshop that focused solely on data discovery. Our goal was to help researchers develop practical strategies to find and evaluate research data.

The workshop introduces both direct and indirect search methods, encouraging participants to explore repositories, bibliographic databases, and even AI tools. We emphasize that data search is iterative and often unpredictable, more like exploration than a checklist. Serendipity is often a factor.

To support the broader adoption of our course, we published the course materials as an Open Educational Resource (OER). The materials included slides in both Danish and English, a teacher's guide in English, and useful handouts. The course can be adapted to the needs of the teacher, from a full-day workshop to a 30-minute add-on to existing courses on research data management. These resources aim to make it easier for teachers to create courses that fit their needs at their local university and to support data searching as a more visible and supported part of the research workflow.

To make our course materials as easy as possible to find and reuse, we made them FAIR with a CC-BY-NC license through the open e-learning platform LearningLib.

In addition, we created a website that revisits key concepts of the course and provides additional information and resources such as good places to search for data.

If we want data to be reused, we must first ensure that it can be found. This starts by recognizing data search as a skill worth teaching, developing, and investing in. We hope that our contribution to this developing field can help others train researchers in finding the data they need.