ldml - application public release

7/31/2019 LDML - Application public release

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Lightweight Data Markup LanguageApplications

Sayandeep KhanDrakoon Aerospace

Invention ReportPublic ReleaseMay 27 2012



Contents

→LDMLReviewExample

→Multidimensional DataDead EndsTranslation : Description guided action

→Multiple Data SourceCoupling

→MetadataBasicsApplication : Machine guided investigation



LDML Review

Lightweight Data Markup LanguageUTF-8Multiple Nodes in One Document

Strict Inter-sentence RelationA graph can be formed



LDML Example

Example Data

River R

Channel Size S c

Carriage Capacity C

c

Actual Carriage Ac

Slit Capacity Ss

Slit Load SL

Vegetation Vg

Rainfall P

Corresponding Tree

R P

Sc

CC

Ac

Ss

SL

Vg

E f



LDML Example

In the last Model:Orange : Attribute Relation, i.e. R>(S

c, A

c, S

s, C

c)

Yellow : Detemination Relation, i.e. Sc> C

c>C

s

Notice S c uniquely determines the other two. It is possible toarrive at C

cand C

sfrom just S

c, along a single branch of the

tree, whose root is known. This is dead-end, and can beremoved. Just save S

c.

Actuall Carriage however depends on Rainfall, andExternal factors E

f. E

fmay be unknown. Therefore this is not

Dead end

Remove Deadends to improve storage!!!



Description Guided ActionTake the statements: R>(S

c, A

c, S

s, C

c,S

L) and S

c

>C c> S s

Parser must look for definitions of eachattribute

→ Deduction relation, Dead end : Calculate,Stop → Deduction relation without dead end:

Search other variables. Alert if missing.

Example: Sc, A

c, S

s, are defined. S

c>C

c, therefore

can calculate Cc. S

c>C

c>S

s, therefore, delete S

s.(A

c

,Vg,E

f )>S

L.

Therefore either define S L or define (V g ,E f )



Multiple Data Sources

The data on river and vegetation arefrom different sources (surveys).

Connected by relations

Clustering of Datasets



Metadata Comparison

Graphs → Each element a node

→ Each relation an edge → Different relations have different weightedvalue

Equivalent Datasets → Isomorphic graphs

Comparison by isomorphism test



Metadata Comparison: example

Orange : Attributes, value: a, Yellow:Deduction, value: b. Both graphs are isomorphic

same dataset, A = p, etc→

A

B

C

F

E

D

p

r

q

u

t

s

Dataset 1Dataset 2



Conclusion

Using relation between attributes: → Remove unnecessary storage

→ Find if information missing

→

Compare datasets (explianation of variablenames not needed) → Couple multiple datasets → Calculate missing information

In future: any algebric procedure applies

LDML : Capable of scientific manipulation of Data

ldml - application public release

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