Dontopedia
Explore

Sankey Diagrams

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-18.)

Sankey Diagrams has 13 facts recorded in Dontopedia across 2 references, with 2 live disagreements.

13 facts·9 predicates·2 sources·2 in dispute

Mostly:visualizes(4), rdf:type(2), used for(1)

Maturity scale raw canonical shape-checked rule-derived certified

Rdf:typein disputerdf:type

Visualizesin disputevisualizes

Used forusedFor

Shows Process FlowshowsProcessFlow

  • true[1]all time · F55f6a65 65b0 4330 9e2a 124d648e12ff

Has List Item NumberhasListItemNumber

  • 8[1]sourceall time · F55f6a65 65b0 4330 9e2a 124d648e12ff

Is Part of ListisPartOfList

Has ExamplehasExample

Has PurposehasPurpose

Rdfs:labelrdfs:label

  • Sankey Diagrams[1]sourceall time · F55f6a65 65b0 4330 9e2a 124d648e12ff

Inbound mentions (4)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

appliesToApplies to(1)

demonstratesDemonstrates(1)

hasMemberHas Member(1)

recommendedVisualizationRecommended Visualization(1)

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

hasExamplebeam/f55f6a65-65b0-4330-9e2a-124d648e12ff
ex:user-interaction-flow
hasListItemNumberbeam/f55f6a65-65b0-4330-9e2a-124d648e12ff
8
hasPurposebeam/f55f6a65-65b0-4330-9e2a-124d648e12ff
ex:flow-showing
isPartOfListbeam/f55f6a65-65b0-4330-9e2a-124d648e12ff
ex:visualization-types-list
labelbeam/f55f6a65-65b0-4330-9e2a-124d648e12ff
Sankey Diagrams
typelme/fcbf98a7-e030-40c2-a78d-6ad05f498f8a
ex:VisualizationTool
typebeam/f55f6a65-65b0-4330-9e2a-124d648e12ff
ex:VisualizationType
showsProcessFlowbeam/f55f6a65-65b0-4330-9e2a-124d648e12ff
true
usedForlme/fcbf98a7-e030-40c2-a78d-6ad05f498f8a
ex:VisualizingCustomerFlow
visualizeslme/fcbf98a7-e030-40c2-a78d-6ad05f498f8a
ex:customer-flow-through-purchase-journey
visualizeslme/fcbf98a7-e030-40c2-a78d-6ad05f498f8a
ex:FromBrowsingToCheckout
visualizeslme/fcbf98a7-e030-40c2-a78d-6ad05f498f8a
ex:PurchaseJourneyStages
visualizeslme/fcbf98a7-e030-40c2-a78d-6ad05f498f8a
browsing-to-checkout-flow

References (2)

2 references
  1. [1]beam-chunk7 facts
    customctx:claims/beam/f55f6a65-65b0-4330-9e2a-124d648e12ff
    • full textbeam-chunk
      text/plain1 KBdoc:beam/f55f6a65-65b0-4330-9e2a-124d648e12ff
      Show excerpt
      5. **Heatmaps** - **Purpose:** Show density or intensity of data points. - **Example:** Highlight areas where certain metrics are consistently below target. 6. **Bullet Graphs** - **Purpose:** Compare a primary measure to one or m
  2. [2]beam-chunk6 facts
    customctx:claims/lme/fcbf98a7-e030-40c2-a78d-6ad05f498f8a
    • full textbeam-chunk
      text/plain17 KBdoc:beam/fcbf98a7-e030-40c2-a78d-6ad05f498f8a
      Show excerpt
      [Session date: 2023/05/24 (Wed) 09:36] User: I'm using Python and R to build predictive models, but I'm having some trouble with feature engineering. Can you give me some tips or resources on how to improve my feature engineering skills? As

See also

Keep researching

Missing something or suspicious of what's here? Kick off a research session — a Claude agent will investigate, cite its sources, and file new facts into a dedicated context you can review before accepting into the shared view.