Datakartassan

Datakartassan is a fictional data management framework created for illustrative discussions of data mapping, schema integration, and lineage tracking. It is not a real product or standard, but is used in academic exercises and hypothetical scenario planning to explore interoperability, governance, and compliance in data ecosystems.

Overview and purpose: Datakartassan envisions a modular platform that describes datasets, their schemas, and the rules for transforming data between domains. It emphasizes data provenance, auditable transformations, and configurable policy enforcement to support responsible data sharing and analysis.

Architecture and components: The model employs a graph-based representation in which nodes denote datasets, schemas, mapping rules, transformation steps, and provenance annotations, while edges capture data flows and dependencies. Adapters connect the framework to diverse data sources and destinations. A distinct mapping language expresses correspondences between source and target schemas, and a transformation engine executes the defined rules. A lineage recorder preserves records of data lineage, and a policy engine enforces access control, retention, and compliance constraints.

Applications and use cases: Datakartassan is framed for teaching data integration concepts, simulating cross-domain data sharing, and evaluating governance scenarios. It supports exploring trade-offs between normalization and denormalization, assessing performance implications of complex mappings, and practicing privacy-by-design and regulatory compliance in synthetic environments.

Development and reception: As a fictional tool, Datakartassan has no real-world adoption or industry standard status. It is primarily used in theory-driven discussions and classroom settings; critiques often point to potential complexity and the risk of oversimplifying real-world data governance challenges.

See also: data provenance, data lineage, schema mapping, data governance.