Semantic eScience Discussion July 15, 2014

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General Meeting Information

  • Previous Meeting
  • Call-in information
    • Goto Meeting
      • Dial +1 (805) 309-0012
      • Access Code: 776-009-689
      • Audio PIN: Shown after joining the meeting
      • Meeting ID: 776-009-689


  • Keep this list from week to week so we know who’s presented and who will present.
  • Please sign up here if you have a good topic to share with others.
  • May. 27, 2014 - introduction, summer plans, no presentation
  • Jun. 03 2014 - Linyun: programming the semantic web 
  • Jun. 10, 2014 - ODIP group (Cyndy, Bob, Adam S., Adam L., etc.) will be at TWC and use 1142 
  • Jun .17, 2014 - Jin: Entity Linking System Tutorial
  • Jun. 24, 2014 - No presentation
  • July. 01, 2014 - Marshall: Golden Spike information portal: a mash-up of vocabulary encoding, SPARQL query and data visualization for the domain knowledge of geologic time
  • July. 08, 2014 - No presentation
  • July. 15, 2014 - Paulo: Jefferson Project
  • July. 22 2014 - 
  • July. 29, 2014 - 
  • Aug. 05, 2014 - Peter Fox: event calculus


  • James Michaelis present on provenance work
  • Jefferson Project 
  • ToolMatch - Matt Ferritto
  • Anirudh - real time streaming data and analytics (PNNL)
  • GeoData 2014 report - Corey/Marshall/Peter
  • ESIP report - Patrick/Stephan/Peter
  • Web Science 2014 report (is anyone attending escience meetings from there)
  • Fall meeting sometime Stephan to present on
  • /ul>



    • Paulo’s talk: Jefferson Project

    Past Action Items

    • None

    Action Items

    • looking for volunteers for presentations


    • The project page for this effort is up at
    •   (this page is being updated by paulo and katie)
    • Will talk about ontologies put together for observation data at Lake George
      • schema for the database: ODM
      • ontologies for provenance, sensor infrastructure and measurement knowledge are needed to capture contextual knowledge of observational data
      • PROV-O for provenance, including human intervention, such as deployment of sensors
      • OBOE for measurement. OBOE is a modularized ontology
      • VSTO for sensors, only the part about how instruments are deployed and organized
    • IBM put millions of dollars worth sensors on the lake to understand and protect the lake
    • Lidar and 3d visualizations from recent scans are showing large differences between what was known previously.  (even more interesting since lake George was reasonably well monitored as lakes go )
    • all the marks in the maps generate data 24/7  (also paulo has a spreadsheet of all of the planned sensors - their types and the kind of data they generate)
    • salt put on the roads in the winter runs into the lake in the next spring. Don’t know for sure how much influence it will cause. the question of the impact of salt on the roads is one of the important questions that the jefferson project is addressing
    • Sensor Deployment Phasing 
      • privacy of data
    • software archtecture
      • Darrin Fresh Water Institute (DFWI) bolton landing (at lake george)
        • Lake George & surround area sensors
      • RPI
      • IBM research
    • Sensor Network Knowledge
      • what are the physical entity characteristics being measured
      • how these characteristics relate to data values and measurement units
    • Selected Ontologies
      • Provenance knowledge
      • sensor infrastructure knowledge
      • measurements knowledge
    • PROV-O Concepts
    • OBOE Concepts
      • Example of entity: air, earth, the lake
    • VSTO Concepts
      • extract a portion of the ontology about how the instruments are deployed and organized - note to patrick/stephan - we may think about the general reusability of the instrument portion of vsto and possibly break it out as a  separate (extensible) module
    • alignments between VSTO and OBOE
    • alignments between PROV-O and OBOE
    • alignments between VSTO and PROV-O
    • HASNetO - Human Aware Sensor Network Ontology (the slide has an old name - HIO - human intervention ontology - the focus on humans is because humans have to make updates to the sensor deployments and both install and tune them)
    • Alignments and Additions summary
    • Lifecycle of the sensor
    • seeking to move away from hard-coded knowledge

    Hoped for discussion was to look at similarities and differences between this work and the stom work - because of the delays in getting started, we may have to move some of this discussion to email / or follow up discussion

    • suggestion
      • software configuration (todo - stephan email Paulo related paper) 
    • overlap
      • time series of data (statistics)  - momo is looking at sensor data but from this time series perspective using a small number of sensors (or a small number of sensor types)