Preprints
Filtering by Subject: Data Literacy
Matching Data Life Cycle and Research Processes in Engineering Sciences
Tobias Hamann M.Sc., Michèle Robrecht, Max Leo Wawer, et al.
2024-06-20 Data Governance, Data Infrastructure, Data Literacy, Data Management Software
Research data management (RDM) has become increasingly significant, focusing on ensuring the most benefit from data creation. This especially applies within the engineering sciences, where many different sources generate big amounts of heterogeneous data. However, integrating RDM into day-to-day work is difficult. Thus, methods need to be defined to effectively and conveniently manage research [...]
How to teach good research data management to next generation researchers?
Syed Ashfaq Hussain Shah, Frank Petzold
2024-04-11 Data Governance, Data Infrastructure, Data Literacy
These days research work is subject to comply with FAIR principles. Additionally, it is subject to the practices of Open Science. Different stakeholders e.g. DFG are setting the goals of reproducible research work. This not only requires adequate handling of data but also the record of related information and practices during the research work. In this way, different tools and workflows are being [...]
Data-Producing Methods in CRC 985: Recommendations for Research Data Management in Large Interdisciplinary Projects
Sonja Herres-Pawlis, Nicole Andrea Parks, Konstantin W. Kröckert, et al.
2024-03-07 Data Literacy
Within CRC 985, groups from a variety of chemical institutes, chemical engineering, physics, and the life sciences collaborate on research on microgel systems. Over a funding period of nearly 12 years, the CRC has produced numerous publications, which are associated with a large amount of underlying research data arising from many different methods. To gain a deeper understanding of this [...]
A survey on the dissemination and usage of research data management and related tools in German engineering sciences
Tobias Hamann M.Sc., Amelie Metzmacher, Patrick Mund, et al.
2024-02-28 Data Governance, Data Infrastructure, Data Literacy, Data Management Software
As the amount of collected and analysed data increases, a need for data management arises to ensure its usability. This also applies in research. This challenge can be addressed by Research Data Management (RDM), which brings clear focus on the reusability of data. To understand the status quo of the application of research data management in engineering sciences in Germany, as well as possible [...]
Towards categorizing ethical questions in data literacy
Samira Khodaei, Anas Abdelrazeq, Ingrid Isenhardt
2023-05-12 Data Ethics, Data Literacy
Data Literacy is crucial for a sustainable engineering education [11]. In aiming to find solutions to solve future challenges, mechanical engineering has started to integrate data literacy into the higher education curriculum [13]. However, ethics are rarely considered in current frameworks. Ethics are seen as a side topic or are equated to data privacy issues [2]. Since literacy aims to empower [...]
PIA - A Concept for a Personal Information Assistant for Data Analysis and Machine Learning of Time-Continuous Data in Industrial Applications
Christopher Schnur, Tanja Dorst, Kapil Sajjan Deshmukh, et al.
2023-05-05 Data Governance, Data Literacy
A database with high-quality data must be given to fully use the potential of Artificial Intelligence (AI). Especially in small and medium-sized companies with little experience with AI, the underlying database quality is often insufficient. This results in an increased manual effort to process the data before using AI. In this contribution, the authors developed a concept to enable inexperienced [...]
Beyond Data Literacy in Engineering Education
Samira Khodaei, Mihail Padev, Anas Abdelrazeq, et al.
2023-01-24 Data Ethics, Data Literacy
Data literacy is a key ingredient for engineering education [14]. Through digital transformation, more data are generated in different scientific fields that will be interpreted. As a highly applicable scientific field, mechanical engineering is predestined to integrate data literacy into the higher education curriculum [17]. However, current frameworks rarely consider ethical questions, [...]