Abstract
BackgroundThe World Wide Web has become a dissemination platform for scientific and non-scientific publications. However, most of the information remains locked up in discrete documents that are not always interconnected or machine-readable. The connectivity tissue provided by RDF technology has not yet been widely used to support the generation of self-describing, machine-readable documents.ResultsIn this paper, we present our approach to the generation of self-describing machine-readable scholarly documents. We understand the scientific document as an entry point and interface to the Web of Data. We have semantically processed the full-text, open-access subset of PubMed Central. Our RDF model and resulting dataset make extensive use of existing ontologies and semantic enrichment services. We expose our model, services, prototype, and datasets at http://biotea.idiginfo.org/ConclusionsThe semantic processing of biomedical literature presented in this paper embeds documents within the Web of Data and facilitates the execution of concept-based queries against the entire digital library. Our approach delivers a flexible and adaptable set of tools for metadata enrichment and semantic processing of biomedical documents. Our model delivers a semantically rich and highly interconnected dataset with self-describing content so that software can make effective use of it.
Highlights
The World Wide Web has become a dissemination platform for scientific and non-scientific publications
The Biotea project comprises and makes available (i) a set of Resource Description Framework (RDF) files generated from the open-access subset of PubMed Central (PMC) and enriched with semantic annotations, (ii) a Web Services Application Programming Interface (API) for querying the RDF dataset, (iii) a SPARQL Protocol and RDF Query Language (SPARQL) endpoint containing a subset of the RDF files as a proof of concept, (iv) an article-centric prototype that acts as an interface to the Web of Data (WoD), and (v) an implemented transformation process from our RDF files to Bio2RDF [18,19]
Annotations are scaffolded by using the Annotation Ontology (AO), domain knowledge is identified by means of domain ontologies, and documents are structured by using DOCO, Bibliographic Ontology (BIBO), Dublin Core Metadata Initiative (DCMI) Terms, and others
Summary
The World Wide Web has become a dissemination platform for scientific and non-scientific publications. Most of the information remains locked up in discrete documents that are not always interconnected or machine-readable. The connectivity tissue provided by RDF technology has not yet been widely used to support the generation of self-describing, machine-readable documents. Scholarly communication has been complemented by the adoption of blogs, mailing lists, social networks, and other technologies that in combination support the tissue, by means of which scholars communicate their work and establish connections with one another. Most of the information remains locked up in discrete documents without machine-processable content. Such interconnectedness and structuring would facilitate interoperability across documents as well as between publications and online resources resources available online. Data and documents are of most value when they are interconnected rather than independent [2]
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