Semantic Process for Engineering Design · from Eng. Design • Capture the semantics of industrial data processing pipelines, for validation, process control, optimization, and viz.

Semantic Processing for Engineering Design

Adj. Prof Ossi Nykänen, [email protected], [email protected] University of Technology (TUT),

Department of Mathematics, Hypermedia Laboratory

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TUT W3C Web Technology Day, October 3, 2012, TUT, Tampere

Intro: TUT/ Department of Mathematics

• Staff around 60(+), 6 Full Professors • Director Prof. Seppo Pohjolainen

• Math education & competitive research • Mathematical analysis with applications• Discrete mathematics• Mathematical modelling• Technology enhanced learning and information modelling

(Hypermedia laboratory, Math education, ...)

• Significant project portfolio (incl. applications)

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Intuitive Rationale for Today: Semantics (?)

• Imagine that you are given a dataset that is so big and/or complex that don’t have any insight into it as such:

D• How do we understand the underlying phenomenon?

• That’s easy: Let’s “look into” the data D

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Example: Comparing 400 Automobiles4

3.10.2012Source: Telea, A. 2008. Data Visualization, A K Peters

Example: Managing Software Modularity5

3.10.2012Source: Telea, A. 2008. Data Visualization, A K Peters

Example: Analysing Evolution of Design6

3.10.2012Source: Telea, A. 2008. Data Visualization, A K Peters

Now Wait a Second...

• Exactly how can we “look into” the data?• What if can’t (omnipotenly) “see” data ─ “where” to look?

─ Don’t look into D, but a semantically annotated version of it (cf. prev. examples):

Desc(D)• …a machine-understandable version of D(a bit like D for Dummies, but for software tools…)

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Quick (?) Solution: Semantic Annotations8

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Enclose Semantics & Transform

Imported Dataset DSemantically

Enriched DatasetDesc(D)

Application via App(Desc(D))

[Use Case]

Semantic Annotation

…e.g. using SemWebTechnologies & Linked Data (LD) Vocabularies, by identifying resources, literal properties, and relationships with other resources (perhaps w.r.t. some common domain ontology)

A Better Solution: Semantic Process9

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Semantic Process(…don’t re-engineer

semantics ─ capture themin the making)

Transform

Application-SpecificMapping

App(Desc(D))

Semantics-Sensitive

Data Acquisition

Data DCreation & Mngmnt Process

[Feedback & Utility]

[Use Case]

Imported, Semantically Rich Dataset Desc(D)

Application (Using General-

Purpose Components)

A More Serious (?) Example from Eng. Design

• Capture the semantics of industrial data processing pipelines, for validation, process control, optimization, and viz. & simulation generation applications (see e.g. the related JIEM article)

• Aligning information, consistency checking, APIs, reasoning, domain modeling, …

• Others apps (at Math Dept.): Social network analysis, simulator design, mathematical modeling, intelligent information systems, …

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Conclusion

• Complex data can be understood & processed only indirectly, via machine-understandable descriptions (↔methods)

• Instead of annotating data, re-engineering the semantics, one should aim for a rich & sustainable semantic process

• Thank you!• Got interested?

Contact: Adj. Prof Ossi Nykänen, Dept. ofMathematics, Hypermedia Laboratory, W3C Finnish Office, SmartSimulators, …

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