Understanding data policies of economic and social science journals.
Renat Shigapov (Data Science Consultant in FDZ | Data Scientist for BERD@NFDI | Coordinator of the NFDI WG “Knowledge Graphs”)
Thomas Seyffertitz (Deputy Head of Collection Management at Vienna University of Economics and Business Library: Economics and Business Administration, Finance, Accounting & Statistics, Research Data Management)
From small coffee lectures to full-day workshops and flipped classrooms – the 𝗕𝗘𝗥𝗗 𝗔𝗰𝗮𝗱𝗲𝗺𝘆 reflects the demand for continuous education in rapidly evolving fields not covered by traditional curricula.
The BERD Academy is a substantial component of our Initiative. It is at the forefront of empowering researchers with accessible and free data science and management knowledge.
From the interview, you can learn more about BERD Academy’s mission, the diverse participant profiles, the instructors with practical expertise, and the innovative didactic approaches used to ensure effective learning.
📆 Tuesday, October 10, 2023 ⏰ 9 am to 5 pm (lunch break from 12 to 2 pm) 📍 LMU Munich
Why Discuss Data Culture?
Public statistics is more than just the application of statistical methods. In this workshop, you will become familiar with how different societal interests influence public statistics and how, in turn, information shapes public discourse.
Throughout the workshop, you will develop a fundamental understanding of data literacy and data culture, catering not only to data professionals but also to all users of data and statistics. We will explore the questions of how conventions are at the heart of the co-production of statistics and society — and what decision-making processes drive them. We will approach the answer by taking concrete case studies and questions from the current political landscape and trying to answer them with the best possible quantifications.
💡 Session 2: Values, Ethics, and What They Mean for Quality
📆 Wednesday, October 11, 2023 ⏰ 9 am to 5 pm (lunch break from 12 to 2 pm) 📍 LMU Munich
How are Values and Ethics Linked to Data Quality?
As with other products, public statistics aims to optimize the design (form) of the use (function) of the products (“form follows function”). In this respect, it is about more than just the application of statistical methods. Rather, the focus must be on the questions that society wants to have answered with solid statistics for its current, pressing, and conflict-laden issues. Other aspects then play a role here, namely whether politics values and finances this infrastructure, whether corresponding data literacy is available in the population at large, and so on.
In this workshop, you will gain a basic understanding of why ethics and values play such an important role when using data. You will get to know different ethical principles and discuss if they are still up-to-date with current developments and new data sources. By doing so, we will explore the relationship between quality of information, integrity, and governance.
📊 Session 3: Data 4 Policy: The Evolution from Statistical to Data
📆 Thursday, October 12, 2023 ⏰ 9 am to 5 pm (lunch break from 12 to 2 pm) 📍 LMU Munich
Let’s discuss the future of data, statistics, and society
New data sources and data science methods open up substantial opportunities for research and for improving statistics. However, the integration of traditional and newer methods requires more than the merging of methodology and technology.
In this workshop, you will discuss the differences between data-driven and question-driven approaches. We will explore in which places of society data plays an important role and how it is regulated. By this, we will expand on the triangle of data, facts, and policy. Let’s discuss the future of data and society!
Learn 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 and 𝗗𝗮𝘁𝗮 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 through our exciting new range of 𝗕𝗘𝗥𝗗 𝗔𝗰𝗮𝗱𝗲𝗺𝘆 courses scheduled for 𝗢𝗰𝘁𝗼𝗯𝗲𝗿 and 𝗡𝗼𝘃𝗲𝗺𝗯𝗲𝗿 2023. Join us for on-site workshops or participate online in interactive sessions.
Completely free of charge and open to everyone, we extend a warm invitation to 𝗲𝗻𝗴𝗮𝗴𝗲 𝗶𝗻 𝗱𝗶𝘀𝗰𝘂𝘀𝘀𝗶𝗼𝗻𝘀 𝗼𝗻 𝗱𝗮𝘁𝗮 𝗮𝗻𝗱 𝘀𝗼𝗰𝗶𝗲𝘁𝘆📊🌍, 𝗴𝗮𝗶𝗻 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗶𝗻𝘁𝗼 𝗲𝗻𝘀𝘂𝗿𝗶𝗻𝗴 𝘁𝗵𝗲 𝗿𝗲𝗽𝗿𝗼𝗱𝘂𝗰𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗼𝗳 𝘆𝗼𝘂𝗿 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵📓, or 𝗮𝗰𝗾𝘂𝗶𝗿𝗲 𝗺𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝘀𝗸𝗶𝗹𝗹𝘀 𝘄𝗶𝘁𝗵 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗮𝗹 𝘂𝘀𝗲 𝗰𝗮𝘀𝗲𝘀 𝗶𝗻 𝗢𝗳𝗳𝗶𝗰𝗶𝗮𝗹 𝗦𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝘀📈.
Picture a gathering of brilliant minds, all driven by the common goal of using data science to make the world a better place…🌈 🦄 – does that sound real to you?
We are excited to share that the Data Science for Social Good (DSSG) hands-on summer program, an exceptional 2-month full-time program has been launched in August, led by Frauke Kreuter and Bernd Bischl of the Munich Center for Machine Learning (MCML).
Many public mission-driven organizations, like educational institutions and NGOs, lag in data science adoption due to factors like limited funds or expertise. DSSG is working to change that!
Aspiring data science talents are joining forces and weaving together their expertise on projects that positively impact society.
Chosen teams will focus on:
➤ Developing a Fire Hydrant Range-Finder Web App to assist the disaster control (“Katastrophenschutz”) in Munich. ➤ Creating and analyzing a land sealing dataset to enhance climate change understanding.
Are you tired of the complexity and lack of transparency surrounding privacy laws?
Don’t worry, we’ve got your back! Our powerful tool is here to help you navigate through the intricacies of data protection regulations. Discover a new level of clarity and transparency as you navigate the world of data protection.
After the successful release of iVA1 and iVA2, we proudly introduce iVA3, the ultimate interactive Virtual Assistant designed to guide you through the examination of whether the processing of personal data within your research project meets federal or state legal requirements.
By asking specific questions, providing short examples, and offering precise definitions, iVA3 guides you through a decision tree tailored to your unique circumstances. It minimizes confusion and streamlines decision-making by providing clear and concise guidance, saving you time and effort.
Ready to experience the potential of iVA3 firsthand? Click here and try it out for yourself.
Are you fascinated by the potential of smartphone data to understand human behavior and society? Are you a data service provider or researcher looking to leverage the power of smartphone sensor data for your social research?
The IAB-SMART project has gathered valuable insights by combining in-app survey data with 1.3 million location observations derived from GPS and mobile network data. Now, we are excited to invite you to our three-part webinar series that will guide you through the process of collecting, processing, and utilizing smartphone sensor data for social research.
While attending the entire series is recommended, you are welcome to participate in individual sessions based on your interests and requirements. Here are the details of each webinar session:
📅 IAB-SMART 2: 𝗝𝘂𝗹𝘆 𝟬𝟱, 2023, 1 pm CEST – 2 pm CEST 🎙️ 𝗪𝗵𝗮𝘁 𝗱𝗼 𝗴𝗲𝗼𝗹𝗼𝗰𝗮𝘁𝗶𝗼𝗻 𝘀𝗺𝗮𝗿𝘁𝗽𝗵𝗼𝗻𝗲 𝗱𝗮𝘁𝗮 𝗮𝗱𝗱 𝘁𝗼 𝗮 𝘀𝘂𝗿𝘃𝗲𝘆 𝗽𝗮𝗻𝗲𝗹? – 𝗔𝘃𝗮𝗶𝗹𝗮𝗯𝗹𝗲 𝗶𝗻𝗱𝗶𝗰𝗮𝘁𝗼𝗿𝘀 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗜𝗔𝗕-𝗦𝗠𝗔𝗥𝗧 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 🗣️ Presented by Florian Zimmermann 💻 Register here
📅 IAB-SMART 3: 𝗝𝘂𝗹𝘆 𝟭𝟮, 2023, 1 pm CEST – 2 pm CEST 🎙️ 𝗛𝗼𝘄 𝘁𝗼 𝘁𝗶𝗱𝘆 𝗮𝗻𝗱 𝗮𝗻𝗼𝗻𝘆𝗺𝗶𝘇𝗲 𝗿𝗮𝘄 𝘀𝗺𝗮𝗿𝘁𝗽𝗵𝗼𝗻𝗲 𝗴𝗲𝗼𝗹𝗼𝗰𝗮𝘁𝗶𝗼𝗻 𝗱𝗮𝘁𝗮: 𝗖𝗼𝗱𝗲 𝗮𝗻𝗱 𝗣𝗿𝗮𝗰𝘁𝗶𝘁𝗶𝗼𝗻𝗲𝗿’𝘀 𝗘𝘅𝗮𝗺𝗽𝗹𝗲𝘀 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗜𝗔𝗕-𝗦𝗠𝗔𝗥𝗧 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 🗣️ Presented by Andreas Filser 💻 Register here
You will learn about the ethical and transparent collection of smartphone data, explore the research potential of geolocation smartphone data, and gain practical insights into tidying and anonymizing raw smartphone geolocation data.
Don’t miss this opportunity to expand your research toolkit and gain comprehensive insights into smartphone sensor data! Register now for the IAB-SMART Webinar Series by visiting the respective links provided above.
Text data plays a crucial role in the NFDI (National Research Data Infrastructure), particularly in the BERD@NFDI and Text+ consortia, which focus on research in Business, Economics, and Related Data (BERD@NFDI) and humanities (Text+). While these consortia cater to distinct communities and research inquiries, they share commonalities in their approaches, such as utilizing machine learning, language models, and other natural language processing techniques. The aim of the Joint Conference on Research on Text Analytics is to showcase various application domains and explore potential collaborations by examining shared methodologies.
Please find the program and the registration opportunity here.
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