Data Management in Collaborative Interdisciplinary Research Projects—Conclusions from the Digitalization of Research in Sustainable Manufacturing

Wang, Wei Min; Göpfert, T; Stark, Rainer

doi:10.3390/ijgi5040041

Cited by 14 publications

(9 citation statements)

References 24 publications

(19 reference statements)

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“…Some CRCs focus on establishing technical infrastructures (e.g. Wang et al 2016, Weber & Piesche 2016, Willmes et al 2014, while other CRCs apply the concept of an ' embedded data manager' (Cremer et al 2015). Nevertheless, only about 10% of all funded CRCs have successfully applied for and include an INF service project providing RDM support (Redöhl 2016).…”

Section: Discussionmentioning

confidence: 99%

Supporting the Interdisciplinary, Long-Term Research Project ‘Patterns in Soil-Vegetation-Atmosphere-Systems’ by Data Management Services

Curdt

2019

Data Science Journal

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Science conducted in cross-institutional, interdisciplinary, long-term research projects requires active sharing of data, documents and further information. Thus, within the Collaborative Research Centre/Transregio 32 'Patterns in Soil-Vegetation-Atmosphere Systems', funded by the German Research Foundation, research data management (RDM) services have been available since early 2007. These services were established to support all researchers during their entire individual research studies. They cover provision of general guidance, support and training for RDM. To fulfil the scientists' needs and requests with regard to storage, backup, documentation, search and sharing of data with other project members, a project-specific RDM system was designed and implemented. This system was developed and continuously modified in collaboration with the scientists to facilitate their system acceptance. Besides the mentioned services, the system supports further common services such as controlled access to data, rights management, data publication with DOI and data statistics (on repository and single data level). All RDM services provided for the scientists are thus bundled and available to the users in one system: a 'one-stop-shop'. After more than ten years of RDM service provision for the CRC/TR32, the repository statistics clearly visualize the use of the diverse RDM system services. Furthermore, it has been shown that an RDM adapted to the needs of interdisciplinary researchers can be fruitful and indispensable when scientists conduct their research study e.g. with a time lag. RDM services established at an early stage can contribute to a successful long-term research project.

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Section: Discussionmentioning

confidence: 99%

Supporting the Interdisciplinary, Long-Term Research Project ‘Patterns in Soil-Vegetation-Atmosphere-Systems’ by Data Management Services

Curdt

2019

Data Science Journal

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“…Interdisciplinary research collaboration projects that are aimed to capitalize potential synergies and produce innovative solutions [1] often own wide varieties of data: ranging from observational, experimental to simulated data and from simple numerical values to time series, images, and videos [2]. Especially state-of-the-art research and development in artificial intelligence (AI) heavily depends on the availability of large data sets of high quality.…”

Section: Introductionmentioning

confidence: 99%

“…However, each discipline can have their own metadata records and approaches of organizing data [1]. The contextual understanding of these data differs among people and gets compromised over time with declining individual and group memory or with movement of staff (domain expert) [4].…”

Section: Introductionmentioning

confidence: 99%

ProMetaS – A Metadata Schema for Process Engineering and Industry

Sherpa

Müller-Pfefferkorn

Tolksdorf

et al. 2023

Chemie Ingenieur Technik

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Data collection in process industry yields a variety of data types. To maintain the knowledge about the data and to enable finding and reusing them (FAIR data), a common description with metadata is necessary. In the project KEEN, ProMetaS – the Process Engineering/Industry Metadata Schema – was developed. It defines various metadata categories adhering to available metadata standards. In this article, ProMetaS, its implementation into the KEEN data platform, and its application in two use cases is described.

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“…This is particularly true for collaborative research that aims to achieve an integrated view of the research subjects and typically involves many researchers from different disciplines. For large and long-term research consortia, and for research that deals with a variety of data in terms of type, size, quality, etc., the employment of an efficient as much as effective infrastructure for the management of research data is mandatory to assure successful highquality research (e.g., Geosling et al 2015;Specht et al 2015;Wang et al 2016;Curdt 2016, andGrunzke et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Managing collaborative research data for integrated, interdisciplinary environmental research

et al. 2020

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The consistent management of research data is crucial for the success of long-term and large-scale collaborative research. Research data management is the basis for efficiency, continuity, and quality of the research, as well as for maximum impact and outreach, including the long-term publication of data and their accessibility. Both funding agencies and publishers increasingly require this long term and open access to research data. Joint environmental studies typically take place in a fragmented research landscape of diverse disciplines; researchers involved typically show a variety of attitudes towards and previous experiences with common data policies, and the extensive variety of data types in interdisciplinary research poses particular challenges for collaborative data management. In this paper, we present organizational measures, data and metadata management concepts, and technical solutions to form a flexible research data management framework that allows for efficiently sharing the full range of data and metadata among all researchers of the project, and smooth publishing of selected data and data streams to publicly accessible sites. The concept is built upon data type-specific and hierarchical metadata using a common taxonomy agreed upon by all researchers of the project. The framework's concept has been developed along the needs and demands of the scientists involved, and aims to minimize their effort in data management, which we illustrate from the researchers' perspective describing their typical workflow from the generation and preparation of data and metadata to the long-term preservation of data including their metadata.

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Data Management in Collaborative Interdisciplinary Research Projects—Conclusions from the Digitalization of Research in Sustainable Manufacturing

Cited by 14 publications

References 24 publications

Supporting the Interdisciplinary, Long-Term Research Project ‘Patterns in Soil-Vegetation-Atmosphere-Systems’ by Data Management Services

Supporting the Interdisciplinary, Long-Term Research Project ‘Patterns in Soil-Vegetation-Atmosphere-Systems’ by Data Management Services

ProMetaS – A Metadata Schema for Process Engineering and Industry

Managing collaborative research data for integrated, interdisciplinary environmental research

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