Industrial Data Management
Industrial Data Management is a systematic framework for the acquisition, storage, integration, processing, and governance of data generated by industrial systems and cyber-physical devices within the Industrial Internet of Things, distinguished by its focus on real-time analytics, interoperability, scalability, and domain-specific constraints in industrial environments.
527
Publications
30.9K
Citations
1.7K
Authors
599
Institutions
Publications per year
2017–2026
372
527
A Complex View of Industry 4.0
Vasja Roblek, Maja Meško, Alojz Krapež · SAGE Open · 2016 · 912 citations · Full text
Computing, Information Technology, Technology Management +17
1–5 of 527
1.7K
National Institute of Standards and Technology, United States
4 publications · 108 citations
4
h-index
4
h-index
National Institute of Standards and Technology, United States
4 publications · 121 citations
4
h-index
4
h-index
4
h-index
1–5 of 1.7K
599
National Institute of Standards and Technology
Gaithersburg, United States
13 h-index
34 publications
1.3K citations
Chalmers University of Technology
Gothenburg, Sweden
11 h-index
31 publications
1.9K citations
RWTH Aachen University
Aachen, Germany
10 h-index
51 publications
4.6K citations
University of Stuttgart
Stuttgart, Germany
9 h-index
28 publications
1.1K citations
Loughborough University
Loughborough, United Kingdom
8 h-index
10 publications
627 citations
Politecnico di Milano
Milan, Italy
7 h-index
24 publications
745 citations

Beihang University
Beijing, China
6 h-index
20 publications
2K citations

Technische Universität Darmstadt
Darmstadt, Germany
6 h-index
16 publications
275 citations
1–8 of 599
39 publications · 3.5K citations
20
h-index
11 publications · 765 citations
11
h-index
10 publications · 363 citations
10
h-index
9 publications · 1.1K citations
9
h-index
9 publications · 1.5K citations
9
h-index
1–5