Parallel Session 11

Parallel Session 11 – Managing Responsibly Research Data

Moderator: Liisi Lembinen, University of Tartu Library, Estonia
Location: Tassos Papadopoulos – Room 104 (1st Floor)

11.1) Long live the knowledge! Proper metadata and how it is created with URN and other persistent identifiers

Presenters: Riitta Koikkalainen and Ulriika Vihervalli, National Library of Finland, Finland

Metadata matters, especially if you wish your digital objects to live long and flourish. Currently most people turn to search engines when in need of information on any subject. But no search engine knows anything other than what it is told. Telling is not possible without names or locations. In the era of digitalisation, high quality machine-readable metadata and machine-actionable identifiers have become more important than ever before.

With this in mind, the National Library of Finland has been providing persistent identifier services to higher education and cultural heritage organisations since the late 1990s. This free-of-charge, actionable and persistent identifier URN – Uniform Resource Name – is an internet standard able to encompass other identifiers under the same umbrella. URN is not limited to identifying documents, but rather it can be assigned to any kind of digital object. The functionalities of URNs are rather similar to DOIs and they can be used in similar ways, but they are not mutually exclusive. The URN standard includes sophisticated functionalities that can be tailored to the namespaces. However, there have been no practical implementations of this as of yet.

Based on feedback from URN end users as well as our in-house specialists, we now have developed new versions of the National Library of Finland’s open-source URN harvester and resolver. This aims to improve the use of persistent identifiers as means of interaction. The new features make integration of URNs easier and smoothen the flows of information. For example, the current URN resolver distinguishes between normal URLs and legal deposit URLs, allowing it to inform the end user if the object is only available in the legal deposit collection. Previously, mapping functioned as one-to-one. Now mapping functions as one-to-many.

By using URNs, one serves libraries, search engines, and, at the end of the day and most importantly, the end users. URNs realise FAIR by making the identified object findable, accessible and re-usable.

11.2) From Theory to Practice: Embedding RDM Competencies into Data Management Plans

Presenter: Jukka Rantasaari, University of Turku, Finland

In response to Research Data Management (RDM) challenges, a collaborative effort between researchers and support experts at two Finnish universities led to the creation of a “Basics of Research Data Management” (BRDM) course. Since 2019, this 4-track, 3 ECTS course has been underpinning doctoral students’ and postdocs’ understanding of RDM, drawing on initial interviews that highlighted the need for improved data management planning, particularly in the areas of intellectual property, data sharing, and data documentation.

Participants of the BRDM course reported significant enhancements in their RDM capabilities, reflecting positively on their research design and adherence to data handling, documentation, and legal and ethical standards. However, they expressed a need for concrete examples to navigate the integration of legal and privacy guidelines into their RDM strategies effectively.

Our analysis of the participants’ Data Management Plans (DMPs), assessed against the Finnish DMP Evaluation Guide’s criteria, revealed a satisfactory median performance. However, significant variations were noted in data sharing, storage, and preservation practices among different disciplines and course tracks. Moreover, DMPs incorporating a data table containing a structured overview of the data types being handled, provided a more comprehensive and detailed description of data lifecycle compared to purely narrative DMPs.

This presentation synthesizes these prior findings to scrutinize the practical application of RDM competencies in DMPs. It evaluates how course-derived skills are manifested in actual RDM planning and the corresponding sections of the DMPs. The focus is on understanding what constitutes RDM competencies, their development during the BRDM course, and their reflection in participant feedback and self-assessments. Furthermore, it examines how these competencies are operationalized within DMP sections and exemplified through best practices detailed in DMPs.

The insights gained serve multiple stakeholders: they guide researchers in enhancing their data management, assist institutions in evaluating and supporting planned RDM practices, and enable funders and publishers to delineate their data management requirements. Ultimately, this contributes to the transparency, integrity, reliability, and reproducibility of research.

Looking ahead, our research will delve into the nuances of RDM competencies across different disciplines, research methodologies, and data types. We aim to explore how the epistemic cultures of various scientific domains, which shape the production and dissemination of knowledge, reflect in data lifecycle practices and the competencies required.

11.3) Roadmap for Planning National RDM Expert Education – Finland’s Approach

Presenters: Anne Sunikka, Aalto University, Finland and Manna Satama, University of Eastern Finland, Finland

In light of the advancing open science landscape, the significance of research data and effective data management has become increasingly pronounced. Adhering to FAIR principles, researchers are encouraged to share their metadata and research data, fostering efficiency and reducing overall time, effort, and costs within the research community. Competence in good research data management (RDM) is now an essential skill for researchers.

The question arises: How do researchers acquire RDM skills? This is where the support of research data management personnel, known as data stewards, data librarians, or data curators, becomes crucial. Currently, training for these support roles primarily takes place on the job and through self-study, alongside their primary responsibilities within, for example, higher education, research infrastructures, or libraries. While lectures or webinars on RDM topics are better than nothing, they do not provide a comprehensive and systematic approach to building RDM competences. Additionally, the vague and unfamiliar nature of RDM professional tasks makes it challenging to plan a career in this field.

To address these shortcomings, the Professionalizing of RDM Experts Working Group, functioning under the Finnish National Coordination for Open Science and Research, devoted two years (2022-2024) to outlining a roadmap for planning an RDM education program tailored to Finland.

This presentation details the roadmap for developing Finnish RDM expert education, covering various steps such as building awareness of the need for RDM education, outlining the main content of the education, and determining the organizer of the education. The final two steps of the roadmap—identifying a sustainable business model for the educational offering and establishing trust and appreciation for the education—will be primarily managed by the organizer, Tampere University. The presentation emphasizes the importance of ongoing dialogue with stakeholders and international collaboration, following the successful model set by the University of Vienna’s Data Steward training.

Furthermore, the presentation delves into how the working group operated, its key participants, and the time invested in the project. Our aim is to provide an example for other countries interested in establishing a systematic training program comprising a modular curriculum tailored to the needs of diverse sectors, including research organizations, public administration, and companies.

53rd LIBER Annual Conference