1. Hierarchical Search in SemantEco Support Varied Ontology Design Patterns Session: "Semantics for Biodiversity: Interoperability with genomic and ecological semantics" Patrice Seyed, Evan Patton, and Deborah McGuinness (presented by Nathan Wilson)

2. Introduction Multiple ontology design patterns for modeling taxonomic classification Vertebrate Taxonomy Ontology (VTO) – Taxons are represented as classes ‘Ictaluridae SubClassOf Siluriformes’ Phenoscape Ontology – Taxa as Individuals ‘Ictaluridae subclade_of Siluriformes’ Population thinking, inference of up-propagation from descendent species populations to ancestors ‘contains_clade o has_member -> has_member’ – A DL description of a clade is propagated up the clade taxonomy

3. Example Inference 1.Ictalurus_punctatus has_member some (has_part (caudal_fin and (bearer_of some bifurcated))) 2.Ictalurus_punctatus subclade_of Siluriformes 3.contains_clade o has_member -> has_member Infer a direct assertion about Siluriformes (the superclade of Ictalurus_punctatus): Siluriformes has_member some (has_part (caudal_fin and (bearer_of some bifurcated)))

4. SemantEco Modular Framework and the Hierarchical Search Component – Adheres to model-view-controller software architecture pattern separation between the underlying representation and that which is presented to the user – Allowing support of varied Knowledge Representation design patterns – Supports user interface rendering for navigation along different axes (e.g., generalization, partonomic, taxonomic)

5. SemantEco Module Framework and the Hierarchical Search Component SemantEco module designers can provide custom hierarchical search facets. Enable flexible navigation of resources via their relationships to others, to providing users with multiple paths for finding data. Leverages JavaScript Trees library (JSTrees) Each node maps to an RDF Resource, and the selection of a node triggers construction/execution of a SPARQL pattern for rendering immediate children nodes A SPARQL query pattern is provided by a module designer along the axes of interest for hierarchical navigation, for retrieving a tree’s root and children nodes. A data-level SPARQL pattern for search using tree selections is ultimately composed in conjunction

6. Flow Client interface selection maps to REST-ful web request Server side SPARQL Query executed, results to client as JSON

7. Phenoscape Faceted App

8. SPARQL Query for “Roots” prefix pheno: select DISTINCT ?child ?parent where { graph { ?child pheno:subclade_of ?parent. FILTER NOT EXISTS { ?parent pheno:subclade_of ?z } }

9. SPARQL Query for “Children” prefix pheno: select DISTINCT ?child ?parent where { graph { ?child pheno:subclade_of. }

10. Conclusions Enables one to develop ontologies and semantic web applications independently Either conceptualization described above for taxon modeling can be leveraged in the Hierarchical Search Facet component with the appropriate supporting SPARQL queries in place. This suits our immediate needs for semantic search in SemantEco as a portal and as an architecture, for a semantically-enabled monitoring environment it supports flexible search backed by semantics.

11. References http://phenoscape.org/wiki/Individual-based_taxonomy James P. Balhoff, Peter E. Midford, Hilmar Lapp: Integrating Anatomy and Phenotype Ontologies with Taxonomic Hierarchies. International Conference on Biomedical Ontologies, Buffalo, NY 2011