Understanding research and data lifecycles is foundational in many work settings, not limited to academia. In this workshop, we give an overview of research and data lifecycles, review data management practices and give an understanding of how to differentiate between different data and software license types. We explain the use of persistent identifiers, such as DOIs (Digital Object Identifiers), the FAIR principles for data (Findable, Accessible, Interoperable, and Reusable) and how to apply them by means of metadata and standards for efficient (research) data management. We will also describe the components of a Research Data Management (RDM) infrastructure, discussing differences between repository systems. All these topics will help with understanding the challenges of digital data preservation, planning and implementing reproducible experiments, as well as the application of Open Science principles.
 

Agenda

• Introduction: Why does data management matter? What is the data lifecycle?

• Best practices: What does it take to manage data?

• Making your data reproducible: Persistent Identifiers and FAIR principles

• Data management Plans - Prepare your data right from the beginning

• Repositories (this is RDM infrastructure)

• Wrap-up & QnA

Goals & Learnings

• Gain a foundational understanding of research and data lifecycles

• Learn best practices for effective data management

• Differentiate between various data and software license types

• Understand the role of persistent identifiers (DOIs) and how to apply the FAIR principles

• Explore different research data management infrastructures and repository systems

• Develop strategies for ensuring data preservation, reproducibility, and Open Science compliance

Place & Time

• 27.03.2025 from 09:00 - 12:00

• Where: Seminarraum Argentinierstrasse, Argentinierstr. 8, Argentinierstrasse 8 od. Paniglgasse, EG, 1040, Wien

Additional Information

This workshop will be held in English and is organised in cooperation with TU Wien Innovation Incubation Center. 

Trainers

Tomasz Miksa

Tomasz Miksa is a Senior Scientist at TU Wien, Centre for Research Data Management and Faculty of Informatics. He works in digital transformation for research data management, making data management more automated and machine-actionable. This includes improving the interoperability of research data repositories and ensuring data is FAIR (Findable, Accessible, Interoperable, and Reusable) and reproducible. He is an experienced researcher in the domain of data management and has a PhD from TU Wien in the “Verification and Validation of Scientific Workflow Re-executions”.
 

Florina Piroi

Florina Piroi is a Senior Scientist at TU Wien, Centre for Research Data Management and Faculty of Informatics. She is involved in interdisciplinary and Industry-related projects in the domain of data science, focusing specifically on data analytics/machine learning and underlying processes. She received her PhD degree from the Johannes Kepler University, Linz, Austria, where her work concentrated on the management and retrieval of mathematical knowledge and automatic theorem provers. She is also an Information Retrieval researcher with experience in domain specific search and search engine evaluation.