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Terminology for Layers

Carsten Bormann edited this page Jul 18, 2017 · 9 revisions

This wiki page (in markdown) tries to capture the results of the first breakout.

Michael McCool, Dan Brickley, Milan M, Kerry Lynn. Juan Carlos Zuniga, Carsten Bormann

Logistics

Meeting 4-5 today (Sunday, July 16), immediately after breakout session, to make notes and fill out outline.

Glossary

Proposed terms and definitions to go here.

  • Template
    • Definition

Topics/Ideas Discussed

An unorganized list of topics and ideas mentioned, to use as input.

  • Need to consider audience, users, and use cases
  • Already a set of tools and stacks in wide use; imperfect, but useful
    • This is not the place for a comprehensive survey, but some example stacks would be useful.
      • JSON-LD/JSON-Schema/JSON/CBOR
      • RDFa/XSL/XML/EXI
  • May be multiple layers even within structural layer
    • One close to the serialization, then a more abstract model closer to the application
    • Don't want to overcontrain structural model by serialization (syntactic model)
    • Structural interop is a prerequisite for semantic interop.
    • Reasons for layering:
      • separation of concerns
      • modularity
      • reuse
      • loose coupling
  • May be multiple sources of semantics: device, link, third parties (multiple, official and unofficial)
    • Instance and type identity useful to search for metadata (see also metadata types, lifecycle...)
    • "It's only hypermedia if data and metadata are combined"
    • Third-party semantics: Manufacturer, ingergrator, user
    • Duplicated labor, consistency, integration issues
    • What are economic incentives for generating metadata
    • May be "pre-shared" semantics that may be implicit in "internal" ecosystem use
    • Pre-shared metadata will have to be made explicit in some contexts eg during translation
  • Translation
    • Compare point-to-point O(n^2) vs intermediate O(n) approaches (and hybrids)
    • Use of intermediary as analysis tool to get (generate, find, or specify/request) a point-to-point translator
    • Goal should be to generate efficient translators, not go up through intermediary every time
    • Intermediary needs to have broad semantic scope

Layers

Semantic Interoperability — understand what the data/actions mean (Probably rooted in ontologies, vocabularies)

Structural: Know how to find certain information, understand the composition (Information Model?, Data Model?, ASN.1, XSD, ...) Two levels:

  • primitive -- constrained by serialization [data model]
  • more abstract, still structural [information model]

Syntactic: parse/generate (Serialization; pretty much domain-independent -- comes from representation framework, BER, XML serialization, EXI, JSON, CBOR...)

Categories:

  • (Needs all three) Application wants to:

    • control one or more devices
    • possibly discover the right device for that
    • Service Composition
    • Rule Systems
  • (Can do with 1 and 2) Universal remote (generic object browser, does not understand semantics) -- Human does the semantic reasoning

  • Translator (does need to understand semantics)

  • Machine learning, big data aggregation

Aspects:

  • Data vs. Metadata (actual metadata vs. syntactic/structural/semantic metadata; static vs. non-static)

    • Separation of metadata
      • Need to match up structure of data with structure of separate metadata then (cf. CSS selectors) -- requires structural interoperability
    • Find them
      • through a link from the data
      • through some external matching
  • "Semantic Model is in the head of the developer" vs. who is responsible for semantically annotating the data from a device... (need structural interoperability to be able to do that); manufacturer-provided vs. integrator-provided ("fifth floor" = context information)

Other Terminology

Describing

  • "the thing as manufactured" [information that should not have to be added by integrator]

vs.

  • "the thing as integrated, with applied metadata"

Ontologies vs. Vocabularies vs. "Tagging dictionaries" (e.g., Haystack, cf. OCF RTs)

See also: Examples.