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

Authors

53

  1. TJ
    Timothy J. Norman

    University of Aberdeen, United Kingdom

    1 publications · 17 citations

    1

    h-index

  2. FB
    Federica Bellizio

    Imperial College London, United Kingdom

    1 publications · 41 citations

    1

    h-index

  3. MN
    Marcos Netto

    Virginia Tech, United States

    1 publications · 41 citations

    1

    h-index

  4. YW
    Yajun Wang

    Jiangsu University of Science and Technology, China

    1 publications · 41 citations

    1

    h-index

  5. RM
    R.R. Mohler

    Oregon State University, United States

    1 publications · 39 citations

    1

    h-index

1–5 of 53

Venues

  1. Journal of the Franklin Institute

    1 publications · 39 citations

    1

    h-index

  2. 1

    h-index

  3. Journal of Network and Computer Applications

    JNCA · 1 publications · 22 citations

    1

    h-index

  4. 1

    h-index

  5. Pervasive and Mobile Computing

    1 publications · 17 citations

    1

    h-index

1–5