ToDI: A Taxonomy of Derived Indices

Advancements in digital technology have eased the process of gathering, generating, and altering digital data at large scale. The sheer scale of the data necessitates the development and use of smaller secondary data structured as ‘indices,’ which are typically used to locate desired subsets of the original data, thereby speeding up data referencing and retrieval operations. Many variants of such indices exist in today’s database systems, and the subject of their design is well investigated by computer scientists. However, indices are examples of data derived from existing data; and the implications of such derived indices, as well as indices derived from other indices, pose problems that require careful ethical analysis. But before being able to thoroughly discuss the full nature of such problems, let alone analyze their ethical implications, an appropriate and complete vocabulary in the form of a robust taxonomy for defining and describing the myriad variations of derived indices and their nuances is needed. This paper therefore introduces a novel taxonomy of derived indices that can be used to identify, characterise, and differentiate derived indices.