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Introduction to Research Data Management – Project- and Data Management (FAIR Data)

Veranstaltungsdaten

Event language: English

Science is becoming increasingly digital, data-driven, and collaborative. This event will provide a general overview of methods, strategies, and tools to help you manage your digital data and collaborate more efficiently.
Digital research data is on the rise: Most research projects generate and/or collect digital data, thus requiring researchers to learn how to handle data responsibly and proactively. Not only do we need to manage and annotate our data; we should also preserve our data and make them available for re-use by publishing them in accordance with FAIR (findability, accessibility, interoperability, and reusability) open data principles. Research data management begins even before the data is collected: A detailed project plan helps to manage research data and make workflows transparent throughout the entire research cycle.

While data management seems to imply plenty of work and little benefit initially, it does come with considerable personal and practical advantages in the longer term: 

• Well-managed and annotated data are easier to sort, retrieve, and understand, thus boosting research efficiency.
• High-quality data management can shield you from accidental data loss.
• Funding organizations often require a detailed data management plan before the start of a project. A reference to published project plans can also be essential for the subsequent publication of your research results.

What is more, good research data management is a vital ingredient in fostering open science because sharing your data responsibly makes it available to the scientific community, enabling further investigations by others.

 Qualification Outcomes 

• You will know the basics of research data management.
• You will know how to publish your data and, if applicable, your code in line with FAIR principles.
• You will be able to formulate data management plans. 
• You will have a clear understanding of the research-data-management and advisory services at Philipps-Universität Marburg.

This event is an introduction to research data management. If you already have more specific questions, you are welcome to get in touch with us directly by e-mailing eresearch@uni-marburg.de.

Methods

Trainer input, group work, plenary discussions & reflection, exercise on own dataset

Requirements 

To participate in the event, you need a PC/laptop (no tablet!) with a current browser and an internet connection via the university network or your own hotspot. We recommend preparing a dataset from your project including the related information and bring it with you to work on during the event.

Proficiency in English at the B2 level of competency or higher is required.

Date

October 20, 2026, 9 am–1 pm

This workshop is available in German on March 8, 2027.

Target group

Doctoral candidates and postdocs from all disciplines

Modalities

Maximum number of 15 participants
Free of charge

Registration

Please register until October 5, 2026 using the online registration form.
This event is offered as part of the MARA "Open Science" program and of Datikum, the "Marburg Datikum programme".