Embrace the transformative power of reusability, in many dimensions, fueling boundless potential in your data journey. Empower yourself–and AI–to effortlessly assemble reusable data components, knowledge, services, and use case elements, sparking unparalleled innovation.

Experience a world where interconnected data drives transformation, igniting new markets and revolutionary ventures with trust and immediacy. Embrace reusability within DataRoad, where collective optimization and prosperity fuel your path towards a data-driven future.

Reusable Discovery

The characteristics of reusable use case elements and data are best defined by FAIR principles that promote Findable metadata properties, Accessible human and machine readabilities, Interoperable common structures, Reusable policies having license, provenance, domain clarity. Discovery activities may reference:

• Contrast Compare content patterns with common elements, overlapping domains, similar personas.
• Domain Granularity level of specificity and real world concept precision.
• Core Abstraction determining essential interaction, foundational value, uniqueness of actors.
• Broader Use generic scenarios that distill purpose, reduce redundancy, promote agility.
• Lexical Analysis key terms, compound structures, phrase relations, named entity recognition.
• Semantic Construct contexts of word embedding, meaning relevance, semantic distance.
• Group Classification based on hierarchical clustering or decision tree learning.
• Data Cataloging format, domain, subject matter, lineage source, sensitivity and criticality.
• Flow Dependency maps using quality policies, scoring formulae and validation criteria.
• Enterprise Knowledge graph declaration structure, format, content, domain.
• Business Alignment to function, process, organizational unit, economic marketplace.
• Usage Analysis relevance to application, processes and ecosystems.
• Ontological Topic themes that articulate the community of interest.
• Expressivity Language that captures the necessary relationships and critical constraints.
• Knowledge Reasoning mechanism required to detect outliers and other inconsistencies.