FP OntoGrid: Paving the way for Knowledgeable Grid Services and Systems Monterey, July 26th 2007 KOPE: Knowledge-Oriented Provenance Environment Jose Manuel Gómez-Pérez, Francisco Javier García (iSOCO), Rafael González (UPM), Chris Van Aart (Y’All)

2 Motivation  Goals  Increase understanding of process execution  Explain provenance in a way closer to how domain experts reason on a given problem  Problem Solving Methods [McDermott,1988] Provenance (Source: UoS micro-site) Provenance Pyramid (Source: myGrid)

3 Problem Solving Methods (PSM)  PSM are knowledge templates that  Establish and control the sequence of actions required to perform a task  Define the kind of knowledge necessary at each task step  Hierarchically specify how tasks decompose into subtasks down to the level of primitive actions  Describe tasks at several levels of refinement  PSM are domain-independent  PSM inputs and outputs modelled as generic roles  Reusable across different domains

4 Problem Solving Methods Visualization Paradigm Decomposition viewInteraction view Knowledge Flow view

5 Applications of Problem Solving Methods  Knowledge Engineering  Knowledge acquisition: Guidelines to acquire problem solving knowledge  Reasoning: Enable flexible reasoning by selecting methods during problem solving  Process analysis: Description of the main rationale of (reasoning) processes  Provenance Interpretation  Explain the results of queries on process documentation

6 Who defines Problem Solving Methods?  Ideally, collaboratively defined by a community of domain experts  Canonical specifications of domain processes  Agreed throughout the community  Examples: Regulations for good medical praxis Diagnosis Reasoning (CommonKADS)  Also possible: knowledge engineer with a little domain knowledge, e.g. population-based brain atlas

7 Provenance Interpretation Workflow

8 Semantic Resources PSM meta-model Domain ontology Roles (catalogue task)  Bridge: Explicit definition of mappings between domain and PSM entities  Refiner: Specification of task decomposition into subtasks

9 Annotation of Process Documentation PASOA interaction p-assertion Automatically annotated against the domain ontology during process execution

10 Twig Matching Algorithm  twig_join(D, i(P), o(P)) is a boolean function which checks whether a twig exists that connects i(P) and o(P) in D, where:  P is a problem solving method  i(P) is the set of input roles of P  o(P) is the set of output roles of P  D is the provenance DAG of the documented process, returned by a provenance query  We consider P as an interpretation of a process if twig_join(D, i(P), o(P)) = true  Bridges allow detecting occurrences of PSM roles in D  Refiners allow applying the algorithm recursively across the PSM hierarchy

11 Twig Matching for Brain Atlas workflow and Catalogue Brain Atlas Provenance Data Flow Prime Catalogue Method Knowledge Flow Brain Atlas Workflow

12 Demo

13 Thanks for your attention! iSOCO Valencia Oficina 107 C/ Prof. Beltrán Báguena 4, Valencia iSOCO Barcelona Edifici Testa A C/ Alcalde Barnils St. Cugat del Vallès Barcelona iSOCO Madrid C/Pedro de Valdivia, Madrid iSOCO Jose Manuel Gómez-Pérez #T #M