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Cesse July 22 2009

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Presentation on social media at the annual meeting of the Council of Engineering & Society Scholarly Executives held July 22, 2009 in Orlando, FL

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Cesse July 22 2009

  1. 1. www.collexis.com Increasing Discoverability: “Case Studies on Publishers Who Drove & Grew Usage“ Darrell W. Gunter EVP / CMO July 22, 2009
  2. 2. The Semantic Web and Its Developments! 10
  3. 3. The Facts 1,2,3 The Author is under great pressure!
  4. 4. New Models / Open Access 4, 5, 6
  5. 5. Grants 7, 8, 9
  6. 6. STM Products and Processes Societies/Publishers
  7. 7. The STM Consumer Producer Author of a book Member of a STM society Author of journal articles Receiving research funding Consumer & reader Peer reviewer Participant & speaker at conferences Taking advantage of continuous education Member of an editorial board
  8. 8. Consumer/ Producer Process Researcher Funding through an STM society Consuming literature and STM products Participation in the publishing process as a peer reviewer Participation in various conferences Presenting results in varoius conferences/ Publishing of proceedings Publication of results in peer reviewed STM journal
  9. 9. <ul><li>New Rules </li></ul><ul><li>require New Tools </li></ul>
  10. 10. Collexis Fingerprint Engine Collexis Technology KnowledgeBase Text Fingerprint
  11. 11. Collexis Knowledge Engine 7.0 Tokenizer Normalizer Abbreviation expansion Dehyphenation Language detection Coordination expansion Part-of-Speech tagging Entity recognition based on regular expressions Noun phrase detection Concept finding Part-of-speech based disambiguation of thesaurus concepts Exclude known idioms Fingerprint aggregation
  12. 12. Collexis Knowledge Engine 7.0 <ul><li>Modular NLP workbench – processing and analyzing of text documents </li></ul><ul><li>Retrieval and aggregation engine – serving the application layer </li></ul>
  13. 13. Collexis – selected references Bundesministerium für Bildung und Forschung Stanford University Asklepios Kliniken Johnson & Johnson Johns Hopkins University University of California, San Franciscio Dana Farber Cancer Institute Harvard University National Institutes of Health Mayo Clinic California Institute for Quantitative Biosciences (QB3), The Wellcome Trust DKFZ
  14. 14. Explore instead of Searching!
  15. 15. Creating expert profiles from documents using semantic technologies <ul><li>Document fingerprints aggregated to expert profiles! </li></ul>
  16. 16. Conceptual Search & Visualization!
  17. 17. Concept & Publications View
  18. 18. Concept & Author View
  19. 19. Emerging Trends by Key Concepts
  20. 20. Potential Co-occurrence of Concepts Hypothesis Generation!
  21. 21. BiomedExperts – more than 180.000 registered users <ul><li>Prepopulated network – based on PubMed </li></ul><ul><li>1.8 million precalculated experts </li></ul><ul><li>More than 20 million relations between them </li></ul><ul><li>Growing each day between 500 and 1000 users </li></ul><ul><li>BME data used in other applications </li></ul>
  22. 23. <ul><li>Co-author based networks </li></ul>
  23. 24. <ul><li>Geographical </li></ul><ul><li>mapping of the </li></ul><ul><li>co-author network </li></ul>
  24. 25. Same data for sub networks
  25. 26. Same data for sub networks
  26. 27. National Research Network
  27. 28. Creating STM sub-networks <ul><li>Having a researcher to join 25 different networks? </li></ul><ul><li>Should the user related information be spread out over 25 different social networks? </li></ul><ul><li>With BiomedExperts an „Umbrella Network“ is available, where complete and disambiguated profiles are maintained – ready to be integrated into customized special interest networks on a topic level, society or publisher level </li></ul><ul><li>One profile, one login, many networks! </li></ul>
  28. 29. STM Sub networks – ready to go today! Sub network for a society Sub network for a journal Reviewer assignment Sub network of all author of one publisher Virtual conferences - network of participants Network of funded researchers
  29. 30. ...or for peer reviewer identification
  30. 31. Reviewer Finder <ul><li>First integration with Aries and Ejournal Press already done </li></ul><ul><li>Fingerprint of manuscript </li></ul><ul><li>Determine the best reviewer </li></ul><ul><li>Free of conflicts </li></ul><ul><li>More efficient and effective process </li></ul><ul><li>Ultimately increases profitability </li></ul>
  31. 32. Asklepios Facts and Figures <ul><li>Asklepios - Europe‘s largest health care provider </li></ul><ul><ul><li>500.000 patients for inpatient care per year, 95 hospitals, 21.000 beds </li></ul></ul><ul><ul><li>34.500 employees </li></ul></ul><ul><ul><li>Asklepios owns medical nursing and allied health schools </li></ul></ul><ul><ul><li>Home care programs and residential care programs </li></ul></ul><ul><li>Asklepios International </li></ul><ul><ul><li>Pacific Health System – California </li></ul></ul><ul><ul><li>Greece, Athens Medical Center </li></ul></ul><ul><ul><li>University hospital in Shanghai: Joint Venture with Siemens and Tongji University </li></ul></ul>
  32. 33. Optimize Workflows (e.g. Avoid interruptions caused by knowledge search, retrieval, and application) Distribute Expert Knowledge (across multiple locations, time zones, medical conditions) Guide Workflows (e.g. Care Plans, Expert-Task Context Allocation) Help Asklepios to know “what Asklepios knows” Stimulate new Knowledge Acquisition Usage Models Why Knowledge Management?
  33. 34. <ul><li>Patient, male, age of 62, needs a knee joint prosthesis due to Rheumatoid Arthritis </li></ul><ul><li>Where is the best place to get it? </li></ul><ul><li>Criteria which will be taken into account: </li></ul><ul><ul><li>Geographical aspects </li></ul></ul><ul><ul><li>Recommendation of his GP </li></ul></ul><ul><ul><li>Publicly available information - mostly via Internet </li></ul></ul><ul><li>Strongest competitors: university hospitals (within the region) </li></ul>Use Case 1 – Expert profiles
  34. 35. Asklepios Research Profiles
  35. 36. Expert Profile of Prof. Grifka
  36. 37. Make Internal Expertise available!
  37. 38. Help Asklepios to know “what Asklepios knows” Virtualize expertise!
  38. 39. Provide a single point of search for all relevant content from publishers! Link internal expertise / experience and external knowledge sources!
  39. 40. <ul><li>Patient with lung cancer and reduced renal function </li></ul><ul><li>Decision in chemotherapeutic drug is pending </li></ul><ul><li>Preferred choice: Cisplatin as chemotherapeutic agent </li></ul><ul><li>Open questions: can Cisplatin be used which has nephrotoxicity as a side effect? </li></ul>Use Case 4 - External Resources and Internal Experience Use Case 4 - External Resources and Internal Experience
  40. 41. Search - Cisplatin shows the relevant publications from Springer, Elsevier, Thieme, OVID and other publishers Asklepios Intelligent Digital Library
  41. 42. <ul><li>Opening an journal article… </li></ul><ul><li>… shows immediately similar publications colleagues </li></ul><ul><ul><ul><ul><li> … and the names and expert profiles </li></ul></ul></ul></ul>Link External Knowledge and Internal Expertise
  42. 43. Key Next Steps <ul><li>Determine best of class </li></ul><ul><li>SWOT Analysis versus the best of class </li></ul><ul><li>Determine key areas to improve </li></ul><ul><li>Survey </li></ul><ul><ul><li>Customers / focus group </li></ul></ul><ul><ul><li>Internal partners / advisory group </li></ul></ul><ul><li>Implementation of new features/ services </li></ul><ul><li>Establish a performance dashboard and measure success </li></ul>
  43. 44. Thank you for your attention! <ul><li>Darrell W. Gunter, EVP / Chief Marketing Officer [email_address] , cell +1-973-454-3475 </li></ul>

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