Data Mesh-up and Mapping using
              Semantic Wiki
     -- with use cases in RPI Map1 and VSTO
                   ...
Tetherless Map Extension
Features
• Data presentation:
   –   Map a coordinate
   –   Map results of a semantic query
   –...
Two Parser Functions
                          Semantic query

{{#map_objects: {{#ask:                    {{#insert_map:
 ...
RPI Map
                        http://map.rpi.edu
                                                 RPI Event Feed
       ...
RPI Map
 External Data   Mediators


                                 Wiki DB
                  Semantic       Wiki Text
 ...
RPI Map


Balloon tip
                               Layer Control




                Bus Tracking




              Main...
RPI Map




RSS Feed
RPI Map
• Why semantic wiki helps?
  – Lessen naming heterogeneity:
      • where are Incubator Center, Peoples Ave Comple...
VSTO
 VSTO = Virtual Solar Terrestrial Observatory
    vsto.hao.ucar.edu, www.vsto.org



                                ...
VSTO Instrument List
  (the traditional way)
VSTO Instrument Map




               VSTO instrument Map
Data source: imported from VSTO instrument ontology
           ...
VSTO Instrument Map




             Real time satellite tracking
Data source: real time query to n2yo.com
Lessons Learned
• Data Integration is the most difficult part
   – Heterogeneity everywhere
   – Data agent/mediator/conve...
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Data Mesh-up and Mapping using Semantic Wiki

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Data Mesh-up and Mapping using Semantic Wiki

  1. 1. Data Mesh-up and Mapping using Semantic Wiki -- with use cases in RPI Map1 and VSTO Map2 Joint Work of Jie Bao, Zheng Jin Guang, Rui Huang, Li Ding Jan 22, 2009 1 http://map.rpi.edu/ 2 http://onto.rpi.edu/wiki/vsto
  2. 2. Tetherless Map Extension Features • Data presentation: – Map a coordinate – Map results of a semantic query – Displays information provided in a KML file. – Layer control. • Navigation: – Location browser – Search and filtering
  3. 3. Two Parser Functions Semantic query {{#map_objects: {{#ask: {{#insert_map: [[Category:Location]] 17.3,17.8 | ?Has LatLong |2 | ?Has URL |G_HYBRID_MAP | ?Has short name |GLargeMapControl | ?Has service |class1 | ?FOAF:page |800 |600 |limit=200 |border: thin dotted#00FF00 |link=none}} |<b>This is an example</b> |Route;http://shuttles.rpi.edu |Empire Building /data/route.kml }} }} Integrate KML file as a map layer 3
  4. 4. RPI Map http://map.rpi.edu RPI Event Feed Event •RPI Building Listing •Parking Map Building Course RPI Catalog Google Map Service People User input RPI Directory Shuttle GPS
  5. 5. RPI Map External Data Mediators Wiki DB Semantic Wiki Text Form Publisher Wiki Template Google Map API SMW RDF DB RDF Consumer Query Semantic Query result 5
  6. 6. RPI Map Balloon tip Layer Control Bus Tracking Main interface
  7. 7. RPI Map RSS Feed
  8. 8. RPI Map • Why semantic wiki helps? – Lessen naming heterogeneity: • where are Incubator Center, Peoples Ave Complex J, J Building, or J Bldg ? – Data can flow (by semantic query) • E.g., Today’s events, Events at a building, Person in the same building – (a little bit) reasoning • All seminars are also meetings (and events) – The wiki-way to improve data • Anybody, anytime, anywhere, anything
  9. 9. VSTO VSTO = Virtual Solar Terrestrial Observatory vsto.hao.ucar.edu, www.vsto.org Instrument management Goal: a unified semantic environment serving data from diverse data archives in the fields of solar, solar-terrestrial, and space physics
  10. 10. VSTO Instrument List (the traditional way)
  11. 11. VSTO Instrument Map VSTO instrument Map Data source: imported from VSTO instrument ontology http://onto.rpi.edu/wiki/vsto
  12. 12. VSTO Instrument Map Real time satellite tracking Data source: real time query to n2yo.com
  13. 13. Lessons Learned • Data Integration is the most difficult part – Heterogeneity everywhere – Data agent/mediator/convertors critical • As parser function/shell script/javascript reload/KML feed, etc. – Semantic wiki makes it easier • Both semantics and wiki should be invisible to users – Wiki as a light-weight RDF database – By Semantic Forms, Templates, Skin and other UI tricks – But recoverable if user needs

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