Eventkalender

Die Erstellung von Lehr- und Lernmaterialien mithilfe von Software gehört für viele Lehrende zum Alltag. Doch nicht jedes Programm eignet sich uneingeschränkt für OER. In diesem Spotlight zeigt unsere Juristin exemplarisch, worauf bei den Nutzungsbedingungen zu achten ist, und welche Programme OER-freundlich sind – und welche eher nicht.

This 2-day conference will mark the culmination of The University of Manchester’s Opening up Research programme 2024/2025 and is a collaborative effort by the Office for Open Research, the School of Engineering Open Research Lead, the UK Reproducibility Network, and the Cancer Research UK Manchester Institute. The conference brings together researchers from across the disciplines to explore the latest advances and to discuss important topical questions being posed by society around open research and integrity.

Unsere  Coffee Lecture-Reihe „Forschungsdatenmanagement und Wissenschaftspolitik“ gibt Einblicke in die wissenschaftspolitischen Beweggründe und Akteure hinter der Stärkung des FDM. Neben dem wissenschaftspolitischen Kontext gehen wir auf  aktuelle FDM-Anforderungen wichtiger Drittmittelgeber für die anwendungsorientierte Forschung ein und geben Ihnen einen Einblick, wie Sie die neuen Standards erfolgreich umsetzen.

Friederike E Kohrs, Research Fellow at Charité BIH QUEST Center for Responsible Research, talks about Strategies for making reproducible research and open science training the norm at research institutions.

"Concerned about the reproducibility and transparency of research? Interested in learning more about meta-research, or the science of science? Looking for hands-on experience? Excited to work with other early career researchers across disciplines?"

Meta-analysis encompasses a broad set of methods to conduct a systematic, quantitative review of the literature in order to derive empirical generalizations. This workshop will deal with methods for conducting a meta-analysis. The purpose is to train the participants to conduct and publish a high-quality scientific meta-analysis within the broad field of management research.

Wir wollen die Synergien an der Schnittstelle von Open Education und Open Science gemeinsam ausloten und durch einen intensiven Austausch zwischen den Akteur:innen Potenziale beleuchten, die sich aus einer engeren Zusammenarbeit der jeweiligen Akteur:innen ergeben. Anhand verschiedener Schwerpunkte werden in interaktiven Formaten konkrete Ideen thematisiert, wie Open Education und Open Science voneinander lernen und als Treiber der digitalen Transformation in der Hochschulbildung fungieren können. In verschiedenen Formaten der Tagung werden zudem auch weitere aktuelle und relevante Themen wie Demokratiebildung und Künstliche Intelligenz thematisiert.

Got an assignment coming up and don't know how to start? Our online seminar (in English) teaches you essential research and writing skills in a 30-minute session. The topic of this session is "Avoid unintentional plagiarism".

How do machines learn to make the right choices? How can individuals, firms, organizations, and researchers use automated decision-making?

This course provides an introduction and intuition for designing algorithms that allow machines to learn based on reinforcements. Reinforcement learning provides decision rules based on learning from partial, implicit, and delayed feedback.

This is particularly useful in sequential decision-making tasks where a machine repeatedly interacts with the environment or users. Reinforcement learning is well known for its successes in robotic control, autonomous vehicles, game playing, and chat agents. In business, economics, and the social sciences, there is a recent explosion of applications including temporal difference learning and adaptive experiments.

The course includes 4 live Online Meetings, in which you will discuss the week’s contents with the instructor and fellow participants:

Meeting 1: June 17, 4:30pm-5:30pm CEST
Meeting 2: June 24, 4:30pm-5:30pm CEST
Meeting 3: July 08, 4:30pm – 5:30pm CEST
Meeting 4: July 15, 4:30pm – 5:30pm CEST

Der erste Tag startet wie gewohnt mit einer Einführung in das Forschungsdatenmanagement, gefolgt von der Verleihung des FAIRest Dataset Award, und schließt mit einem Überblick über die aktuellen Thüringer Aktivitäten im Bereich Forschungsdatenmanagement ab. Am zweiten Konferenztag stehen Softwarelösungen zur kollaborativen Zusammenarbeit im Umgang mit Forschungsdaten im Mittelpunkt. Ergänzt durch Erfahrungsberichte aus der praktischen Anwendung.

Im Vorfeld zur Jahrestagung QUADRIGA findet das Barcamp statt. Du arbeitest wissenschaftlich mit Daten oder vermittelst in Deiner Lehre Datenkompetenzen? Du entwickelst Open Educational Resources oder forschst zu Future Skills in der Hochschullehre? Du hast Lust auf interdisziplinären Austausch oder möchtest Gleichgesinnte an Deiner Arbeit im Feld der datenbasierten Wissenschaften teilhaben lassen? – Dann ist das Barcamp genau das Richtige für Dich!

Als vom BMBF gefördertes Datenkompetenzzentrum für die Wissenschaft widmet sich QUADRIGA der Vermittlung und Stärkung von Datenkompetenz für die Forschung. Die diesjährige Jahrestagung markiert die Halbzeit der Projektlaufzeit und möchte gemeinsam mit der Community den Fokus auf Strategien, Best Practices und Outputs für die Vermittlung von Datenkompetenz legen. Neben dem Blick auf die vergangenen anderthalb Jahre soll zusammen an weiterführenden Ideen, Konzepten und Policies gearbeitet und mit anderen Akteur:innen im Bereich Datenkompetenzen in den Austausch getreten werden. Dafür interessiert uns insbesondere, was Strategien und Best Practices, aber auch konkrete Herangehensweisen und Outputs in der Datenkompetenzvermittlung sind.

Struggling to turn data into something useful for your research? Wondering how to assess the reliability of AI-generated insights? Finding it challenging to choose the right algorithms and methods for effective data analysis? If these or similar questions sound familiar, then join the EconData Workshop for practical input you can apply immediately. This is your chance to bring up the challenges that matter most to you.

This event describes the author’s journey from traditional academic publishing to choosing a new, scholar-led OA press for books. It addresses some of the common questions, roadblocks and concerns academics encounter around OA publication, such as the assumed necessity of a publication charge and the concern that OA books will be of lower quality. It outlines the work that a new UK nonprofit, the Open Book Collective, is doing to provide authors with reputable high quality OA book publication options without the need for BPCs. It will also explore the importance of Open licensing for academic works, and plans for a peer support network for academic authors wishing to play an active role in the transition to an equitable, sustainable landscape for OA books.

This is the latest in the series of regular free webinars from the UK Research Integrity Office on research integrity and related issues.

What does a ‘good’ research culture look like? This event will explore how research culture could be measured in a way that supports ongoing improvement, without imposing burdens or bureaucracy. Speakers will explore how this might be implemented throughout the research community, to help organisations feel more confident that their research systems, policies, environment and culture promote high quality and ethical research.

Roman Gerlach (TKFDM, Friedrich-Schiller-Universität Jena) talks about Data Publishing and the requirements of the Publishers.

The abundance of text data and the advent of powerful deep learning models has led to rapid advancements in Natural Language Processing (NLP). However, adapting models to specialized tasks still requires a nuanced understanding of the data. This adaption often requires human-annotated data that are considered to be time-consuming and labor-intensive. Active Learning addresses this by strategically involving humans in the learning loop, selecting instances for annotation that are most likely to maximize performance gains. This approach not only optimizes human effort but also enhances the model’s adaptability to specific tasks with fewer annotated instances, making the training process more efficient and effective. In this workshop you will get introduced to the concepts of Human-In-The-Loop Learning and (Deep) Active Learning. In a hands-on practical session, you will design a (Deep) Active Learning Cycle using Python.

Many scholarly fields conduct descriptive research about the research process. Advocates and reformers have prescriptive ideas about how the research process might be improved. Policymakers, funders, publishers, and other stakeholders enact changes to the social and technical infrastructure of research. All have an interest in whether changes and reforms have their intended effects or unintended consequences that might accelerate or inhibit advancement, translation, and application of research. Together, these researchers and stakeholders are the research and development pipeline for improving the system and practice of research. The Metascience 2025 Conference will bring these communities together to share ideas, evidence, and foster a culture of continuous experimentation and improvement

A global gathering for knowledge sharing, community building, and opportunities to define a roadmap of research and intervention priorities to accelerate science.

Many scholarly fields conduct descriptive research about the research process. Advocates and reformers have prescriptive ideas about how the research process might be improved. Policymakers, funders, publishers, and other stakeholders enact changes to the social and technical infrastructure of research. All have an interest in whether changes and reforms have their intended effects or unintended consequences that might accelerate or inhibit advancement, translation, and application of research. Together, these researchers and stakeholders are the research and development pipeline for improving the system and practice of research. The Metascience 2025 Conference will bring these communities together to share ideas, evidence, and foster a culture of continuous experimentation and improvement.