David Osumi Sutherland - Ontology-based Application Starter Kit (OBASK) скачать в хорошем качестве

David Osumi Sutherland - Ontology-based Application Starter Kit (OBASK)

Session: April 24 - Standards 1 - 03 Original Title: The Knowledge Graph Development Kit Abstract: The use of common biomedical ontologies to annotate data improves data findability, integration and reusability. Ontologies do this not only by providing a standard set of terms for annotation, but via the use of ontology structure to group data in biologically meaningful ways. One way to take advantage of this is via a knowledge graph in which ontologies and ontology semantics provide the glue that links content annotated knowledge and data in well documented and transparently queryable ways, providing an extensible base for building a APIs and applications and a potential input to machine learning. One barrier to fulfilling this potential is the lack of easily-usable standardised infrastructure for using ontologies and standard semantics to build and structure Knowledge Graphs in a form suitable for driving web applications. Triple stores can theoretically fulfil this role, but remain a niche technology and their standard query language (SPARQL) is not ideal to use for querying ontologies in OWL. Ensuring that web applications and APIs driven by knowledge graphs are easily usable by the biomedical community requires mechanisms to harness the power of semantics to label and categorise content in ways that are tailored to the application and the community. To overcome these barriers we built the Knowledge Graph Development Kit - a highly configurable containerised pipeline for integrating ontologies and curated information into easily queryable knowledge graphs. The pipeline consists of a triple-store integration layer that loads and integrates ontologies and curated content (TSV templates that the pipeline converts to RDF), and 3 front end servers: An OWLERY server supporting OWL-EL queries across ontologies and knowledge graphs; A Neo4j server that supports graph queries and visualisations and provides an accessible knowledge graph representation; A SOLR server that supports tuneable autosuggest with default settings that are optimised for ontology search and stores cached query results. A standard interconversion between OWL and Neo4J is central to this pipeline. It is optimised for human readable cypher queries and supports a highly configurable semantic tagging system built on the Neo4J label system. Semantic tagging is designed to harness the power of ontology and knowledge-graph semantics to add short, easily understandable, application-specific, human readable tags to ontology terms and annotated content. These semantic tags can be used as badges to efficiently communicate with users in terms that make sense to them, as a mechanism for configuring autosuggest search, for faceted browsing and even for configuring a web application We will present details of the pipelines and examples of their application in 3 different applications: Virtual Fly Brain, the Allen Brain Atlas Cell Type Explorer and The Cell Annotation Platform.