MIT CSAIL IAP ELS 2012 01-28 v1
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MIT CSAIL IAP ELS 2012 01-28 v1

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A brief presentation on linked data at Elsevier, presented to the MIT CSAIL Industry Affiliates on 2012-01-28.

A brief presentation on linked data at Elsevier, presented to the MIT CSAIL Industry Affiliates on 2012-01-28.

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MIT CSAIL IAP ELS 2012 01-28 v1 MIT CSAIL IAP ELS 2012 01-28 v1 Presentation Transcript

  • MIT COMPUTER SCIENCE AND ARTIFICIAL INTELLIGENCE LABORATORY 1/16/2012
  • Who We Are Global Global Global community audience market 7,000 editors 15 million doctors, = 70,000 editorial board members 200,000 referees + nurses and health professionals 10 million+ + North America researchers in 500,000+ authors 4,500 institutes Europe Asia- 5 million students Pacific Science & Technology Health Sciences Science Journals (online and print) Global Medical Research Databases Global Clinical Reference Books (online and print) Clinical Decision Support Nursing & Health Professions U.S. Pharma EMEA & Latin America APACMIT COMPUTER SCIENCE AND ARTIFICIAL INTELLIGENCE LABORATORY 1/16/2012
  • Linked Data in Scientific Publishing Linked data from partners and the Web Better discovery through semantic search & navigation Text Entities, Better understanding through analysis and Scholarly concepts and visualization content relationships Tables Images New knowledge through aggregation and synthesis Scholarly knowledge organization systemsMIT COMPUTER SCIENCE AND ARTIFICIAL INTELLIGENCE LABORATORY 1/16/2012
  • From Research Publications to Research Linked Data Provenance Entity record metadata Relational Metadata Document Asset metadata Relational Relational Metadata metadata Media object Asset Asset metadata MetadataMIT COMPUTER SCIENCE AND ARTIFICIAL INTELLIGENCE LABORATORY 1/16/2012
  • Adopting Linked Data at Elsevier • Embrace linked data principles while leveraging our existing content production workflow and infrastructure – Find the right balance between production/QA and online delivery • Leverage partners for content enhancement and knowledge organization – Reuse Web-standard vocabularies, taxonomies, ontologies and entity resources where possible • Build out linked data design patterns for application development • Deliver benefits across the complementary use cases of researcher and practitionerMIT COMPUTER SCIENCE AND ARTIFICIAL INTELLIGENCE LABORATORY 1/16/2012
  • Work to Date • Standards – RDF/XML for production/QA • Infrastructure – Linked Data Repository for online delivery services • Applications – Clinical Key (in beta) – EMMeT medical taxonomy – Lancet, SciVerse linked data mashupsMIT COMPUTER SCIENCE AND ARTIFICIAL INTELLIGENCE LABORATORY 1/16/2012
  • Long Range Objectives • Build out linked data services for smart content – Expose linked data for our primary and secondary content – Link out to emerging, authoritative ontologies and repositories – Generate linked data for partners’ content • Deliver linked data to support user-driven innovation – Foster a developer ecosystem using our services as a platform – Collaborate in building needed authoritative resources (e.g. ORCID) • Establish linked data business models – The Four Principles make what works for the Web of Content work for the Web of Data without modificationMIT COMPUTER SCIENCE AND ARTIFICIAL INTELLIGENCE LABORATORY 1/16/2012