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SMS Breakout Nov 2004

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Topics for SMS Breakout at SEEK AHM

Wednesday, November 3, 1:30 -- 5:00 (Walnut, 6th)

Moderator: Bertram Ludaescher

Agenda

  • Updates: Overview and Progress
    • Semantic Typing
  • General Discussion
    • Current issues
    • New ideas
    • Priorities
    • Goals (Short-term, 6-month, 1 year)

Notes

  • Bertram (overview)
    • requirements:
      • semantic (in addition to structural) annotation of:
        • services (actor) and
        • datasets
      • for ... discovery, WF design, ...
      • prerequisites: what does this annotation langauge have?
    • structural types
      • array of float; list of record of (int, float, string); etc.
      • e.g., relational schema type, ptolemy type
      • applies both to data and "functions" (actors)
      • essentially, useful for plumbing -- the level of the programmer, or data provider
    • semantic type
      • formal expression referencing concepts in an ontology
      • to provide a high-level, conceptual of data and services
    • data(set)
      • informal descriptions: eml style metadata, keywords, controlled vocabularly
      • formal description
        • dataset ~ concept
        • attribute (column) ~ concept
        • fine-grained:
          • query(X1, X2, ..., Xn) ~ concept expression(X1, ..., Xn)
          • Xi are "tags" or variables point to substructure
    • actors (services)
      • overall function
      • input/output signature (-> reuse framework from dataset annotation)
    • Questions
      • How do you require that certain things must be registered, e.g., that a lat lon point has an x and y coord
      • How do you handle null values in a table ... e.g., a row doesn't have an x value
      • What is the difference between an annotation langauge and a description logic
  • Shawn (details of semantic registration language)
    • simplified Antweb example
      • abundance datasets
      • d1,d2 have similar structure (geo-referenced data)
      • d3 is differently structured (co-occurence based)
      • d4 lists host/parasite relationships (inquilinism)
    • Measurement, parasitism ontology (from SWDB'04 paper)
      • Presentation
      • observation, TaxonID, Parasite, Host
      • Example: annotating d1 ...

d1(Ge,Sp,Co,Lt,Ln) ~
Observation(O), value(O,Co), context(O,S), location(S,P), LatLonPoint(P), latDeg(P,Lt), lonDeg(P,Ln), item(O,A), Abundance(A), property(A,N), SciName(N), genus(N,Ge), species(N,Se).
      • Who is creating these mappings?
      • Shawn: use of a tool

  • Discussion about interface ...
    • Can we use growl browser to do the semantic annotation mappings graphically
      • similar in style to xml mapping tools
      • what is missing:
        • multiple selection of nodes
        • difficult to get relevant stuff when you expand nodes ... many nodes you don't care about up the inheritence tree
        • just want subclass and derived properties
        • graph query language ... to filter ... decouple what you show and select
          • e.g., i am only interested in isa links, so you might want to have a power user language, to subset what you are currently showing
          • would generalize; think it would be a useful extension to these visual editors, ... "+ isa; - any"
          • expression language for power use to turn on and off certain things; incremental search that start from results
        • graphic frame logic
          • a fundamental problem with visualization formulas as opposed to logical _consequent_ of the formulas

  • Jessie: ProFormaVis -- based on Angiosperm ontology
    • structures, attributes-values
    • reads in ontology; divides the gui into structure hierarchy, selected structure description details
    • the ontology doesn't try to define what a plant is, but gives the set of things you might want to say about plants
    • trying to describe a specimen, e.g., leaf, with attribute veination pattern, and anastomosing and arcuate...
      • the veination patther is anastomosing and arcuate
    • the end to end application: the scientist refines the set of things and properties (attribute values) that are useful for a collection; a form is generated / configured based on those filters; for others to classify items to
    • Bob Morris, et al., allows general description of things -- Structure of Descriptive Data -- TADWIG
    • Commercial program called Lucid 3

  • follow-up list
    • growl extension selective viewing / filtered views based on some keywords / or in general queries / or just let user select nodes in the neighborhoods in the tree


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This particular version was published on 03-Nov-2004 14:13:32 PST by SDSC.bowers.