RDF for PubMedCentral

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Information about RDF for PubMedCentral

Published on February 15, 2014

Author: alexgarciac

Source: slideshare.net


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.

2/14/2014 Biotea, RDF4PMC RDF4PMC, RDFizing PubMed Central Alexander Garcia1, Leyla Jael García Castro2, Casey McLaughlin1 1Florida State University 2Universitat Jaume I 1

The Biotea project Why Semantic Web Technologies? RDF4PMC in a nutshell Architecture RDFization process • • • • PMC RDFization Content enrichment Some numbers for RDF4PMC Architecture • Using the data • • • • • • • • • SPARQL Bio2RDF integration Web services A first prototype Challenges and Lessons Currently working on… Future Work Conclusions Acknowledgments Biotea, RDF4PMC • • • • • 2/14/2014 Outline 2

Christine L. Borgman • Methodologies, methods and techniques supporting semantic enrichment of scholarly communication • Once enriched, then how is this changing our user experience? Biotea, RDF4PMC Scholarly data and documents are of most value when they are interconnected rather than independent 2/14/2014 Biotea 3

Biotea • How are publications connected to each other? • Putting together explicit assertions from different papers to form new implicit assertions • Semantic Web Technology supporting scholarly communication, Literature Based Discovery and the SearchRetrieval-and-Interacting-with-the-Document (SRID) processes Biotea, RDF4PMC Christine L. Borgman 2/14/2014 Scholarly data and documents are of most value when they are interconnected rather than independent 4

• Retrieve all papers that have a component X (CHEBI) and the cellular location in GO terms Biotea, RDF4PMC • Generates an adaptable open approach, the data becomes the platform • The SW delivers an integrative platform • Makes it easier for the community to build over the platform • Simplifies programmatic access to information 2/14/2014 Why SWT for research documents • As simple as relating terminologies • Delivers Social Network ready content 5

Biotea, RDF4PMC • Delivers an interoperable, interlinked, and selfdescribing document model in the biomedical domain. • A network of interconnected documents • Semantic infrastructure for PMC • An interface to the Web of Data • A knowledge model for biomedical literature – easily extendible 2/14/2014 RDF4PMC in a nutshell 6

Biotea, RDF4PMC • RDFizing biomedical literature by orchestrating ontologies such as • DoCO, BIBO, DC, FOAF, W3CPROV, and others • Datasets are available • RDF for metadata and content • RDF for annotations from text-mining • RDFizator will be available • Adding other ontologies and annotators is possible • Working with XML from other sources is possible 2/14/2014 RDF4PMC in a nutshell 7

PMC RDFization RDF Generation Biotea, RDF4PMC References Enrichment 2/14/2014 Metadata+ Content + References RDFReactor PMC NXML 8

9 Biotea, RDF4PMC 2/14/2014

Annotations: Content Enrichment Biotea, RDF4PMC 2/14/2014 Enriched RDF RDF Generation Automatic Annotation Web service Metadata+ Content + References Web service 10

11 Biotea, RDF4PMC 2/14/2014

Biotea, RDF4PMC 2/14/2014 RDF4PMC, some numbers 12

RDF4PMC Server Architecture RDF DB Slave RDF DB Master Master Server Import scripts + RDF files PMC RDFization Web & SPARQL Server (development) RDF DB Slave Web & SPARQL Server (production)

Consuming the data: SPARQL Query expressed in natural SPARQL query language Retrieving PubMed ?article a bibo:Document ; bibo:pmid ?pmid ; identifier, article title, dcterms:title ?title . section title, and ?section a doco:Section ; paragraphs for those dcterms:isPartOf ?article ; dcterms:title ?secTitle . Biotea, RDF4PMC WHERE { 2/14/2014 SELECT ?pmid ?title ?secTitle ?text  articles containing the FILTER (regex(str(?secTitle), "introduction", "i")). ?para a doco:Paragraph ; dcterms:isPartOf ?section ; term “cancer” in any section whose title cnt:chars ?text . FILTER (regex(str(?text), "cancer", "i")). } LIMIT 50 includes “introduction” 14

Consuming the data: SPARQL Query expressed in natural Retrieving PubMed identifier SELECT distinct ?pmid for those articles that have WHERE { been semantically annotated ?article a bibo:AcademicArticle ; with the biological entity bibo:pmid ?pmid .  Biotea, RDF4PMC language 2/14/2014 SPARQL query CHEBI:60004. The semantic ?annotation a aot:ExactQualifier ; annotation comes from the ao:annotatesResource ?article ; occurrence of the term ao:hasTopic <http://purl.obolibrary.org/obo/CHEBI_60004> . “mixture” in any paragraph } of the retrieved articles. CHEBI:60004 A mixture is a chemical substance composed of multiple molecules, at least two of which are of a different kind 15

Annotations Biotea, RDF4PMC 2/14/2014 Content Metadata & References Bio2RDF Integration 16

Consuming the data: Web services Retrieval Service 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 2/14/2014 http://biotea.idiginfo.org/api/terms Biotea, RDF4PMC A list of terms and their related topics 17 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

Semantically enriched publication Metadata+ Content + References Automatically Annotated RDF Biotea, RDF4PMC 2/14/2014 Consuming the data: a dashboard for semantic bio-publications SPARQL 18 Catalase

Consuming the data: first prototype Cloud of Bio-annotations (term + # of bio-entities) 2/14/2014 Title & authors Biotea, RDF4PMC Links Abstract Paragraphs containing the annotation selected by the user Graphical tools 19

Biotea, RDF4PMC 2/14/2014 Consuming the data: A first prototype 20

Challenges and Lessons Tables and images  Links Inline tables  Format is lost Supplementary material Most of them follow one DTD but … • References • At least 4 different styles • Some times are just plain text Biotea, RDF4PMC • • • • 2/14/2014 • Content • Annotators • Not always available • Stop words are tricky 21

Challenges and Lessons • Annotation is context dependent Biotea, RDF4PMC • Delivering the expressivity of the data set to the end user is a complex issue 2/14/2014 • Where are the facts? How to validate the facts? • Maintaining the triplet store has a learning curve of its own • Building SW infrastructure is H A R D 22

Currently working on: Literature Discovery Process • Search • Usually string-based search mechanisms • Little cognitive support • Retrieval • Simple list of DB entries • Little cognitive support • Interacting with the document • Straight into the PDF • Zero cognitive support • Data availability

Currently working on: Literature Discovery Process • Search • Usually string-based search mechanisms • Little cognitive support • Retrieval • Simple list of DB entries • Little cognitive support • How, why and where are a set of documents similar? • Interacting with the document • Straight into the PDF • Zero cognitive support

Currently working on: Literature Discovery Process • Search • Usually string-based search mechanisms • Little cognitive support • Retrieval • Simple list of DB entries • Little cognitive support • Interacting with the document • Straight into the PDF • Zero cognitive support

Future Work • User Experience • • • • Web services for data analysis RDF browser More visualization tools Supporting and taking advantage of the structure of the document • Collaborative element Biotea, RDF4PMC • URI standardization following similar patterns to identifiers.org and Bio2RDF • Integration into Bio2RDF • Dataset identification and summary (void) • Improve data for references 2/14/2014 • RDF 29

Future Work Biotea, RDF4PMC • From PDF to XML to RDF to Enriched Metadata for the PDF • The PDF is gently introduced in the WoD • Once the metadata has been enriched then 2/14/2014 • Application in Clinical Psychology, the MSRC case • Rich interaction supporting: SEARCH-RETRIEVALINTERACTION WITH THE DOCUMENT (PDF) 30

Conclusions • New vocabularies as well as annotators can easily be plugged in • Our approach is useful for both open and non-open access datasets Biotea, RDF4PMC • the transformation into RDF from the original PMC files • the annotation of the RDF • an API which makes that data available. 2/14/2014 • We provide • Publishers may decide what to expose via RDF and what content to make available • Our approach is also applicable for PDF-only environments 31

The MSRC consortium Greg Riccardi, FSU Oscar Corcho, UPM Olga Giraldo, UPM Bob Morris, Harvard University Michel Dumontier, Carleton University Dietrich Rebholz-Schuhmann, University of Zurich Diane Leiva, FSU US DoD Grant MOMRP Grant w81xwh-10-2-0181 All of those who gave us feedback about the RDFization and the quality of our RDF datasets Biotea, RDF4PMC • • • • • • • • • • 2/14/2014 Acknowledgments 32

Contacts • Alexander García: agarciac@gmail.com • L. Jael García Castro: leylajael@gmail.com Biotea, RDF4PMC 2/14/2014 Thanks for you attention 33

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