Data Model Alignment
Data Model Alignment is a methodological framework within cross-platform data harmonization and IoT interoperability that establishes semantic and structural consistency between heterogeneous data models by systematically mapping and reconciling their conceptual schemas, syntactic representations, and contextual metadata to enable seamless data exchange and integration across diverse platforms and devices.
36
Publications
1.9K
Citations
131
Authors
64
Institutions
Publications per year
2017–2026
10
36
1–5 of 36
131
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64

European Bioinformatics Institute
Cambridge, United Kingdom
3 h-index
10 publications
609 citations
Technical University of Munich
Munich, Germany
3 h-index
7 publications
155 citations
Wellcome Trust
London, United Kingdom
2 h-index
9 publications
594 citations
University of Cambridge
Cambridge, United Kingdom
2 h-index
7 publications
438 citations
Remote Sensing Application Center
Sofia, Bulgaria
1 h-index
1 publications
32 citations

Polish Academy of Sciences
Warsaw, Poland
1 h-index
4 publications
804 citations
Ludwig-Maximilians-Universität München
Munich, Germany
1 h-index
2 publications
106 citations
Statistisches Bundesamt
Wiesbaden, Germany
1 h-index
1 publications
37 citations
1–8 of 64
Repository · 1 publications · 12 citations
1
h-index
IJDST · 1 publications · 57 citations
1
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1 publications · 15 citations
1
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1 publications · 126 citations
1
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1 publications · 53 citations
1
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1–5