About BERD

Research Symposium | June 10-11

The BERD Research Symposium, organized by the consortium BERD@NFDI, is scheduled for June 10-11, 2024. The event encompasses conference-style sessions and a young researchers’ colloquium, fostering collaboration and exchange of information in research in business, economics, and social science. The event’s primary focus is the collection, pre-processing, and analysis of unstructured data such as image, text, or video data.

The event kicks off on June 10, 2024, with a keynote on the planned research data law, held by Prof. Dr. Thomas Fetzer (University of Mannheim). The afternoon is split into two simultaneous tracks “Big Data Analytics” and “Big Data Harvesting and Collecting,” covering various topics: The sessions of the first track focus on “Searching and Finding Existing Unstructured Data Samples Online“, “Advanced Data Crawling” (Prof. Dr. Reto Hofstetter, University of Lucerne) and “Applications in Collecting and Preparing Unstructured Data from Images (OCR)“, while the sessions of the second track explore “Best Practice Preprocessing“, “Text Mining – State-of-the-Art 2024” and “Image Mining – State-of-the-Art 2024.”

The second day, June 11, 2024, starts with a keynote from Prof. Dr. Stefan Feuerriegel (LMU) on “NLP to achieve the Sustainable Development Goals”. Afterward, the BERD Community Event will host a colloquium for young researchers, featuring research presentations challenging unstructured data. 

Throughout the event, participants can engage in discussions, explore hands-on applications, and stay updated on the latest advancements in Big Data Analytics and unstructured data challenges. Additionally, including the young researchers’ colloquium ensures a platform for emerging scholars to share their work and insights. The agenda reflects an informative program catering to a diverse audience interested in the intersection of data science, analytics, and open science principles.

  • There is no participation fee for the conference.
  • In addition, we are happy to inform you that we were able to secure extra funding that allows us to support young researchers with respect to their travel expenses. Conditional on your submission to the Young Researchers Colloquium, we will reimburse travel expenses up to the amount of EUR 500 for the first 15 submissions (expenses for transportation + hotel). Proof of travel expenses must be provided. We will inform you about the travel support once we receive your submission. Please, find our detailed travel expense reimbursement conditions here.

For more information, please visit the Symposium’s website.

Register here.

We look forward to meeting you in Mannheim,

Conference Co-Chairs:

Prof. Florian Stahl (Mannheim University)
Prof. Hartmut Höhle (Mannheim University)

Scientific Committee:

Dr. Matthias Assenmacher (LMU Munich)
Dr. Lars Gemmer (University of Cologne)
Prof. Marc Fischer (University of Cologne)
Prof. Sibylle Lehmann-Hasemeyer (University of Hohenheim)
Prof. Goeran Kauermann (LMU Munich)

About BERD

BERD@NFDI is a research data infrastructure dedicated to transforming the way Business, Economic, and Related Data are managed.

With a special focus on unstructured data, such as images, videos, audio, and text files, we provide a comprehensive suite of services and tools. These tools facilitate the searching, collecting, indexing, processing, analyzing, and preserving both data and algorithms, simplifying your data management needs throughout the entire research process.

Our approach aligns with FAIR (Findable, Accessible, Interoperable, and Reusable) principles, ensuring that your data is not only efficiently managed but also conforms to the highest standard of data integrity and accessibility. 

In furtherance of our commitment to improving research practices, we are actively working to consolidate our services into a robust, unified platform. Explore the beta version of the platform here.

Tools and Services

Knowledge Graphs

We develop Knowledge Graph infrastructure for German company data distributed over many providers, registers, and periods. Many valuable datasets are still confined to analogue books. We use a variety of algorithms to OCR, structure, and semantify the unstructured data and to create knowledge graphs.

interactive Virtual Assistant

iVA is an online tool that simplifies understanding data protection regulations and legal data usage options. It offers tailored guidance through a decision tree with practical, directly applicable information.

Algorithms for Data Science

This open dictionary compiles text and image algorithms and is specifically designed for social science research. Users can utilize the tool to discover suitable algorithms for their data or contribute by sharing their own algorithms.

BERD Academy

Our BERD Academy provides a wide selection of courses, workshops, and educational content encompassing various aspects of data science and data management.