Enriching the Ontology for Biomedical Investigations (OBI) to Improve Its Suitability for Web Service Annotations Chaitanya Guttula, Alok Dhamanaskar, Rui Wang, John A. Miller, Jessica C. Kissinger Jie Zheng, and Christian J. Stoeckert, Jr. 1. Analyze WSDL/WADL Documentation Concepts added to Ontology Conclusions and Future Work Semantic annotation of Web services for WUBLAST, NCBIBLAST, ClustalW, t-coffee, Signal-P and WSDBFetch has resulted in creation of 90 new ontology terms. We have proposed these terms to the OBI Community and are pending approval. We will continue to annotate more web services and tools in the bioinformatics domain. As more concepts are covered we expect our need to create new terms to decrease. Preliminary Evaluation confirms that annotated web services give better results when used with suggestion engine than un-annotated ones. Which supports the usefulness of the terms added to OBI and reinforces our belief in the methodology we used for enriching the OBI. We are working on improving the performance of the Suggestion Engine such that it can make better use of the rich annotations we are providing. And a more comprehensive evaluation can be expected soon. We are also working on a Web Service Discovery Tool that will take semantic annotation into account when searching for Web services. We also plan to enhance our annotation tool to facilitate fast annotation of WSDL files. References : 1.Phillip Lord et al.: Applying Semantic Web Services to Bioinformatics. 2.Barry Smith, et al.: The OBO Foundry: Coordinated Evolution of Ontologies to Support Biomedical Data Integration. 3.Brinkman RR, et al.: Modeling Biomedical Experimental Processes with OBI Rui Wang, et al: Web Service Composition using Service Suggestions. Acknowledgements: Funding for this study was provided in part by NIH R01 GM Ontologies provide a rich modeling framework, reasoning capabilities, facilitate community agreement and are Web accessible making them an ideal candidate to annotate tools and Web services. OBI (Ontology for Biomedical Investigation) o OBI[3] includes terms that are applicable across various biological & technological domains. o With BFO as an upper level ontology, OBI is interoperable with other OBO [2] compliant ontologies. o Annotation of tools or web services typically involves describing -- the operations -- their inputs and outputs o OBI’s existing structure makes it easier to enrich it with concepts to support Web service annotations We are collaborating with EDAM [4] group in our efforts to enrich OBI. (EDAM is an ontology that provides a controlled vocabulary for description of bioinformatics tools and data.) Motivation Real world data analysis tasks often require coordinated use of multiple tools. There has been a dramatic increase in Web services and tools in the biomedical community but there is a need for an easy way to design workflows. A large number of tools are available for the construction of workflows (e.g. in the Galaxy system) and additional tools can be added with Web services. However, the user must know how, a priori, to construct them into a logical workflow. (Figure 1). Semantic annotation of Web services and tools can be used to assist the user in creating bioinformatics workflows[1] as it can adequately describe the input, output and functionality of the tools. processual_en tity Planned Process Web service WS Operation Entity Information Content Entity Data Item Data Format Specification continuant occurrent Evaluation and Application of Semantic Annotations Effectiveness of annotations: Evaluation from Rui Wang et al. [5] The Figure above confirms that the annotated Web services perform better for service discovery and suggestions than un-annotated ones. Evaluations indicated functionality annotations (annotations on operations) contribute the most towards suggesting correct Web services, followed by input/output annotations and finally precondition/effects annotations. Suggestions Figure 1 – Galaxy Workflow Designer. Galaxy is an easy to use Web-based platform that provides a way to construct workflows using existing tools in a very simple fashion. However, even Galaxy presents challenges. Often, there are hidden steps that may not be apparent to a novice user. Is it possible to provide service suggestions (that make use of semantic annotation) that will help a user construct a workflow to bridge the gap between A and B? Figure 2 – OBI top level hierarchy extended to add Web service and WS Operation. Web service operation and Web service are types of planned process and inputs and outputs are types of Information content entity. Figure 3 – Utilization of suggestions to add workflow steps The suggestion Engine has been loosely coupled with Galaxy, such that it returns a ranked list of suggested Web Service Operations based on the current state of the workflow and desired functionality supplied by the user (optional). Abstract : With the increasing development and use of ontologies in the bioinformatics domain, opportunities for their utilization in applications and workflows are being created. In our effort, we discuss how the Ontology for Biomedical Investigations (OBI) can be enriched to support annotation of Web services. The methodology includes designing ontology analysis diagrams for Web services and analyzing them to find the terms that are need to be added to the ontology. The enriched ontology is then used for annotating the Web services. Using annotated Web services to perform service discovery and make service suggestions provides a way to evaluate the validity of the annotations made and the terms added to the ontology. Part of Ontology Analysis Diagram for WUBlast Once we have proposed the term, defined it, determined its relationships with other terms, and determined the hierarchy in the ontology where it can be added, we add the term to the ontology using Protégé. On adding terms to the ontology, we check the ontology for consistency using the Hermit Reasoner. Methodology to Enrich OBI Top k Suggestions Blast Analysis..? Suggestion Engine: 2. List the proposed terms in the Terms Template 3. Create a Web Service specific Ontology analysis diagram based on generic model 4. Provide the textual definition 5. Add terms to OBI Generic Ontology Analysis diagram, which serves as a model for creating Web Service Specific diagrams 1.identify super class in OBI and 2.reveal relationship with other terms We have a standard template which we populate as we proceed with proposing terms, defining them and determining the hierarchy. Populated Proposed terms template A B BLAST Sequence Analysis Multiple Pairwise sequence alignment using ClustalW The output of getResult operation for WUBLAST returns a list of SequenceIds The run operation for ClustalW accepts sequences to be aligned as inputs Operations of WuBlast annotated with enriched OBI Operations of ClustalW Web Service annotated with enriched OBI <xsd:element maxOccurs="1" minOccurs="1" name="jobId“ nillable="false“ type="xsd:string"/> <xsd:element maxOccurs="1" minOccurs="1" name="type“ nillable="false" type="xsd:string"/> 1 1 Excerpts from a WSDL file for WUBLAST web service <xsd:element maxOccurs="1" minOccurs="1" name="jobId“ nillable="false“ type="xsd:string“ sawsdl:modelReference= “ /> <xsd:element maxOccurs="1" minOccurs="1" name="type“ nillable="false" type="xsd:string“ sawsdl:modelReference=" Excerpts from WUBLAST WSDL with enriched OBI