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Among other objectives, the Open Research movement seeks to assure transparency in research methods and accessibility to existing data for secondary analysis.  How does this work with qualitative data? What points should one consider when designing qualitative research? Where do the limitations lie? Does open research archiving also present opportunities?  Dr. Pat Danahey Janin, Independent Researcher, University of Essex will give an overview of where qualitative research sits within the open research movement and address these questions through examples of practical experiences.

The importance of open research is widely accepted by many in the research ecosystem with touted benefits for research impact, integrity, reproducibility. Democratising research through open research is widely valued. But are we lagging when it comes to recognising and rewarding the work done by the wide range of researchers, research enablers and others involved in the culture of research? In this session we hear from three experts in the space of embedding institutional reward and recognition practices.

Karen Desborough from the UKRN’s OR4 project will discuss its community of practice – a largescale national initiative to reform how open research is recognised and rewarded in researcher assessment. Delphine Doucet will from the University of Sunderland will discuss their institutional engagement with the OR4 community of practice and Georgina Endfield from the University of Liverpool who will discuss the institutional changes underway through Project Thrive.

The Royal Society’s Science in the Age of AI report, published in May 2024, states that research funders and scientific communities should ensure AI based research meets open science’s principles and practices to realise AI’s full potential in advancing science.  In this session, Nicole Mwananshiku, Policy Adviser at the Royal Society, will explore the report’s key findings, focusing on the roles of transparency, reproducibility, and equity in ensuring trustworthy and inclusive AI-driven research.

Eine umfassende Dokumentation trägt zur Nachnutzbarkeit von Forschungsdaten bei. Lernen Sie, wie effektives und qualitativ hochwertiges Dokumentieren geschickt in den Forschungsalltag integriert werden kann.

here is an ecosystem where open research is increasingly prioritised with a range of frameworks, concordats, policies and recommendations for increasing open research practices. Monitoring and evaluating uptake of open research practices helps us to understand compliance with policies, gain insight on the impact of engagement with open research practices and evaluate the effectiveness of those policies and recommendations. However, the research ecosystem brings together a wide range of inputs with considerations to be made on the appropriateness of open research practices. Moreover, the range of open research practices available to us is myriad. How do we measure, monitor and evaluate open research practices accurately and responsibly?  

In this session, Laetitia Bracco will present the French Open Science Monitor, a national tool designed to steer French public policy regarding Open Science. She will explain the background, methodology and outcomes of this project which currently covers scientific publications, clinical trials, research data and software.  

Iratxe Puebla will talk about Make Data Count, an initiative that promotes the development of open data metrics to enable evaluation of data usage. Iratxe will discuss how data metrics offer an opportunity for a fresh approach to evaluating usage and impact, and share updates from Make Data Count projects that aim to scale the data usage information available to the community, enhance the context of usage measures, and advance adoption of data evaluation.

In this session Dr John Shaw will introduce FORRT, share some of their projects, such as the Replication and Reversals Project, and introduce their latest Project- POSTEdu, a pedagogically-informed, evidence-based, self-guided program for supporting the teaching of Open Science.   

The Framework for Open Reproducible Research Training (FORRT) provides a pedagogical infrastructure & didactic resources designed to recognize and support the teaching and mentoring of open and reproducible science. 

Most of the time we talk about open research within our own communities and yet open research can have a greater impact and affect than we realise outside of academia.  In this session we will be hearing from two colleagues:  Dr Andi Skilton, who  helped set up and is Chair of Trustees for the small charity Stargardt’s Connected, will talk about being open from his charity’s perspective and Professor Pooja Saini, who carries out research with small charities, will talk about the issues she has faced balancing her research aims, her collaborators’ aims and being as open as possible. 

Security and privacy are key aspects in developing and maintaining trustworthy systems. A lack of security results in vulnerable systems that are exposed unprotected to potential attackers and are presenting an incalculable economical and personal risk. As personal data has become the new currency in the digital era, its protection from unauthorized processing and distribution is a key issue to preserve the privacy and self-determination of individuals.

ReproducibiliTea is a journal club initiative that has resulted in journal clubs about open science and replicability in academic departments all over the world (see https://reproducibilitea.org/ for more history and information). IGDORE is now proud to announce our own ReproducibiliTea journal club fully online, allowing people to join from wherever they happen to be in the world!

This journal club is suited for beginners to open science. To fully understand what the open science movement is built upon, we will cover important basic concepts and discuss the most seminal works. Each session will be based on an article which all participants read in advance. Depending on the session topic, other resources such as Youtube videos or optional reading may be provided to facilitate the discussions. These will always be optional; you are never expected to prepare more than reading the session article.

Everyone is welcome – from student to Nobel Prize laureate; from intern to CEO. No prior knowledge is required to participate, but the article discussions will probably be more valuable to you if you have a university-level understanding of quantitative and/or qualitative research methodology

SQL (Structured Query Language) und darauf aufbauende relationale Datenbanken ermöglichen es, Daten strukturiert abzulegen und abzufragen. Im Zuge dieses Hands-on-Workshops werden Grundkenntnisse und Konzepte zum effizienten Abfragen von Forschungsdaten mittels SQL vermittelt. Ziel des Workshops ist es, Sie mit der Abfragesprache vertraut zu machen.

Verwendete Methoden des digital durchgeführten Workshops sind Live-Coding, Einzelübungen, Plenums- und Gruppenarbeit sowie Diskussions- und Reflexionsrunden, die durch Fallbeispiele ergänzt werden. Der Workshop wird von Rabea Müller (ZB MED) ausgerichtet. Es werden keine besonderen IT-Kenntnisse vorausgesetzt.

Data science approaches are based on statistical/mathematical methods as well as computer science competences. In this context, it is crucial to understand the basic principles of statistical methods. This will help to adequately apply statistical methods and to produce reliable statistical results.

Wikidata ist eine offene und freie Datenbank in der heterogene Informationen in Form eines Wissensgraphen (Knowledge Graphen) abgelegt und abrufbar sind. Ziel ist es, eine menschen- und maschienenlesbare, interdisziplinäre sowie multilinguale Ressource bereitzustellen. Als Teil der Linked Open Data Cloud wird dabei auf offene Standards wie RDF oder SPARQL aufgebaut. Durch diese Eigenschaften ist Wikidata auch sehr attraktiv für das Forschungsdatenmanagement. Im Zuge dieses Hands-on-Workshops werden Sie mit den zugrundeliegenden Konzepten und der Nutzung von Wikidata als auch mit verschiedenen Werkzeugen wie Scholia im FDM-Kontext vertraut gemacht.

Verwendete Methoden des digital durchgeführten Workshops sind Einzelübungen, Plenums- und Gruppenarbeit sowie Diskussions- und Reflexionsrunden, die durch Fallbeispiele ergänzt werden. Der Workshop wird von Dr. Till Sauerwein und Rabea Müller (ZB MED) ausgerichtet. Es werden keine besonderen IT-Kenntnisse vorausgesetzt.

Nach einer inhaltlichen Einführung durch das Projektteam, referieren Expert:innen zu konkreten Handlungsoptionen hierzu. Anschließend erarbeiten wir in Kleingruppen handhabbare Lösungen für das Publikations- und Kostenmonitoring im Kontext institutioneller Repositorien. Die Ergebnisse des Forums werden durch das Projektteam in Form einer Handreichung dokumentiert. Insgesamt werden so die Entwicklung von Best Practices im Bereich der Informationsinfrastrukturen auf nationaler Ebene unterstützt und die Vernetzung der Open-Access-Professionals gefördert.

The theme of RDAP Summit 2025 is Evolutions in Data Services: Forging Resiliency. We encourage proposals that explore concepts such as technical, human, and organizational durability and flexibility in response to challenges and changes in research and data service needs.

Our next topic will be “Artificial Intelligence and Open Science”. More information will follow.

In this workshop we will identify what impact is (and isn’t), the different types of impact and the potential ‘reach and significance’ of your research. You will reflect on how well prepared you are to create and capture impact and look at the important role played by your stakeholders. You will leave the session having made a good start on your Impact Map, which will provide a useful guide for you as your research evolves.

A comprehensive management of research data is part of each research project and belongs to good scientific practice. It accompanies each phase of a research project – from the proposal phase via data acquisition and data analyses to the publication phase. The overall goal of research data management is the production of findable (F), accessible (A), Interoperable (I) and reusable (R) – FAIR – data sets.

A good stewardship of data (following the FAIR principles; Wilkinson et al., 2016) and an open data culture (Nosek et al., 2015) foster reproducibility as well as sustainability in science and makes up the fundament for data science applications.

Uta Wehn, Associate Professor of Water Innovation Studies at IHE Delft Institute for Water Education, The Netherlands, talks about Citizen Science.