Webinar on FAIR Data, 15.12.2023, 10:00 - 11:30
This webinar looks at FAIR data from two perspectives. First, participants learn how they can use recent advances in AI for FAIR data sharing, and second, the webinar provides expert advice on how to share research data upon publication. The presentation focusses on data policies in economic and social science journals, however, the data policies should also be relevant for other research areas.
Optimizing FAIR Data Sharing with ChatGPT (Renat Shigapov)
Implementing FAIR data sharing principles in practice can be complex and labor-intensive. This presentation will illustrate how ChatGPT can facilitate this process. We will: (1) explore ChatGPT's role in automating the creation of rich metadata, crucial for enhancing data findability; (2) provide practical examples of how ChatGPT assists in establishing clear data access protocols and usage guidelines; (3) demonstrate ChatGPT's support in selecting appropriate vocabularies and ontologies for seamless data integration; and (4) discuss ChatGPT's capability to generate comprehensive documentation and recommend suitable data licenses, which are essential for ensuring data reusability. Attendees will acquire valuable insights into utilizing ChatGPT for more efficient and user-friendly FAIR data sharing.
What you should know about the data policy of economic and social science journals. (Thomas Seyffertitz)
When submitting a research paper to a journal, it is increasingly required that the underlying data (i.e., research data) be provided or referenced. Especially in top journals, this has become mandatory in recent years. Consequently, it is essential for authors to familiarise themselves with the data guidelines of the respective journal. In this webinar, we will use some examples of data guidelines from various publishers and journals to show you what you should look out for before submitting a scientific article. First, we will show where you might find the respective data guidelines. We will then explain some of the features of such data guidelines using examples and introduce you to specific elements in individual journals: When and in what form should data be provided? What can I do if sensitive or licensed data is used in the work? To this end, we have analysed relevant guidelines from renowned economic and social science journals and compiled the most important findings. This should help to raise awareness of the journals' data guidelines and help authors to recognise potential pitfalls.
This is an open online event with registration via Google Forms:
After registration, we will send you the link for the webinar.
We invite participants to send us their questions before the workshop (deadline: 5.12.23). Please use the text field in the registration form to send us your questions and we will do our best to address them in the webinar.
Dr. Renat Shigapov
Data Science Consultant in FDZ | Data Scientist for BERD@NFDI | Coordinator of the NFDI WG “Knowledge Graphs”
Mag. Thomas Seyffertitz
Deputy head of Collection Management at WU Library: Economics and Business Administration, Finance, Accounting & Statistics, Research Data Management.