We have successfully connected research groups and initiated collaborations.
Background: At the start of the project, we wondered: “What data literacy offerings are already available in Saxony?” This led to the idea of compiling all existing offerings and visualizing them on an interactive map. Our research showed that other approaches to visualization typically involved significant effort — for example, information from various data sources often had to be manually collected and entered on a regular basis.
Solution: Come2Data contributed its own approaches to automated data collection and collaborated with partners from NFDI4Earth, NFDI4Energy, SaxFDM, and other initiatives. We conducted a joint workshop on this topic at Love Data Week 2025, followed shortly thereafter by a poster presentation at CoRDI 2025.
Result: Our collaboration resulted in the Come2Data Map — an interactive map that makes data literacy offerings in Saxony visible and thus easy to find; it also demonstrates how cooperation and technical approaches work together to strengthen FAIRness in science.
Clear guidelines make it easier to navigate complex data issues.
Question: Many people are confused when it comes to licenses: „Under which license should I publish this dataset? Am I doing anything wrong here?“ In one specific case, a researcher wondered whether simply marking a dataset with a Creative Commons license was sufficient to establish a legally sound basis for the use of her work; furthermore, she was unsure whether material properties and research data could be protected by copyright in and of themselves.
Solution: Come2Data created and provided two guidance documents: one on „Licensing Research Data“ and another on „Copyright in Research Outputs„. These documents explained the legal foundations and practical criteria for her specific use case.
Result: This case demonstrates that guidance documents are essential for quickly providing clarity. Especially when dealing with the legal aspects of research data — a topic often involving complex issues — guidance documents serve as clear and practical guidance for researchers.
For specific challenges, we connect you with experts.
Request: A doctoral student needed assistance with conducting a bibliometric analysis.
Solution: Come2Data forwarded the request to the SLUB Bibliometrics team, which possesses the necessary expertise.
Result: Through this referral, the doctoral student gained access to specialized expertise and a point of contact for further processing of her request.
Practical training strengthens the data literacy of students and faculty.
Request: As part of the 2025 Key Competencies Week at TU Dresden, Come2Data was invited to hold the workshop „Hilfe, wo sind meine Daten? – Daten sicher ablegen, organisieren und wiederfinden“ („Help, where are my data? – Storing, organizing, and retrieving data securely“).
Solution: We conducted the workshop: We explained the objectives, benefits, and basic methods of research data management.
Result: Using clear principles — illustrated with practical examples — participants learned the basics of research data management and gained clarity on how structured data storage and simple organizational rules simplify daily work by saving time and reducing frustration.
We develop materials and concepts that integrate data literacy into the classroom.
Request: There was a need to integrate web scraping and data harmonization into teaching within the context of empirical social research and to identify suitable training programs.
Solution: We developed a series of workshops on „Nutzung von Python für die Daten- und Textanalyse/Natural Language Processing (NLP) in den Sozialwissenschaften“ („Using Python for Data and Text Analysis/Natural Language Processing (NLP) in the Social Sciences“). The workshops covered the basics of Python, the use of relevant libraries, methods of text and data analysis, and applications of AI and machine learning. We also published a handbook to complement these workshops.
Result: Faculty and students received practical materials and training that facilitate the use of modern data analysis methods in teaching and promote sustainable skills.