Universal Data Analytics as Semantic Spacetime

Types are not enough…

Graph spacetime

          A  B  C  D  E  F  G  H
A 0 - - - - - - -
^ B - 0 - 3 - - - -
| C - - - - - - - -
| D - 1 - 0 - - - -
row E - - - - 0 - - -
| F - - - - - 0 - -
| G - - - - - - 0 -
v H - - - - - - - 0
<--- column ---> matrix(r,c) = value
matrix(2,4) = 3
matrix(4,2) = 1

Graphs: associations, links, or “edges” vs types

  1. A emailed B
  2. A is the child of B
  3. A employs B
  4. A is an alias for B
  5. A belongs to B
Figure 1: A directed, labelled “edge” or link in a graph between objects A and B.

Nodes, “vertices”, agents — and their types

IF A (emailed OR spoke OR shouted OR texted OR tweeted OR *) TO B

Rethinking associative link semantics

  • A “CONTAINS” B (a kind of spatial relationship),
  • A “FOLLOWS” B (a kind of temporal relationship),
  • A “EXPRESSES” B (a local property) and
  • A “is NEAR to” B.

Modelling sort-of graphs in Go

var child_of = make(map[string]string)child_of[“A”] = B
type VectorPair struct {
From string
To string
}
var employs = make(map[Pair]bool)employs[VectorPair{From: “A”, To: “B”}] = true

Associations in Arango

Figure 2: A graph representation of some “entities”. It’s a natural way to think about relationships in pictorial terms — but the difference between salvation and damnation lies in the proper labelling of the arrows.

Associations with causal semantics

Forward: “Contains”,Backward: “Is part of”,Negative-forward: “does not contain”Negative-backward: “is not part of”
Figure 3: separating link semantics from the link using a look-up table (map)Figure 3: separating link semantics from the link using a look-up table (map).

Making an SST toolkit

ASSOCIATIONS[“groupalias”] -> structured edge type values
  1. The forward explanation text.
  2. The reverse direction text.
  3. The forward negative.
  4. The reverse negative.
(A,B,ASSOCIATION[“alias”],”+”)
type Association struct {
Key string `json:”_key”`
STtype int `json:”STType”`
Fwd string `json:”Fwd”`
Bwd string `json:”Bwd”`
NFwd string `json:”NFwd”`
NBwd string `json:”NBwd”`
}
var ASSOCIATIONS = make(map[string]Association)ASSOCIATIONS[“CONTAINS”] = Association{ “CONTAINS”, GR_CONTAINS, ”contains”, ”belongs to or is part of”, ”does not contain”, ”is not part of” }
var STTYPES []IntKeyValueconst GR_NEAR int = 1      // approx like
const GR_FOLLOWS int = 2 // i.e. influenced by
const GR_CONTAINS int = 3 // inside/outside
const GR_EXPRESSES int = 4 // represents, etc
Figure 4: the four elementary spacetime relationship types.

Associating with edges in Arango

CreateLink(node1, ”group-alias”, node2, weight)CreateLink("Norwegian", "IS_LIKE", "Swedish", 60/100)
Figure 5: browsing the links collection in Arango, we see the document structure of links.
Figure 6: a fully formed semantic spacetime model may have several node and edge collections

Summary: building on the SST package

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@markburgess_osl on Twitter and Instagram. Science, research, technology advisor and author - see Http://markburgess.org and Https://chitek-i.org

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Mark Burgess

Mark Burgess

@markburgess_osl on Twitter and Instagram. Science, research, technology advisor and author - see Http://markburgess.org and Https://chitek-i.org

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