We believe that the editorial process of today is firmly under-saturated with productive insight due to a lack of data that can accurately describe the journalistic output. When newsrooms typically describe themselves as ”data-driven” they are in fact, most often, describing post-hoc data analysis in which they are trying to gain some insight about journalistic content without a controlled vocabulary to describe it.
Answering the question "why did this job work" with any kind of precision when you seldom describe your content in detail is therefore difficult. With KIT Core, a completely new set of taxonomies, or categories, we aim to create such a controlled vocabulary.
The ontology contains three major areas of new taxonomies for editorial content;
Within these three we capture the three classic editorial questions – What, Why and How – that traditional content tagging and post hoc semantic analysis does not have the vocabulary to describe. Taxonomies are applied to each story by the editor in the synopsis phase of the editorial process and thus acts as a blueprint for the reporter in researching and creating the content itself.
By collecting this data Storykit gives precise recommendations to content creators on how they should produce every job for the best results.