What is missingness? In a world that is dominated by big data and data-driven economies, we seem to have lost track of what falls outside of data-ification: missingness. Missing data, missing people, missing stories, missing and messy numbers. All these, it seems, are not interesting.
Missing data (and the idea of the missing variable) is relevant in Statistics and Machine Learning. Any books about data science will advise the researcher to minimise missing data, make sure that the data corpus is as complete and ‘final’ as possible. However, what happens when the data corpus is made of missing names, missing stories, missing issues and missing people? Missingness acquires a political meaning, challenging what we have learned from the idea of biopower: what if missing data becomes a form of biopower? How can computation help ‘resist’ this missing-ness?
This website will showcase the multiple meanings that missing-ness assumes and has assumed in various research project, with the help of populating the blog and the project pages with many and interesting reflections and case studies.