Schema

This page outlines the data schemas Owl (preliminarily) uses.

Content for this page is under active development.

Owl uses a variety of schemas to gain a cohesive, end to end dataflow, to structure data and to create seamless dataflow transitions between input, compute, store and reply.

```python
# =========COREDOMAIN==============

class CoreDomain(BaseNode):
    coreDomainID = StringProperty(unique_index=True)
    derivedFromQueryID = StringProperty()
    primaryTopic = StringProperty()
    description = StringProperty()
    keywords = JSONProperty()
    relevanceScores = JSONProperty()
    perspective = StringProperty()
    geographicalScope = StringProperty()
    socioeconomicScope = StringProperty()
    temporalScope = DateProperty()
    spatialCoverage = JSONProperty()
    license = StringProperty()
    facetRelations = RelationshipTo('Facet', 'RELATED_TO_FACET')

    def add_facet_relation(self, facet):
        self.facetRelations.connect(facet)


# =============SOCIALFACET===================


class SocialFacet(Facet):
    impactScore = FloatProperty()
    topics = RelationshipTo('Topic', 'HAS_TOPIC', model=EvolvingRelationship)
    mentions = RelationshipTo('Mention', 'MENTIONS', model=EvolvingRelationship)
    dynamics = RelationshipTo('Dynamic', 'HAS_DYNAMIC', model=EvolvingRelationship)
    feedback = RelationshipFrom('UserFeedback', 'TARGETS_SOCIAL_FACET')
    weight = FloatProperty()
    queryLens = StringProperty()
    relatedFacet = RelationshipTo('Facet', 'RELATED_TO', model=EvolvingRelationship)
    temporalCoverage = RelationshipTo('TemporalEvent', 'COVERED_BY', model=EvolvingRelationship)
    entities = RelationshipTo('Entity', 'INCLUDES_ENTITY', model=EvolvingRelationship)
    relations = RelationshipTo('Relation', 'INCLUDES_RELATION', model=EvolvingRelationship)
    keywords = JSONProperty()
    factions = RelationshipTo('Faction', 'INCLUDES_FACTION', model=EvolvingRelationship)
    influencedBy = RelationshipTo('Influence', 'INFLUENCED_BY', model=EvolvingRelationship)
    evidencedBy = RelationshipTo('Evidence', 'EVIDENCED_BY', model=EvolvingRelationship)
    sequentialPathway = RelationshipTo('SequentialPathway', 'FOLLOWS_PATHWAY', model=EvolvingRelationship)


# =============CULTUREFACET===================

class CultureFacet(Facet):
    culturalSignificance = StringProperty()
    traditions = RelationshipTo('Tradition', 'HAS_TRADITION', model=EvolvingRelationship)
    artifacts = RelationshipTo('Artifact', 'HAS_ARTIFACT', model=EvolvingRelationship)
    feedback = RelationshipFrom('UserFeedback', 'TARGETS_CULTURE_FACET')
    weight = FloatProperty()
    queryLens = StringProperty()
    relatedFacet = RelationshipTo('Facet', 'RELATED_TO', model=EvolvingRelationship)
    temporalCoverage = RelationshipTo('TemporalEvent', 'COVERED_BY', model=EvolvingRelationship)
    entities = RelationshipTo('Entity', 'INCLUDES_ENTITY', model=EvolvingRelationship)
    relations = RelationshipTo('Relation', 'INCLUDES_RELATION', model=EvolvingRelationship)
    keywords = JSONProperty()
    citations = RelationshipTo('Citation', 'CITED_BY', model=EvolvingRelationship)



# =============ENVIRONMENTFACET===================

class EnvironmentFacet(Facet):
    sustainabilityScore = FloatProperty()
    challenges = RelationshipTo('Challenge', 'FACES_CHALLENGE', model=EvolvingRelationship)
    strategies = RelationshipTo('Strategy', 'EMPLOYS_STRATEGY', model=EvolvingRelationship)
    feedback = RelationshipFrom('UserFeedback', 'TARGETS_ENVIRONMENT_FACET')
    weight = FloatProperty()
    queryLens = StringProperty()
    relatedFacet = RelationshipTo('Facet', 'RELATED_TO', model=EvolvingRelationship)
    temporalCoverage = RelationshipTo('TemporalEvent', 'COVERED_BY', model=EvolvingRelationship)
    spatialCoverage = RelationshipTo('SpatialCoverage', 'HAS_SPATIAL_COVERAGE', model=EvolvingRelationship)
    entities = RelationshipTo('Entity', 'INCLUDES_ENTITY', model=EvolvingRelationship)
    relations = RelationshipTo('Relation', 'INCLUDES_RELATION', model=EvolvingRelationship)
    keywords = JSONProperty()
    environmentalFactors = RelationshipTo('EnvironmentalFactor', 'INCLUDES_FACTOR', model=EvolvingRelationship)


# =============INTRAFACET===================

class IntraFacet(Facet):
    internalConnectivityScore = FloatProperty()
    confidence = FloatProperty()
    # Relationships with weighted and evidenced connections
    socialCultureRelationship = RelationshipTo('CultureFacet', 'SOCIAL_CULTURE_RELATIONSHIP', model=FacetRelationship)
    socialEnvironmentRelationship = RelationshipTo('EnvironmentFacet', 'SOCIAL_ENVIRONMENT_RELATIONSHIP', model=FacetRelationship)
    cultureEnvironmentRelationship = RelationshipTo('EnvironmentFacet', 'CULTURE_ENVIRONMENT_RELATIONSHIP', model=FacetRelationship)
    # Potential outcomes and evidences as separate nodes linked to this facet
    outcomes = RelationshipTo('PotentialOutcome', 'HAS_POTENTIAL_OUTCOME')
    evidence = RelationshipTo('Evidence', 'SUPPORTED_BY_EVIDENCE')

class FacetRelationship(StructuredRel):
    weight = FloatProperty()
    confidence = FloatProperty()

class PotentialOutcome(BaseNode):
    description = StringProperty()

class Evidence(BaseNode):
    label = StringProperty()
    description = StringProperty()



# ===========GEM==================


class Gem(BaseNode):
    id = StringProperty(unique_index=True, default=lambda: uuid4())
    facets = RelationshipTo(Facet, 'COMPRISED_OF', model=ComprisesFacet)
    dynamicWeights = JSONProperty()
    interactionScores = JSONProperty()
    semanticInteractions = RelationshipTo(Facet, 'SEMANTIC_INTERACTION', model=SemanticInteraction)
    visualizationElements = JSONProperty()
    keyVisuals = JSONProperty()
    history = RelationshipTo('HistoryEvent', 'HAS_HISTORY')
    query = StringProperty()
    result = RelationshipTo(CoreDomain, 'RESULTS_IN')
    confidence = FloatProperty()
    source = StringProperty()
    weights = JSONProperty()
    likes = IntegerProperty()
    coupledWith = RelationshipTo('Gem', 'COUPLED_WITH')
    positionality = JSONProperty()
    creator = RelationshipTo('User', 'CREATED_BY')
    createdAt = DateTimeProperty()
    lastModifiedBy = RelationshipTo('User', 'LAST_MODIFIED_BY')
    lastModifiedAt = DateTimeProperty()
    usage = RelationshipTo('UsageEvent', 'USAGE')
    sentiment = RelationshipTo('Sentiment', 'HAS_SENTIMENT')
    apiEndpoint = StringProperty()
    documentation = StringProperty()

class ComprisesFacet(StructuredRel):
    # Custom relationship attributes can be added here if needed

class SemanticInteraction(StructuredRel):
    relationship = StringProperty()
    # Additional interaction-specific attributes

class HistoryEvent(BaseNode):
    eventType = StringProperty()
    date = DateTimeProperty()

class UsageEvent(BaseNode):
    user = RelationshipFrom('User', 'USES')
    timestamp = DateTimeProperty()
    action = StringProperty()

class Sentiment(BaseNode):
    score = FloatProperty()
    positiveReviews = IntegerProperty()
    negativeReviews = IntegerProperty()

```