Weber 2010 brn


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Weber 2010 brn

  1. 1. Weber, Eilbracht, Kesberg @ TMRA 2010 1 Sixth International Conference on Topic Maps Research and Applications – TMRA 2010 Leipzig, 29 September – 1 October 2010 Gerhard E. Weber, Ralf Eilbracht, Stefan Kesberg Nexxor GmbH, Stuttgart, Germany, Topic Maps for subject-centric publishing from document-centric content management systems – a case study on a website of a regional cluster of companies
  2. 2. Weber, Eilbracht, Kesberg @ TMRA 2010 Unternehmen 2Problem statement document-centric CMS high costs of linking documents editors need to know which documents to link Unternehmen many pages information relevant for a particular subject in many pages few links related subjects in different documents as isolated texts user has to read many pages to connect the dots = restricted usability of content +
  3. 3. Weber, Eilbracht, Kesberg @ TMRA 2010 Unternehmen 3Suggested solution subject centrism offer subjects networked by knowledge models instead of isolated text fragments in documents Unternehmen many perspectives render views of subjects not just of documents include relational views automatically generated from underlying graph many access paths offer many access paths to users‘ target views rather than a few hierarchical navigation structures Topic Maps-driven as access layers „on top“ of document-centric CMS frontends increased usability + + + =
  4. 4. Weber, Eilbracht, Kesberg @ TMRA 2010 4Anwendungsbeispiel What is it? website of a cluster of some 250 biotech and medtech companies in metropolitan area of Stuttgart, and to its south cluster management company funded by regional administrative unitsWho creates it? URL cluster members, cluster managers, other interested parties looking for customers, partners, experts Who uses it? company profiles, project participations, news, eventsContent Website of regional cluster of biotech companies
  5. 5. Weber, Eilbracht, Kesberg @ TMRA 2010 5AnwendungsbeispielThe old document-centric web app… navigation company infos menu bar search fulltext overview one alphanumerically sorted table with company names and focus descriptions alphabetical paging each company one page with data on focus, profile, address, management, contact, year founded, etc. without links to related information
  6. 6. Weber, Eilbracht, Kesberg @ TMRA 2010 6Anwendungsbeispiel Companies located in a particular city, county, or higher administrative unit? Members in Stuttgart, county Zollernalbkreis, district Tübingen? Cities or other administrative units represented in the cluster, and by what companies? Companies related to particular field of activity in a particular administrative unit? Diagnostics in county Zollernalbkreis? Focus on a particular company: other companies headquartered in the same county? other companies with the same fields of activity? other participants of the same projects? … did not enable users to see the connections
  7. 7. Weber, Eilbracht, Kesberg @ TMRA 2010 7Topic Map creation Anwendungsbeispiel Data source XML dump provided by webservice from CMS spreadsheet file describing fields of activities Ontology creation minimal ontology designed with 18, 8, 17, and 14 types for topics, assocs, roles, occurrences, respectively Knowledge models geographic containments of administrative units Data preprocessing address fields preprocessed for entity recognition of locations XML/spreadsheet data transformed to Topic Maps with mapping framework all maps merged Transformation monthlyUpdates
  8. 8. Weber, Eilbracht, Kesberg @ TMRA 2010 8Anwendungsbeispiel Topic Maps package topicWorks with Topic Maps engine, configurable frontend, template system URL individuals by default rendered in „topic view“ topic view collocates names, associations, and occurrences types by default rendered in „table view“ table view lists instances and statements about them customization for topics of particular interest (templates, tolog) Visualization patterns Company info of biotech cluster as Topic Maps based web app
  9. 9. Weber, Eilbracht, Kesberg @ TMRA 2010 9Subject-centric information on cluster members Markt topic: company topic: year 1999 topic: Stuttgart topic: diagnostics relational view automatically rendered from underlying topic maps collocates all instances of type „company“ – and its subtypes – and all statements about these instances What is known about BioTeSys?
  10. 10. Weber, Eilbracht, Kesberg @ TMRA 2010 10Markt precious information on the company – lots of reading, though View of a particular cluster member – 1
  11. 11. Weber, Eilbracht, Kesberg @ TMRA 2010 11MarktView of a particular cluster member – 2 associations anchor the company in time, space, and fields of activity of the biotech cluster topic: BioProfile what is known about this subject ?
  12. 12. Weber, Eilbracht, Kesberg @ TMRA 2010 12Markt there are 15 participating cluster members What is known about BioProfile? which members are – like BioTeSys – active in diagnostics? it is an R&D funding program
  13. 13. Weber, Eilbracht, Kesberg @ TMRA 2010 13MarktOverview on a particular field of activity What member info is available?
  14. 14. Weber, Eilbracht, Kesberg @ TMRA 2010 14MarktOverview on a particular city hierarchy browser 9 cluster members headquartered in Esslingen
  15. 15. Weber, Eilbracht, Kesberg @ TMRA 2010 15MarktGeographic knowledge model – drill up drill-up to county level
  16. 16. Weber, Eilbracht, Kesberg @ TMRA 2010 16MarktOverview of a particular county What are the cluster members‘ fields of activity?
  17. 17. Weber, Eilbracht, Kesberg @ TMRA 2010 mildew susceptibility 17MarktOverview of the fields of activity in the cluster relational view rendered automatically
  18. 18. Weber, Eilbracht, Kesberg @ TMRA 2010 18Markt text filter reduces to fields of activity of a particular company, and identifies other relevant members Overview of the fields of activity in the cluster + text filter
  19. 19. Weber, Eilbracht, Kesberg @ TMRA 2010 19Markt search for a particular county Semantic search – displaying typed results, using inference 43 relevant topics found, and grouped by type search evaluates inference rule on geographic containment for retrieving all relevant topics
  20. 20. Weber, Eilbracht, Kesberg @ TMRA 2010 20MarktSemantic search – reducing results to type of interest reduce results to the type of interest, here: medtech companies 10 medtech cluster members located in the sought-after county
  21. 21. Weber, Eilbracht, Kesberg @ TMRA 2010 CMS TM app number of pages 240 500 internal links 240 6000 overviews 1 230 21 documents in CMS topic map companies in medical technology? medtech companies in Reutlingen? biotech companies in Landkreis Tübingen active in diagnostics? retrieval efforts for finding answers manually browsing over 200 web pages 1 click 1 click + 1 filter 1 search + 1 click 21Anwendungsbeispiel geographic knowledge models, multiple fields of activity in spreadsheet Document-centered CMS versus Topic Maps-based web app
  22. 22. Weber, Eilbracht, Kesberg @ TMRA 2010 Topic Maps-based web app* on top of a document-centric CMS with member information of a biotech cluster. 22ZusammenfassungSummary and conclusion Use case Conclusion Topic Maps-based web frontends on top of document-centric CMS improve content usability by subject-centric information delivery. *