EKG Principles
At agnos.ai we have adopted these ten guiding principles for building sustainable enterprise knowledge graphs.
Our Design Principles
We define an EKG as meeting these criteria. They guide our thinking and the vision of connecting data across silos within and beyond your organization.
01. Identity
Objects are identified with unique, permanent and resolvable identifiers
02. Meaning
Meaning is directly resolvable to a machine-readable mathematical statement
03. Distributed
Facts about any given object may be provided by multiple sources
04. Open World
Information from various sources can vary over time. These “multiple versions of the truth” must be reconciled on access by context
05. Self-Describing
All datasets are completely self-describing with information about lineage, provenance, source, quality and governance
06. Measurement
The quality of fit-for-purpose data must be measured and actionable
07. Use Cases
Information in the EKG exists with a known business justification and prioritized purpose
08. Control
Entitlement, privacy and business policies will be automatically executed, enforced and audited at the data point level
09. Ecosystem
All components of the data ecosystem will be subject to service level agreements
10. Standards
The EKG platform and content should be based on open standards
Make The Leap
To take your first step towards a more meaningful data infrastructure, have a conversation with one of our experts.