A Java Spring Boot service that detects when changes to identity classification schemas produce exclusion, and measures who bears the cost.
The goal of the system is to automatically look at a particularly consequential part of a digital infrastructure, analyse its changes over a long period of time, and assess the risk of exclusion that this poses.
While it's possible to understand consequences based on individual changes to an infrastructure, many of the most consequential changes are only felt in the gradual slow change of infrastrucutre, which may only develop over years or decades.
The system will analyse the identity classification schema and assess how slow, gradual changes to an infrastructure can lead to challenges for the people represented by the infrastructure.
By analysing both the individual version-changes and the successive version changes, the system assesses the identity category drift that has taken place, and how this can be consequential for people.
The system is underpinned by theories of infrastructure, particularly the work of Bowker and Star. It is also influenced by intersectionality lens developed by Crenshaw, and Nixon's theory of slow violence.
The system is inspired by the doctoral thesis of the author Katherine Wyers, who conducted her doctoral research on the challenges of understand how disadvantage can manifest through the slow temporality of digital infrastructure. https://katherinewyers.com
Timeframe: Short term, scoped to individual version-changes to a classification schema Purpose: Understand the short-term implications of the introduction of a new schema version.
Assesses the semantic difference between two versions of a schema, categorised by change type (deletion, merge, split, rename, or granularity reduction). The Schema Diff determines not only what has changed, but also the risk of exclusion posed by this change
Timeline: Long, over years or decades Purpose: Understand how a series of schema changes slowly shape the lives of the people represented by the categories
Tracks how a set of identity categories have been shaped over a series of three or more schema changes. This feature makes it possible to understand the slow temporality of identity data infrastructure by assessing how changes take place over several concurrent schema changes
CURRENT PHASE: Implementing core CRUD functionality with Security features
FUTURE PLANNED DEVELOPMENT: Implement the data model for the schema, and import the first test case Implement the mapping feature to map between schema versions Implement the Schema Diff algorithm to assess the risk
Implement the Slow Drift Detector algorithm to assess change over a series of concurrent schema changes