Event Calendar

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

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".

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.

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

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.

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.

This course will provide participants who have basic skills in statistics and econometrics with an introduction to current core methods used in the analysis of observational, experimental, and quasi-experimental data.

Why is research data often less accessible than expected? What happened to the original idea of open access, and why are we moving away from it despite better tools and technologies? Instead of giving final answers, the webinar invites discussion. It looks at how open science can support transparency, fairness, and responsible data use. We’ll also talk about the risks of relying too much on specific platforms – especially when using AI – and why independent, ethical data practices matter.

Have any doubts or questions about your obligations as a Horizon Europe (HE) grant holder in terms of Open Access to publications and Research Data Management? We will present the HE requirements, followed by some time for your questions to our experts. You will also get a preview of the main tools and services OpenAIRE provides to help project coordinators and research support staff on the requirements' compliance.

The conference theme is “Promises and problems of new and alternative data sources and data formats for survey research. Methodological challenges and substantive conclusions”.  The conference shocases the latest survey research and offers a number of professional development opportunities, including short courses and awards.

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.

Der Online-Workshop informiert über urheberrechtlichen Fragen bei der Nutzung generativer KI-Systeme. Im Fokus steht dabei die Weiternutzung von KI-Output in Lehrveranstaltungen – auch im Rahmen von offenen Bildungsmaterialien (Open Educational Resources (OER)).

Working towards Open Scholarship in the Age of Intelligent Automation is the FSCI 2025 theme. FSCI organizers seek course submissions contributing to and exploring this theme, though all ideas in scholarly communication are welcome for consideration. The theme will also shape the institute’s plenary events.