Biotea: RDFizing PubMed Central in Support for the Paper as an Interface to the Web of Data

Leyla Garcia CastroDepartamento de Leguajes y Sistemas Informáticos

Universitat Jaumé I

Alexander Garcia, Casey Mclaughlin, Institute for Digital Information,

Florida State University. Tallahassee

Corresponding author: alexgarciac@gmail.com

In a nutshell, Biotea at http://biotea.idiginfo.org• Is a semantic dataset for full-text, open-access subset of PubMed Central• Makes extensive use of existing ontologies and semantic enrichment services• Supports the generation of self-describing machine- readable scholarly

documents. • Comprises a flexible and adaptable set of tools for metadata enrichment and

semantic processing of biomedical documents.• Provides semantically rich and highly interconnected dataset with self-describing

content.

AGC and CM have been funded by US DoD Grant MOMRP w81xwh-10-2-0181.

Scholarly data and documents are of most value when they are interconnected rather than independent Christine L. Borgman

Consuming the dataset, a first prototype

Graph-based retrieval for the terms “catalase”; only shared terms with more than 30 associated biological terms are included in the results.

Search and retrieval based on human gene names: the term is resolved with GeneWiki, and the associated UniProt accession is used in the query

RDF4PMC and Bio2RDF

1. Retrieval: Metadata + Cloud of annotations

Enriched content based on annotations is displayed in the interactive zone

Interactive zone

Contextual reading

Graphical tools

2. Enriched content facts-based reading

NXML

MetadataBIBO

RDFized article

Content CNT Provenance PROV-OVOID

Annotation

Enriched contentRDFization

1. Metadata & content

2. Semantic content enrichment

RDF4PMC, our workflow

3. Navigating the neighborhood

Consuming the dataset, SPARQL and API Retrieval Service

A list of terms and their related topics http://biotea.idiginfo.org/api/terms

A list of topics and their related vocabularies http://biotea.idiginfo.org/api/topics

All topics related to a term e.g., http://biotea.idiginfo.org/api/topics?term=cancer

All vocabularies related to a term e.g., http://biotea.idiginfo.org/api/vocabularies?term=cancer

All terms that start with a specific string (for autocompletion) e.g.,http://biotea.idiginfo.org/api/terms?prefix=canc

All topics related to a vocabulary e.g., http://biotea.idiginfo.org/api/topics?vocabulary=po

RDF of articles that include a term e.g., http://biotea.idiginfo.org/api/articles?term=cancer

Count of RDF of articles that include a term e.g., http://biotea.idiginfo.org/api/articles?term=cancer&count=true

A list of vocabularies and their prefixes http://biotea.idiginfo.org/vocabularies

RDF of articles that include a vocabulary e.g., http://biotea.idiginfo.org/api/articles?vocabulary=po

SPARQL query Query expressed in natural language

SELECT distinct ?pmidWHERE { ?article a bibo:AcademicArticle ; bibo:pmid ?pmid .?annotation a aot:ExactQualifier ;ao:annotatesResource ?article ;ao:hasTopic <http://purl.obolibrary.org/obo/CHEBI_60004> .}

Retrieving PubMed identifier for those articles that

have been semantically annotated with the biological

entity CHEBI:60004. The semantic annotation comes

from the occurrence of the term “mixture” in any

paragraph of the retrieved articles.