Data Instrumentation

Data Instrumentation is a scholarly contribution that constitutes a systematic method or framework designed to capture, measure, and transform raw data into meaningful inputs for artistic generation, enabling the integration of empirical data within data-driven art practices.

40

Publications

2.2K

Citations

120

Authors

55

Institutions

Publications per year

2017–2026

6

Authors

120

  1. AD
    Anders Drachen

    University of York, United Kingdom

    4 publications · 264 citations

    4

    h-index

  2. AC
    Alessandro Canossa

    Northeastern University, United States

    4 publications · 264 citations

    4

    h-index

  3. DR
    David Ramsey

    Université du Québec à Trois-Rivières, Canada

    1 publications · 687 citations

    1

    h-index

  4. CM
    Costanza Miliani

    University of Perugia, Italy

    1 publications · 29 citations

    1

    h-index

  5. AK
    Alexei Kuzmin

    University of Latvia, Latvia

    1 publications · 115 citations

    1

    h-index

1–5 of 120

Venues

  1. Astronomy and Astrophysics

    2 publications · 46 citations

    2

    h-index

  2. IEEE Transactions on Software Engineering

    TSE · 2 publications · 96 citations

    2

    h-index

  3. Bulletin of the American Meteorological Society

    BAMS · 1 publications · 29 citations

    1

    h-index

  4. Applied Spectroscopy

    1 publications · 77 citations

    1

    h-index

  5. Solid Earth

    1 publications · 63 citations

    1

    h-index

1–5