Semantic eScience Meeting February 24, 2014

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General Meeting Information

Agenda

Attendance

  • Yu might not be able to attend, got a high fever, however will work from home. 
  • Linyun
  • Corey
  • Matt
  • anirudh prabhu
  • Xixi Luo
  • Marshall
  • Han
  • Peter Fox
  • Patrick West 

Past Action Items

  • New students in the lab need to send Patrick an email – request account, get the right access, need-to-know’s
  • After this meeting, everyone get up and rearrange the tables, one big meeting table so you’re facing each other [done]
  • Patrick: add Xixi to escience email list [done]
  • Other students? Katie Chastain? [Done]

Action Items

  • Linyun: upload slides

Presentations

  • Keep this list from week to week so we know who’s presented and who will present. Please sign up if you have a good topic to share with others.
  • Feb. 3, 2014 - Introductions, no presentation
  • Feb. 24, 2014 - Linyun Fu - Data theory (Wickett et al.’s and Mealy’s papers)
  • Mar. 10, 2014 - Jin Zheng - thesis
  • Mar. 24, 2014 - Yu Chen - TBD
  • Apr. 14, 2014 - Patrick West - ToolMatch
  • Apr. 28, 2014 - Peter Fox - event calculus

Possible talks

Notes

  • Matt: from this area, fourth semester, graduate student
  • Each one else gives a self-intro
  • Patrick mentioned a few projects and tools: DCO, OpenDAP, Provenance, ToolMatch, ECOOP, Trac Tickets
  • Fox: we have sponsored projects at lab, but for eScience meeting we talk about research, not project affairs. Feel free to talk about your own work.
  • Patrick: every new comer should get a tw.rpi.edu account (get one at the low left part of the site page), get familiar with the repository we use, github, eScience email list, etc.

Linyun’s Presentation

  • Linyun’s Presentation about Data Theory: Wickett et al.’s and Mealy’s papers
    • Traditionally, data types are creeping
    • GH Mealy’s 1967 paper: real world >>> our theory >>> machine representation
    • Entities, values and data maps: data map as
    • signs value to attribute of entity
    • Structural maps and pointers
      • structured map: value is the entity itself  – use of pointer
    • Procedure and data processing
    • Access functions and data organization
    • Data description: a specification of machine data systems and representations
    • Data type: a fragment of data description, describing an entity and its application maps
    • Machine independence or representation independence, the latter!
    •  It’s about TRIPLES! Data science and RDF in now days are not a building in the air!
    • Wickett’s scientific data representation model 2012
    • Propositional content >>> symbol structure >>> Patterned matter and energy
    • Linyun: it provides a formal way to describe what provenance information is important. The model provides a list of items for such description
    • Mealy describes the real world to data structure to data; Wickett describes the provenance feature of a model