Changes between Version 14 and Version 15 of PimoService


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Timestamp:
09/20/06 23:26:23 (18 years ago)
Author:
nadeem
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  • PimoService

    v14 v15  
    66[http://www.dfki.uni-kl.de/~sauermann/2006/01-pimo-report/pimOntologyLanguageReport.html PIMO Technical Report]), which is an improved manifestation of the Wikitology idea. 
    77 
    8  * Interface: source:branches/gnowsis0.9/gnowsis-server/src/java/org/gnowsis/pimo/PimoService.java 
     8 * Interface: source:trunk/gnowsis-server/src/java/org/gnowsis/pimo/PimoService.java 
    99 * JavaDoc: [http://www.gnowsis.org/statisch/0.9/doc/gnowsis-server/javadoc/org/gnowsis/pimo/PimoService.html PimoService.html] 
    1010 * on inference: PimoInference 
     
    3535The semantics of the PIMO language allow us to verify the integrity of the data. In normal RDF/S semantics, verification is not possible. For example, setting the domain of the property knows to the class Person, and then using this property on an instance Rome Business Plan of class Document creates, using RDF/S, the new information that the Document is also a Person. In the PIMO language, domain and range restrictions are used to validate the data.  
    3636The PIMO is checked using a Java Object called PimoChecker, that encapsulates a Jena reasonser to do the checking and also does more tricks: 
    37  * source:branches/gnowsis0.9/gnowsis-server/src/java/org/gnowsis/pimo/impl/PimoChecker.java 
     37 * source:trunk/gnowsis-server/src/java/org/gnowsis/pimo/impl/PimoChecker.java 
    3838 
    3939The following rules describe what is validated in the PIMO, a formal description is given in the gnowsis implementation's PIMO rule file. 
     
    7575As the user is assisted through all these steps, and intelligent default values are entered beforehand, it may be that many RDF graphs can be made valid through this import assistant. We hope that this approach keeps invalid RDF out of the store and on the other hand lets  users import as many external RDF sources as possible. Similar to piggy-bank, scripts are needed for this task. 
    7676 
    77 The interesting part is now, that this import assistant can be realised as centralised online (web 2.0 like) application. Users can let the online service "pimo transformation server" run its magic on any RDF they find in the net. If one user writes a useful import script for, say, FOAF, then the script is stored at the transformation server. So the transformation scripts are "user generated content" and shared within the Gnowsis/Nepomuk commmunity. A core element in this approach are tools like the "Exobot" (source:branches/gnowsis0.9/gnowsis-server/src/java/org/gnowsis/exobot/Exobot.java) or Haystack's adenine programming language. The scripts to transform RDF from one state to another can be written using a combination of SPARQL, inference rules, and other operations. There is no need to install a runtime for this language, one installation of the transformation engine at the transformation server is a good start. 
     77The interesting part is now, that this import assistant can be realised as centralised online (web 2.0 like) application. Users can let the online service "pimo transformation server" run its magic on any RDF they find in the net. If one user writes a useful import script for, say, FOAF, then the script is stored at the transformation server. So the transformation scripts are "user generated content" and shared within the Gnowsis/Nepomuk commmunity. A core element in this approach are tools like the "Exobot" (source:trunk/gnowsis-server/src/java/org/gnowsis/exobot/Exobot.java) or Haystack's adenine programming language. The scripts to transform RDF from one state to another can be written using a combination of SPARQL, inference rules, and other operations. There is no need to install a runtime for this language, one installation of the transformation engine at the transformation server is a good start. 
    7878 
    7979The goal here is that users can import as much RDF as possible, and if one user found out how to transform data into valid PIMO, then this "how-to" information is stored into a script, that can be used by the next user. Based on paths of source files or classes found inside the new rdf, it is easy to program a case-based-reasoning machine that suggests which script may be used to make a file valid.