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Title:

Survey data of teaching and guiding DMP (Data Management Plan) to next generation researchers

Document type:
Forschungsdaten
Publication date:
18.11.2025
Responsible:
Hussain Shah, Syed Ashfaq
Authors:
Hussain Shah, Syed Ashfaq; Petzold, Frank
Author affiliation:
TUM
Publisher:
TUM
Identifier:
doi:10.14459/2025mp1835864
End date of data production:
15.10.2025
Subject area:
DAT Datenverarbeitung, Informatik; EDU Erziehungswissenschaften; INF Informationswesen, Bibliotheks-, Dokumentations-, Archiv-, Museumswesen; WIS Wissenschaftskunde
Resource type:
Experimente und Beobachtungen / experiments and observations; Umfragen und Interviews / surveys and interviews; Statistik und Referenzdaten / statistics and reference data; Textdokumente / text documents
Data type:
Bilder / images ; mehrdimensionale Visualisierungen oder Modelle / models; Texte / texts; Tabellen / tables; Programme und Anwendungen / software and applications
Description:
During their course of study and research work participants are provided training and support to manage their research data. At the end of training and support sessions, organisers usually conduct surveys to gather feedback and to evaluate approaches and effectiveness.
Such a survey was conducted at the end of the first phase (from 2020 to 2023) of the TRR277 AMC, a large Collaborative Research Centre (CRC) funded by German Research Foundation (DFG). Research workloads in such centres are usually distributed among various teams and institutions which may geographically be located at distinct locations. The participants come from different domains with varying skills and competencies. Researchers in these centres use and generate heterogeneous, large amount of data. In contrast to typical general guidance, training activities and courses which are usually based on theories, general purpose learning and qualification, the guiding and training activities in such projects/ settings are more oriented towards formal practices, quick adoption and implementation.
The survey was carried out to assess and rate the teaching & guiding practices/ methodologies conceived during that period for good management of research data. The training and support topics/ contents, concepts and approaches were developed for in person, digital medium as well as for hybrid environment. The participants of the survey were recipients of the materials and events of teaching & guiding, and took part in managing the actual research data.
This package of data contains survey data, software code and generated analysis. Data in this package relates to the activities for Data management plans (DMP). For survey data relating to the Research data management (RDM), please refer to the data package “Survey data of teaching and guiding RDM to next generation researchers” available at https://doi.org/10.14459/2025mp1835865
Data in this package consists of R Quarto, CSV, PDF, HTML/ JS/ CSS and PNG file formats. The R Quarto file contains R code for data analysis. The survey responses submitted by the respondents are in PDF and CSV file formats. The compiled results are in HTML and PNG file formats. A PDF file of the compiled results has also been provided as an example. However, HTML and PNG formats have been preferred output formats for textual, tabular and image data.
The analysis of data has been presented through simple descriptive statistics using R. However, it could be further analysed and used for complex descriptive as well as inferential statistical analysis.
The code of R Quarto file may conveniently be served as basis for Web/ digital form applications and may also be altered by the relevant groups as per their own preferences/ demands.
Links:

https://doi.org/10.14459/2024mp1735029

Key words:
Survey; Survey data; Teaching and training; DMP; Data management plan; Dynamic data management plan; RDM; Research data management; CRC; Collaborative research centre; FAIR data; Research data; Open science
Technical remarks:
View and download (49,6 MB total, 8 Files)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1835864):
rsync rsync://m1835864@dataserv.ub.tum.de/m1835864/
Language:
en
Rights:
by, http://creativecommons.org/licenses/by/4.0
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