Scientific Workflows Scientific workflows describe structured activities arising in scientific problem-solving. Conducting experiments involve complex and structured computations. Semantic mismatches among resources involve much human intervention. Participating services are owned by different organizations, defining compensations is critical to a successful recovery from failures. Semantically Resolving Type Mismatches in Scientific Workflows

Workflows in Bioinformatics Integrating different tools to solve biological problems Usually involves: Manual data transfer between applications Understanding data formats Converting file formats where appropriate Manual workflows involve a large number of steps. Manual execution is time-consuming and error-prone User is required to possess a deep knowledge and understanding of disparate application environments

Semantically Resolving Type Mismatches in Scientific Workflows WSWUBlast Service Operation Using tools in Bioinformatics blastn (query, database, ) blastn (query, database, ) Blast Service Specification of an in silico experimental design: Sequence Similarity Search DNA Sequence Similarity Search

Semantically Resolving Type Mismatches in Scientific Workflows Automated Workflows Make the task of creating a workflow a simple “drag and drop” process Make the resulting workflow diagram self documenting, showing exactly how to perform bioinformatics experiment Automatic execution of steps specified in workflow Monitoring workflow execution to help debugging and intervention Reduces complexity for scientific users, as well as support sharing and allow repeatability

Semantically Resolving Type Mismatches in Scientific Workflows Bioinformatics Workflow Systems Specialized workflow systems designed to develop workflows in bioinformatics Different workflow standards and systems: BPEL: Business workflow standard adapted for scientific workflows UNICORE: a Grid middleware, it provides a GUI for workflow devcelopment Globus: an open source toolkit implementing many Grid related standards Kepler: graph based modelling language to develop workflows Taverna Workbench: choreography tool for bioinformatics Web Services Triana: develop component based workflow and provide coupling with Grid middleware tools

Windows Workflow Foundation (1) Part of.NET Framework 3.0 Workflows are a collection of activities. Components Base Activity Library: Out-of-box activities and base for custom activities. Runtime Engine: Workflow execution and state management. Runtime Services: e.g. RDBMS, persistence, transactions Visual Designer: Graphical and code-based construction in Visual Studio or standalone Semantically Resolving Type Mismatches in Scientific Workflows

Windows Workflow Foundation (2) Semantically Resolving Type Mismatches in Scientific Workflows

Semantic Web Services The augmentation of Web service descriptions with Semantic annotations. Aims to automate Web service discovery, composition, invocation, and monitoring. Two different approaches: Revolutionary: OWL-S, and WSMO. Evolutionary: WSDL-S, and SAWSDL. The SAWSDL approach builds on existing Web service standards and is agnostic to ontology representation. Semantically Resolving Type Mismatches in Scientific Workflows

Semantic Annotations for Web Services Description Language SAWDL is an extension of WSDL using the extensibility elements. Two basic types of annotations: Model reference, associates selected WSDL components with Semantic concepts. Schema mapping, deals with data heterogeneity by transforming one data representation into another. Annotations for WSDL 1.1 and WSDL 2.0. API and tool support including: SWASDL4J, Woden4SAWSDL, Radiant... Semantically Resolving Type Mismatches in Scientific Workflows

SAWSDL Scope definitionimport types messagepartportTypeoperation input outputfaultbindingoperation input outputfaultserviceport Annotated using modelReference Annotated using modelReference with schemaMapping Note: - All elements may have as first child Semantically Resolving Type Mismatches in Scientific Workflows

SAWSDL Example <wsdl:definitions targetNamespace=" xmlns:wsdl=" xmlns:xs=" xmlns:sawsdl=" <xs:element name=“purchaseOrderResponse“ type=“xs:string” sawsdl:modelReference=" onse" sawsdl:liftingSchemaMapping=" …… <wsdl:input messageLabel="OrderRequestMessage" element=“purchaseOrderRequest"/> <wsdl:output messageLabel="OrderResponseMessage" element=“tns:purchaseOrderResponse"/> Semantically Resolving Type Mismatches in Scientific Workflows

Leveraging existing Java for.NET A C# implementation of the SAWSDL specification. Support of Model Reference annotations, OWL/RDF definitions. Lifting/Lowering schema support, XSLT/SPARQL mapping definitions. Allows the creation of SAWSDL based applications. Extends the.NET API for WSDL1.1. Support for WSDL2.0 through XSLT. Semantically Resolving Type Mismatches in Scientific Workflows

Implementation Development of a custom activity that extends the base Web Service activity shipped with WF. Enables a semi-automatic composition of Semantic Web Services, and the execution of the workflow. Can be composed with Web Services described using WSDL files. A C# implementation of the activity. Semantic capabilities are provided by the Jena library, integration with C# is enabled via IKVM. Semantically Resolving Type Mismatches in Scientific Workflows

Semantic Reasoning Model reference annotations describe the functionalities a Web service provides. Use ontologies as semantic models for the semantic annotations. Reasoning capabilities are provided by using: Jena, an open source Semantic Web framework for Java. Pellet, an open source Java OWL-DL reasoner. Currently support schema type and message part annotations to achieve automatic parameter binding. Semantically Resolving Type Mismatches in Scientific Workflows

Schema Type Mapping Provide mappings between XML and semantic models. Lifting Schema Mapping specifies mapping between WSDL Type Definitions in XML and semantic data. Used XSTL and XQuery as mapping languages. Lowering Schema Mapping specifies mapping between semantic data and WSDL Type Definitions in XML. Used SPARQL to query ontology, followed by XSTL and XQuery. Semantic data is queried through SPARQL, it is supported by Jena through its query engine. Semantically Resolving Type Mismatches in Scientific Workflows

IKVM.NET An implementation of Java for the Microsoft.NET Framework. It includes the following components: A Java Virtual Machine implemented in.NET. A.NET implementation of the Java class libraries. Tools that enable Java and.NET interoperability. Used to compile Jena and Pellet JAR libraries into.NET DLL assemblies, Java bytecode is translated to Common Intermediate Language (CIL). Allowed using Jena’s capabilities in the implementation of the Semantic Web service activity. Semantically Resolving Type Mismatches in Scientific Workflows

Semantic Web Service Activity (1) Activity bindings are the key feature that enables property binding between activities, or on the workflow itself. This mechanism allows data propagation between composed activities. WF rely on syntactic approaches when binding properties between activities. The SWS activity implements a basic semantic matching engine to better support semantically compatible properties. Semantically Resolving Type Mismatches in Scientific Workflows

Semantic Web Service Activity (2) Automatically bind SWS parameters to composed workflow activities using the semantic approach. The semantic model annotation of an activity’s input has to be equivalent or a subclass of the composed activity’s output one. Values are mapped to the appropriate data representation at design time. Missing activity bindings can be manually added using the WF visual designer. Semantically Resolving Type Mismatches in Scientific Workflows

Bioinformatics Workflow Example X14298 embl GetEntry getFASTA_DDBJEntry WSWUBlast M7WEXBN7013 Atgagtgatggagcag ttcaaccagacggtggt caacctgctgtcagaa atgaaagagctcagga tctgggaacgggtctgg aggcggg blastn accession sequence database jobID

Semantically Resolving Type Mismatches in Scientific Workflows WSWUBlast Automatic Binding in Bioinformatics Workflow blastn Semantic Reasoner Output Input SAWSDL Semantic Concept Degrees of Match: -Exact -Subclass Degrees of Match: -Exact -Subclass Bind Parameters, Carry out necessary translations Sequence DNA Sequence GetEntry getFASTA_DDBJEntry SAWSDL

Conclusion & Future Work API implementations that enable the development of semantically annotated Web services. Semantic Web service activity integration to WF, facilitating workflow building and manipulation. Future Work: Improve the SWS activity by processing more SAWSDL annotations, e.g. operation and portType. Semantically annotate Bioinformatics Web services, then use WF to build a workflow composed of SWS activities in order to test the implementation. Implement an approach to semantically guide and verify compensations and exceptions. Semantically Resolving Type Mismatches in Scientific Workflows