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Visualizing SWRL Rules with Grailog Frame Formulas

This project introduces a systematic approach to visualizing Semantic Web Rule Language (SWRL) rules using Grailog's graph representation. By integrating OWL and Datalog, we visualize slotted formulas for better comprehension of logic in SWRL. The Grailog framework aids cognitive understanding through graph-based imagery, providing an intuitive means to convey complex relationships and rules. The implementation is compatible with OWLViz in Protege and supports various graphical formats. Explore our GitHub repository for additional insights and contribute to the project.

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Visualizing SWRL Rules with Grailog Frame Formulas

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  1. Visualizing SWRL Rules Using Grailog Frame Formulas Team 8 : Bo Yan Juyan Zhang Ismail Akbari Instructor: Harold Boley

  2. Introduction • SWRL (Semantic Web Rule Language) is an implemented Semantic Web rule language, combining the sublanguages Web Ontology Language, Description logic (OWL DL) and Rule Markup Language (Unary/Binary Datalog). • Graph inscribed logic (Grailog) invokes imagery for logic proposed cognitively motivated systematic graph standard for visual-logic knowledge. • Visualizing SWRL’s Slotted Formulas in Grailog

  3. Unary/Binary Datalog formulas VS. Slotted formulas Three RuleML Syntaxes Syntax Visualization Symbolic Presentation Serialization RuleML/Grailog RuleML/POSL RuleML/XML

  4. Predicates: Unary Relations (Classes) General: Graph (class applied Logic to instance node) class class(inst1) HasInstance inst1 Example: Graph Logic Billionaire Warren Buffett Billionaire(Warren Buffett)

  5. General: Graph (labeled arc) Logic Predicates: Binary Relations binrel inst1 inst2 binrel(inst1, inst2) Example: Graph Logic Trust Trust (Warren Buffett, General Electric) Warren Buffett General Electric

  6. General: Graph (Object-Centered) (inst0-centered) Logic Object-Centered Logic:Grouping Binary Relations Around Instance class class(inst0)  binrel1(inst0, inst1)  binrel1 inst1 inst0 binreln(inst0, instn) . . . instn binreln Example: Graph (Object-Centered) (Socrates-centered) Logic Philosopher Philosopher(Socrates)  Substance(Socrates, P1)  Teaching(Socrates, T1) Substance P1 Socrates T1 Teaching

  7. Logic of Frames (‘Records’): AssociatingSlots with OID-Distinguished Instance General: Graph (PSOA-like Frame) (bulleted arcs) Logic class inst0#class( inst0 class, slot1= inst1, . . . slotn= instn slot1->inst1; slot1 inst1 . . . inst0 . . . slotn->instn) instn slotn Example: Graph (PSOA-like Frame) Logic Philosopher Socrates#Philosopher( Substance->P1; Teaching->T1) Substance P1 Socrates T1 Teaching

  8. Tools 1.OWLVIZ

  9. Be designed to be used with the Protege OWL plugin. • allowing comparison of the asserted class hierarchy and the inferred class hierarchy • has the facility to save to various concrete graphics formats including png, jpeg and svg.

  10. GITHUB

  11. A web-based hosting service for software development projects that use the Git revision control system. GitHub offers both paid plans for private repositories, and free accounts for open source projects. • Our projectrepository: https://github.com/boliuy/SWRL-RULES-VISUALIZER

  12. Implementation

  13. Step1: Convert into slotted fomulas syntax(U/B): syntax(slotted) Person(p)^ -> p#person( hassibling(p,c) hassibing->c) Array:

  14. swlrb: • swrlb:greaterthan -> age1 ( (age1,ag2) (greaterthan->age2) • array:

  15. Step2. Convert into dot template • color&shape for simple nodes • special shape for classes • add dots to the arrows which connects nodes belongs to different class

  16. Step 3 Generate graphs • using dot file as the input of graphviz

  17. An Example

  18. Person(?x) ^ Man(?y) ^ hasSibling(?x,?y) ^ hasAge(?x,?agel) ^ hasAge(?y,?age2) ^ swrlb:greaterThan(?age2,?age1) -> hasOlderBrother(?x,?y)

  19. body parts: • Person x null class • Man y null class • hasSibling x y property • hasAge x agel property • hasAge y age2 property • swrlb:greaterThan age2 age1 SWRL_Building • head parts: • hasOlderBrother x y property

  20. Conclusion • SWRL can be representd on Unary/Binary Datalogfomulars or Slotted formulars, and both of them have their own characters on graphs and logics. • Visulizing the slotted fomulars lets people easily to understand the logic of rules • Welcome to our projectrepository at the website of Githupto see and comment our project: https://github.com/boliuy/SWRL-RULES-VISUALIZER

  21. References • [1] http://en.wikipedia.org/wiki/Semantic_Web_Rule_Language. • [2] The GrailogSystematics for Visual-Logic Knowledge Representation with Generalized Graphs. Boley Harold, http://www.cs.unb.ca/~boley/talks/RuleMLGrailog.pdf. • [3] http://protege.cim3.net/cgi-bin/wiki.pl?SWRLTab. • [4] http://thechiselgroup.org/2004/07/06/jambalaya. • [5] http://www.co-ode.org/downloads/owlviz. • [6] SaeedHassanpour, Martin J. O'Connor, Amar K. Das, “Axiomé: a Tool for the Elicitation and Management of SWRL Rules”, OWL: Experiences and Directions (OWLED), Chantilly, VA, 2009. • [7] http://protegewiki.stanford.edu/wiki/Axiom%C3%A9.

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