Grant Number: IIS Institution of PI: Arizona State University PIs: Zoé Lacroix Title: Collaborative Research: Semantic Map of Biological Data Sources: Entity Identity and Path Characterization Research Objectives:Significant Results: Approach: Graphic: Broader Impact: A fundamental problem facing the biological researcher today is correctly identifying a specific instance of a biological entity, e.g., a specific gene or protein, and then obtaining a complete functional characterization of this entity instance by exploring a multiplicity of inter-related sources. An example question that could be answered by such a correct and complete characterization is as follows: “What cancer-related proteins have been identified and what knowledge has been collected by other researchers over the past two years?” In this project, we develop technology to represent the complexity of biological resources using a semantic map that reflects the view of biologists. The first step is identifying scientific objects or entities represented by these sources and capturing the properties that characterize them. Once entities are characterized, relationships and links among entities will be explored and exploited. 1- Identifying biological resources to evaluate queries Scientists have limited knowledge of the multiple resources made available to them. There are many reasons for this including: too many resources (thousands), different content, format, data access, data analysis, data clustering, data quality. Therefore there is a need to guide scientists in the process of expressing queries. The first contribution of the project is the BioNavigation system that provides scientists the ability to express scientific queries at a high (logical) level and extract from these queries the 'navigational‘ component (i.e., the sub-query that expresses the abstraction of resources to be queried). We express this sub-query as a regular expression. 2- Exploiting discrepancies of biological resources within the query process The study made on 4 resources at the NIH National Center for Biotechnology Information (NCBI) shows that different evaluation paths have different properties: they retrieved different entries, they retrieved different characterization (number of attributes), they have different costs (time and space). These characteristics may be exploited in the query process to optimize (or minimize) the number of retrieved entries, their characterization, and the cost of evaluation. Developed technology will support life scientists in their research. A system that provides information about available resources is a critical need to support scientific discovery. The BioNavigation System Browse Mode Visualize the conceptual, physical graphs and mappings Learn about sources and capabilities by right click on the node Options to change the visualization of the two graphs Query mode Build regular expression by selecting conceptual level nodes and selection buttons Specify if intermediate nodes can be included in the path Set Physical constraints (i.e. only paths using or avoiding a particular data source) Results Submit the regular expression to execute the E-Search Display the list of paths ordered by rank to the user