STEAM Knowledge Graph
5 minute read
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.
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