Open AccessCreating return on investment for large-scale metadata creation
Author(s) -
Michelle Urberg
Publication year - 2021
Publication title -
information services and use
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.304
H-Index - 19
eISSN - 1875-8789
pISSN - 0167-5265
DOI - 10.3233/isu-210117
Subject(s) - metadata , transparency (behavior) , computer science , scale (ratio) , investment (military) , return on investment , meta data services , data science , world wide web , metadata repository , political science , computer security , neoclassical economics , economics , physics , quantum mechanics , politics , law , profit (economics)
The scholarly communications industry is turning its attention to large-scale metadata creation for enhancing discovery of content. Algorithms used to train machine learning are powerful, but need to be used carefully. Several ethical and technological challenges need to be faced head-on to use of machine learning without exacerbating bias, racism, and discrimination. This article highlights the specific needs of humanities research to address historical bias and curtail algorithmic bias in creating metadata for machine learning. It also argues that the return on investment for large-scale metadata creation begins with building transparency into metadata creation and handling.