Veranstaltungskalender

Increasing Transparency, Integrity, and Trust in Research is the FSCI 2024 theme. FSCI organizers seek course submissions contributing to this theme, though all ideas in scholarly communication are welcome for consideration. The theme will also shape the institute’s plenary events. With the increasing prominence of AI, it is essential that the research and scholarly communication communities emphasize transparency, enhance integrity, and renew trust in our community’s work. We hope to focus on these components as we present courses on topics within the scholarly communication ecosphere.

Work on your problems related to the session’s theme with the help of others! We will run some mini peer code review! Bring small pieces of your code along and discuss it with others over pastries! Any level and any programming language welcome!

Data Science for Social Good (DSSG) is a two-month summer program where two teams of fellows collaborate on real-world data science projects, aiming to create a meaningful impact for the social good.

Open Access (OA) is a well-established mode of distributing scholarly research that impacts academic libraries and librarians at every level. We all have a role to play in this rapidly evolving landscape. If you’re feeling unclear on foundational concepts, or want a refresher, this session is for you. We’ll cover the basics, including definitions, the development and aspirations of the OA movement, approaches, challenges, and what basic outreach might look like, as well as entry level resources for learning more. Zero previous experience is expected or required. This session is the anchor of a three-part series which also includes OA Case Studies and Emerging Issues in OA.

Discuss Data is a community-centred repository for archiving, sharing and discussing research data on Eastern Europe, the South Caucasus and Central Asia. It goes beyond ordinary repositories as it combines research data management functions with a discussion platform for the community-driven quality assessment of research data. Questions of data quality gained especially importance in the context of the Russian Aggression against Ukraine, as there is an increasing debate within the area studies focussing on that region about reliability, validity, transparency and other aspects and challenges related to research data quality.

In dieser Veranstaltung lernen Sie die Merkmale offener Bildungsmaterialien kennen und reflektieren deren Chancen und Herausforderungen. Besonderes Augenmerk liegt auf dem Urheberrecht und der offenen Lizenzierung. In interaktiven Übungen erfahren Sie, wie Sie offen lizenzierte Bildungsmaterialien in Ihre Lehre einbinden können und was bei der Erstellung eigener OER zu beachten ist. Gemeinsam nehmen wir didaktische Fragen rund um OER in den Blick und diskutieren Qualitätsdimensionen offener Bildungsmaterialien

This session will deepen your understanding of Open Access by providing a set of specific case studies. We will discuss three major areas of work: supporting OA through licensing agreements and policies, empowering scholars with new literacies, and supporting access and discovery through repositories. Each area will be grounded in the work of specific institutions which run the gamut from large public R1s to smaller regional institutions. We will also invite you to share case studies from your own institution and those that inspire you. We hope you will leave with a clearer sense of what Open Access looks like on the ground and a set of compelling models for doing the work at a diverse set of institutions, including your own.

Do you ever feel that the data you need for your research is accessible but it’s not in a convenient table, such as company reports or building plans? Perhaps the information you need is spread out across many different documents? If only we could read and extract structured data from thousands of written documents. In this course, we explore how to accomplish this task by combining web scraping, Optical Character Recognition (OCR), and Natural Language Processing (NLP). Over four weeks, we provide online lessons and interactive sessions to learn the fundamentals of these key technologies.

The course includes 4 live Online Meetings, in which you will discuss the week’s contents with the instructor and fellow participants: 27. Aug. / 03. Sep. / 10. Sep. / 17. Sep.

Profitieren Sie von den vielseitigen Beiträgen und Workshops zur Produktion und Nutzung frei verfügbarer Lehr- und Lernmaterialien und erfahren Sie in den Best-Practice-Beispielen, wie der Einsatz und die Erstellung von OER gelingen kann – passgenau für Ihr Fach!

This course focuses on quantitative empirical accounting research, covering theoretical, methodological and technical aspects of this research program. It also introduces students to the concepts of Open Science. In terms of applications, it concentrates on financial and non-financial reporting issues but also touches on some managerial and auditing topics. The dates of this course are: 03.09. / 06.09. / 10.09./13.09.

Dieser Snack bietet eine kompakte Einführung in das Thema Datenschutz speziell für Forschende. Erfahren Sie, welche rechtlichen Rahmenbedingungen Sie bei der Verarbeitung personenbezogener Daten beachten müssen und wie Sie diese praktisch umsetzen können. Im Fokus stehen das Datenschutz-Infoportal und die neue Checkliste „Datenschutz für Forschungsvorhaben“ der Universität Bremen. Diese Ressourcen bieten Ihnen eine konkrete Hilfestellung bei der DSGVO-konformen Planung und Durchführung Ihrer Forschungsprojekte.

Do you want to learn how to make use of text data for your research? This in-person workshop is ideal for researchers who want to learn the potential of Natural Language Processing (NLP) and Large Language Models (LLMs) for economic and related research. You will receive a broad overview of the theoretical foundations of NLP and its practical concepts. The workshop closes with a Coding Lab to apply this knowledge to real world problems.

This event will provide a forum for discussions about evidence-based data metrics and responsible assessment of open data. Our summit last year highlighted that there are strong foundations for data metrics, but also a need to raise awareness and pursue conversations about data evaluation across sectors. By hosting this second Make Data Count Summit next September, we want to provide a dedicated venue for continued engagement with this topic. 

Summit will explore how data metrics can inform responsible assessment of open data usage. Over two days, we will foster a common understanding of existing data metrics and the infrastructure and practices that support them, learn about the latest developments in the collection and applications of data usage information, and discuss necessary next steps in infrastructure, policy and evaluation processes to forward adoption of evidence-based data usage metrics.

The Barcamp Open Science is a barcamp dedicated to the Open Science movement. It is open to everybody interested in connecting with like-minded people embracing Open Science, unlocking new perspectives and networking on Open Science, and thriving Open Science together!

Do you want to learn how to make use of text data for your research? You will receive a broad overview of the theoretical foundations of NLP and its practical concepts. The workshop closes with a Coding Lab to apply this knowledge to real world problems.

By joining (or accessing the material after the school), you will learn how to: clarify your research design and set up your statistical plans in advance of collecting data to prevent biases in analyses, with the help of preregistration and data simulation; create computationally reproducible workflows so you can be more efficient and spot mistakes in data wrangling or analyses, through programming with version controlled scripts; prepare, manage and share data and code in connection with your articles by applying the Findable, Accessible, Interoperable, Reusable principles, and using adequate repositories and licenses. Increase the impact of your research and secure the acknowledgement of your and others contributions by opening your research practices!

Das Tagungsmotto lautet „Offene Bildung: Durch Technologie, Transparenz und Nachvollziehbarkeit die Zukunft gestalten“.

As demonstrated in our earlier sessions, Open Access (OA) has gained traction over the last three decades, and its principles and practices are widely applied across scholarly disciplines. That application has surfaced a number of issues that have complicated the adoption of OA—particularly its effectiveness in advancing equity. As OA has evolved, so have the possible barriers to adoption and dilemmas in whose interests are prioritized. This session will explore some of the ways in which the aspirations and benefits of OA are complicated by the legal, technical, and sociocultural context in which we work.

Participants of this course will learn how to conduct and publish a high-quality meta-analysis in the area of management and business research. To this aim, the course follows a step-by-step procedure that covers the entire meta-analysis research process, including problem formulation and definition of a research question for a meta-analysis, literature search, study and effects coding, data preparation and analysis with different software tools, and reporting and publishing. Participants will further learn how to evaluate meta-analyses in the business and management literature and to follow the respective methodological discussion about meta-analyses in their field.