Data Observability
Data Observability is a data management framework that enables the assessment and monitoring of data health through measurable characteristics such as freshness, distribution, lineage, schema, and completeness, distinguishing it from broader data governance by focusing on system transparency and issue detectability.
12
Publications
392
Citations
53
Authors
33
Institutions
Publications per year
2017–2026
5
12
Towards Observability Data Management at Scale
Suman Karumuri, Franco Solleza, Stan Zdonik et al. · ACM SIGMOD Record · 2021 · 47 citations
Félix Rafael Segundo Sevilla, Yanli Liu, E. Barocio et al. · International Journal of Electrical Power & Energy Systems · 2021 · 41 citations · Full text
1–5 of 12
53
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1–5 of 53
33
University of Michigan
Ann Arbor, United States
1 h-index
2 publications
44 citations
IBM Research - Thomas J. Watson Research Center
Yorktown Heights, United States
1 h-index
1 publications
17 citations

University of Nottingham
Nottingham, United Kingdom
1 h-index
3 publications
123 citations
Franche-Comté Électronique Mécanique Thermique et Optique - Sciences et Technologies
Besançon, France
1 h-index
4 publications
88 citations
Intel (Germany)
Munich, Germany
1 h-index
1 publications
47 citations
RISE Research Institutes of Sweden
Gothenburg, Sweden
1 h-index
1 publications
41 citations
Oregon State University
Corvallis, United States
1 h-index
2 publications
78 citations
John Brown University
Siloam Springs, United States
1 h-index
2 publications
94 citations
1–8 of 33
1 publications · 39 citations
1
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1 publications · 41 citations
1
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JNCA · 1 publications · 22 citations
1
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1 publications · 75 citations
1
h-index
1 publications · 17 citations
1
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1–5