Floating Cubes

Problem

Lack of a training corpus for AI systems

Improved by these Interventions

Introduce tooling that creates structured metadata

Tools that enable metadata managers to create and manage structured metadata that conforms to a model. This enables more use cases for both human and machine users to leverage the metadata.

Generate a "Silver Corpus" for AI training

A "Silver Corpus" is an efficient bootstrapping approach to creating a precursor to a "golden corpus" in order to train an AI process efficiently.

Prevented by these Capabilities

An integrated information backbone

Data Language specializes in high-value information systems design and governance. A strong and highly contextual information backbone is essential for delivering and maintaining competitive digital products.

Metadata is part of a feedback loop to optimize AI RPA training

A business' core assets and associated metadata are part of a continuous optimization loop, where SMEs confirm or correct predictions, and the system learns from this.

Caused by these Problems

Metadata holds no value for human or machine processes

If metadata does not include structure or context (from a model), it is impossible to harness it in structured scenarios such as AI training, and driving product features.

Seen in these Maturity Models

Digital Media Metadata Maturity Model

Stage 1: Basic Metadata

Assets have simple, unstructured "Tags" used to power free-text search and can aggregate/group the assets. This level offers no information for machines or humans beyond free-text search and basic collections.

Digital Media Metadata Maturity Model