An Empirical Study of the State of Research Data Management in the Semiconductor Manufacturing Industry

This is a Preprint and has not been peer reviewed. This is version 3 of this Preprint.

Authors

Dirk Ortloff, Sabrina Anger, Martin Schellenberger

Abstract

The paper presents insights into the situation concerning research data management (RDM) in the high-tech manufacturing industry and respective research institutions. Besides standards and guidelines, data management and its degree of formalization play a decisive role in digital transformation in all organizations. The authors of this study benefited from the opportunity arising within the framework of the European collaborative project iDev4.0 to evaluate RDM in the industry as well as in research institutions of different sizes and orientations. The study focuses on RDM-related soft criteria (e.g., understanding, awareness, value assessment) but also the concrete implementation of RDM. For this survey, the team conducted expert interviews and evaluated them using a qualitative analysis oriented to Mayring’s approach [1]. The results provide insight into the attitude of involved stakeholders towards RDM on the one hand and its practical implementation on the other. Identified commonalities, differences, and needs of the different parties are presented in this paper.

Comments

Comment #56 Dirk Ortloff @ 2023-09-25 08:30

The comment of Kevin Logan requesting a revised version came after the upload of a major revision fixing most of the reviewer's comments. Because the project is already over, the requested extension on the interviewed base of entities is not possible anymore. Therefore, we would like to ask the reviewers to have a second glance.

Comment #47 Kevin Logan @ 2023-08-30 17:08

As the editor responsible for this publication, I wish to thank the reviewers for their diligent work. In light of the considerable methodological flaws highlighted in the review, I ask the authors to respond to the reviewers in a detailed comment and address the issues highlighted in their comments in a majorly revised version of the manuscript. The reviewers will be asked to evaluate whether the shortcomings have been expunged in the revision.

Invited Review Comment #45 Ina Heine @ 2023-08-14 11:16

 Content:

The authors conducted a qualitative study about the state of RDM based on semi-structured interviews with 7 participants (6 industry representatives, 1 research institution), which are all part of an EU project called iDev4.0. The study’s objective was “to evaluate the current status with regard to RDM and derive future potential for cooperation, improvement and digital transformation”. For this, the authors applied principles of qualitative content analysis.

 

Overall assessment:

The addressed topic is very interesting and of high relevance for both research and practice. It is well suited for ing.grid’s scope and target audience. However, the study’s insights seem to be rather limited and more general than the paper’s main title suggests, i.e. without apparent relevance especially for manufacturing. This might be mainly related to some methodological issues (identification of research gap, questionnaire development and sampling).

For instance, the sample size is very small and has been sampled by convenience, which does significantly reduce the study’s conclusiveness. I am aware that the authors mention this in line 128, but there is no explanation/reasoning of why this “spotlight investigation” is relevant and suitable for meeting the stated objective. In addition, there is no information provided on who (in terms of profession, experience etc., also brief company profiles should be provided à size, industry, etc.) participated for the respective organization as interviewee, how long each interview took, there are no transcripts, how many others people were approached, how were they selected? I could also not find the questionnaire or a reference to where to find it. It is stated that the questionnaire was developed based on a literature review, but there are no references given. The introduction should be shortened and more to the point, especially considering the paper’s title and relevant prior research.

If it is not possible to extend and rerun the study, I would recommend to include the mentioned methodological details and add a discussion section, which also includes the study’s limitations and implications. Furthermore, I would recommend to provide more context when presenting the results as they do – in their current form of presentation – not really meet the study’s objective or add much to the existing field of knowledge.

 

Some minor points:

-       Line 95: Naming of figure 3 before figure 2

-       Line 99: Reference to Figure 15?

-       Value of Figure 3 (à mere text)

-       Value of “FAIR” – Figure? (no title/numbering)

-       Check language use

Invited Review Comment #35 Jan Linxweiler @ 2023-07-16 12:41

Content:

The authors conducted an in-depth survey within the EU project iDev40 to gain insight into the landscape of RDM in the high-tech manufacturing industry as well as respective research and development institutions. The motivation for the survey is the relevance of RDM in the digital transformation of organizations in general. A special focus is put on the degree of formalization of RDM.

Section 1 provides all the general background information for the study and the respective project.

Section 2.1 looks at the history and the current state of open data programs and initiatives in Germany and the EU in general.

Section 2.2 gives the definition of specific terms like RDM and FAIR. 

Section 3 describes the approach of the survey and its implementation and analysis from the methodological perspective. The team chose a qualitative survey based on expert interviews. For that, the interviewers developed a questionnaire as a guideline for the interviews.

Section 3.1 gives a details view of how the questionnaire was conducted and structured.

Section 3.2 explains how the individual interviews were done. 

Section 3.3 details how the interviews got analysed following a qualitative content analyses approach by Mayring. The authors point out the survey is not focussing on a complete view of research data management in the industry nor on quantitative results. 

Section 4 starts with a summary of the results and continues listing result details in the following sections 4.1 to 4.4

Section 5 gives a conclusion. 

Overall assessment:

The article "State of Research Data Management in Industry and Research Institutions in the Manufacturing Industry" is well-written and easy to follow in the first three sections, but needs improvements in sections 4 and 5. 

Relevance:

RDM is without a doubt of high relevance for the digital transformation process not only in academia but also in industry.

Major Improvements: 

Section 3 starts with a summary of the survey results and is then continued with sections 4.1 to 4.4 mainly listing key points. These sections do not provide much value as the context is often missing. I would highly recommend creating a continuous text from the bullet-point listing. Along with this, I propose to provide a section for the discussion of the results from which the Conclusion is derived. Currently, there is no connection between the results and the conclusion. Furthermore, the conclusion is relatively short in relation to the scope of the survey and the mentioned. It might be helpful to re-structure the sections: "results", "discussion" and "conclusion".    

Minor Improvements:

- Add a reference to Mayring's approach in the abstract

- DOI for reference [9] missing

- Text in Figure 1: font size too small (not readable)

- Text in Figure 2 and Figure 6: font size seems to be rather small, too

- Style of references in lines 36-49 is not consistent with the rest

- Consistent capitalization of "data management plan" 

- Lines 81,82: repetition "at least"

- Line 110 should be on the previous page

- Line 137 should be on the previous page

- Line 221: The abbreviation "RDM" has already been introduced (line 8) and has been used before line 221 multiple times

- Line 220: repetition: "in many"

- The structure of the text in lines 228 to 249 needs to be improved (mixture of isolated sentences and bullet points)

- Lines 228 to 287: Some sentences are ending with a "full stop", others don't.

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Metadata
  • Published: 2023-06-07
  • Last Updated: 2023-08-30
  • License: Creative Commons Attribution 4.0
  • Subjects: Data Infrastructure, Data Management Software
  • Keywords: RDM, State of affairs, Industry, Institutes, State of affairs, Industry, Institutes
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