RDMeasurement – Development of a quality assurance model for Research Data Management (RDM) in the Humanities
This poster briefly describes my PhD-project, which focuses on the abstract modeling of RDM needs and services within the Arts and Humanities. I am developing a protocol-template for RDM consultations, identifying categories of RDM demands and developing a formal language to describe RDM. All this is done on the basis of inductive category building in the sense of a summarizing content analysis which I am performing on documentations of RDM consultations.
My goal is to consolidate, professionalize and measure RDM both qualitatively and quantitatively. This will in turn make it possible to control RDM activities, make reliable statements on actual RDM and evaluate service and organization structures. In addition, I am modeling generic workflows to cope with RDM needs and strategies in the context of RDM consultations. In sum, I intend to define and establish a comprehensive framework on RDM, covering at least the Humanities.
Click on the poster image to enlarge
The Data Center for the Humanities (DCH) is the first contact point for researchers in the Arts and Humanities at the University of Cologne - and not only - whenever there are any questions on RDM. Similarly to the aims of the Research Data Alliance, our main goals are (1) supporting researchers to make reseach data open in the sense of the FAIR-principles, (2) working in and establish comprehensive networks disciplinary and interdisciplinary and (3) raising awareness on RDM through training.
In this context, my research on standardization of RDM-structures and -workflows, on the theorization of RDM-requirements and the modelling of RDM-landscapes, is touching central aspects of various RDA working and interst groups, e.g. the standardization and implementation of data policies, the development of education and training standards on handling reseach data or common standards for DMPs.
I am looking forward to having a fruitful exchange with other researchers, experts and colleagues in the field of RDM, in order to get to know other approaches, strategies and points of view.
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 RDA_Melbourne_Helling.pdf | 2.07 MB |
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Author: Rob Hooft
Date: 01 Apr, 2020
Hi Patrick,
Have you considered looking at the FAIR principles in order to suggest RDM practice?
It can be helpful to walk through the FAIR principles, and identify the ones that can be accomplished using relatively small changes in RDM processes and achieve immediate results for re-usability.
Author: Patrick Helling
Date: 01 Apr, 2020
Hey Rob,
thank you a lot for your comment! Indeed, the FAIR principles are very present to my work: they are fundamental for my daily business as a data manager at the Data Center for the Humanities (DCH). I am also part of the GO FAIR Data Stewardship Competence Centers (DSCC) Implementation Network: as well as on other topics, we also focus on the definition of comprehensive competence standards for data stewards related to the FAIR principles, which is actually one of the goals in the context of my PhD as well, at least as far as the Humanities are concerned.
Anyway, the FAIR principles are very important for RDM. From my point of view, they have of course a very high impact on RDM processes and they must be taken into account while modeling theses processes. Within my analysis and standardization processes the FAIR principles are always a prominent point of orientation. Categories for RDM requirements, standardized workflows and the formal description model for RDM in the Humanities is already (in its actual status) dependent on the FAIR principles and it will and neeeds to be so in the future too!
Author: Ryan O'Connor
Date: 06 Apr, 2020
Hi Patrick,
Interesting poster and project! You mention that you will be conducting a quantitative analysis of RDM protocols; from where will you get the data on these protocols? Are you producing your own dataset or using an existing one (or combination of both)?
Author: Patrick Helling
Date: 07 Apr, 2020
Dear Ryan,
thank you for asking. These protocols represent the documentation of conseling sessions. For example, when researchers come to us at the Data Center for the Humanities (DCH) at the University of Cologne with a question on research data management, we conduct a consultation and record in writing what the conversation is about. I anonymize these protocols, analyze them qualitatively inductive in terms of content and develop a coding system through which information units can be identified. Finally, I will also analyze these information units quantitatively in order to be able to make statistical statements about the actual RDM landscape (starting from the local context and widening up the perspective later on).
At the moment I have 90 protocols, which have been produced during the consultation sessions at the DCH. At the same time, I am in contact with colleagues from other RDM competence centers so as to include their documentation of consultations in my analysis.
I hope that answers your questions, otherwise feel free to ask again.