STEAM Knowledge Graph

A visual map of how Science, Technology, Engineering, Arts, and Mathematics interconnect across this site — showing nodes, edges, and the semantic relationships that form the STEAM knowledge graph.

The knowledge graph below is the living map of this site. Every section is a node; every arrow is a named edge that explains how two areas of knowledge relate. This is the structural backbone behind the STEAM mission: not just five siloed disciplines, but an interconnected network where insights travel across boundaries.

The STEAM Domain Graph#

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title STEAM Knowledge Graph — MadSciGuys

rectangle "**Science**\nBiology · Chemistry\nPhysics · Medicine" as SCI
rectangle "**Technology**\nBiotech · Energy\nManufacturing · IoT" as TECH
rectangle "**Engineering**\nChemical · Civil\nElectrical · Aerospace" as ENG
rectangle "**Arts**\nKnowledge Mgmt\nPharm · Industry 4.0" as ARTS
rectangle "**Mathematics**\nPredictive Modeling\nData Science · ML" as MATH

SCI -right-> TECH : "enables"
TECH -right-> ENG : "implements"
ENG -up-> ARTS : "designed by"
ARTS -left-> MATH : "formalized by"
MATH -down-> SCI : "models"

SCI -[#9B59B6,dashed]-> MATH : "measured by"
ARTS -[#27AE60,dashed]-> TECH : "shapes UX of"
MATH -[#E67E22,dashed]-> TECH : "optimizes"
ENG -[#E74C3C,dashed]-> SCI : "applies"
ARTS -[#2980B9,dashed]-> SCI : "frames questions for"

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Node Detail: What Each Domain Contains#

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package "1 · Science" {
  class Biology {
    Molecular Biology
    Cell Biology
    Biochemistry
  }
  class Chemistry {
    Organic · Inorganic
    Physical · Analytical
  }
  class Physics {
    Quantum Mechanics
    Thermodynamics
    Cosmology
  }
  class Medicine {
    Internal Medicine
    Medical Genetics
    Immunology
  }
}

package "2 · Technology" {
  class BioTech
  class Energy
  class Manufacturing
  class Transportation
}

package "3 · Engineering" {
  class ChemicalEng as "Chemical Eng"
  class ElectricalEng as "Electrical Eng"
  class AerospaceEng as "Aerospace Eng"
  class ComputerEng as "Computer Eng"
}

package "4 · Arts" {
  class KnowledgeMgmt as "Knowledge Mgmt" {
    Ontological Semantics
    Design Study Method
    Taxonomy
  }
  class Pharma {
    Regulations (ICH)
    Scientific Method
    QbD / Control Strategy
  }
  class Industry40 as "Industry 4.0" {
    IoT · Big Data
    Cyber-Physical Systems
    Smart Factory
  }
}

package "5 · Mathematics" {
  class PredictiveModeling as "Predictive Modeling" {
    Data Science Lifecycle
    Feature Engineering
    Non-linear Regression
  }
}

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Cross-Domain Relationship Map#

The edges below show the named semantic relationships used across this site. These are the types of connections that form the knowledge graph structure.

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rectangle "Ontological Semantics" as ONT
rectangle "Knowledge Management" as KM
rectangle "Predictive Modeling" as PM
rectangle "Data Science Lifecycle" as DSL
rectangle "Industry 4.0" as I4
rectangle "Big Data" as BD
rectangle "Pharma / ICH QbD" as QBD
rectangle "Control Strategy" as CS
rectangle "S88 / S95 Standards" as S88
rectangle "Scientific Method" as SM
rectangle "Design Study Method" as DSM

KM -down-> ONT : "grounded in"
ONT -right-> KM : "structures"
PM -down-> DSL : "lifecycle of"
DSL -right-> BD : "requires"
BD -up-> I4 : "powers"
I4 -left-> S88 : "standardized by"
QBD -right-> CS : "produces"
QBD -down-> SM : "follows"
SM -left-> PM : "informs design of"
KM -[dashed]-> DSM : "evolved by"
DSM -[dashed]-> KM : "validates"
QBD -[dashed]-> ONT : "ontology alignment"
S88 -[dashed]-> ONT : "ontology alignment"

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Relationship Edge Vocabulary#

The knowledge graph uses a controlled vocabulary of edge types so relationships carry semantic meaning:

Edge Type	Meaning	Example
`enables`	A makes B possible	Science enables Technology
`implements`	B builds on A’s principles	Technology implements Engineering
`models`	Math describes phenomena in A	Mathematics models Science
`formalized by`	A gains rigor through B	Arts formalized by Mathematics
`grounded in`	A’s theory derives from B	Knowledge Mgmt grounded in Ontological Semantics
`powers`	A provides data/energy for B	Big Data powers Industry 4.0
`standardized by`	B defines A’s vocabulary	Industry 4.0 standardized by S88/S95
`follows`	A uses B’s process	Pharma follows Scientific Method
`informs design of`	A shapes how B is constructed	Scientific Method informs Predictive Modeling
`evolved by`	B refines and extends A	Knowledge Mgmt evolved by Design Study Methodology

Personas in the Graph#

Each persona sits at a specific set of nodes and traverses particular edge types in their daily work:

Persona	Primary Nodes	Key Traversals
Knowledge Manager	Knowledge Mgmt, Ontological Semantics, Design Study Method	grounded-in, evolved-by, structures
Data Scientist	Predictive Modeling, Data Science Lifecycle, Big Data	lifecycle-of, requires, informs-design-of
Pharma Product Developer	Pharma/ICH, Control Strategy, Scientific Method	follows, produces, standardized-by
Systems Integration Engineer	Industry 4.0, S88/S95, IoT, Cyber-Physical Systems	standardized-by, powers, implements
Analytical Chemist	Chemistry, Biology, Pharma	enables, applies, models
Theoretical Chemist	Chemistry, Physics, Mathematics	models, formalized-by, enables
Mathematician	Mathematics, Predictive Modeling, Data Science	models, formalized-by, optimizes
Design Researcher	Arts, Design Study Method, Knowledge Mgmt	evolved-by, frames-questions-for, shapes
Creative Strategist	Arts, Industry 4.0, Engineering	designed-by, shapes-UX-of, enables

How to Extend This Graph#

Every page on this site can participate in the knowledge graph by adding related_concepts to its frontmatter:

related_concepts:
  - concept: "Page Title"
    url: "/docs/path/to/page/"
    relationship: "grounded-in"   # use vocabulary from table above

New content authors should ask: What does this page depend on? What does it enable? What formalizes it? Those answers are the edges that grow the graph.