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Perspectives and Priorities for Digital Libraries Research

Perspectives and Priorities for Digital Libraries Research. Erich J. Neuhold GMD-IPSI - Integrated Publication and Information Systems Institute Darmstadt University of Technology. Digital Libraries. All kinds of data stores that handle multimedia information (content)

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Perspectives and Priorities for Digital Libraries Research

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  1. Perspectives and Priorities for Digital Libraries Research Erich J. NeuholdGMD-IPSI - Integrated Publication and Information Systems Institute Darmstadt University of Technology

  2. Digital Libraries All kinds of data stores that • handle multimedia information (content) • describe the information (metadata) • place the human in the center • know and support the human player • are available at any time and at any place • are connectable to other user centered applications

  3. Digital Libraries This leads to a combination of • Libraries • Museums • Archives • Corporate and private Information Stores that are actively supported by

  4. Informing Organisms supporting culturalheritage • technology components • information based • simple and complex • growing in functionality • interoperating • mobile • intelligent

  5. The Issues: A lot exists and goes on in • research (components) • advanced demonstrators (just working) • advanced prototypes/pre-products (non scaling) • products but more of it is needed in the Internet domain (i.e. global village). We have • isolated solutions • simple solutions • technology driven solutions

  6. Information and Knowledge Databases(object relational, objects oriented, document oriented, multimedia, active, real-time) InformationRepresentation and Description Schemes (structured, semi-structured, unstructured, Meta-Data, QoS parameters) Information Content Analysis(text (linguistics), voice (speech), sound, image, video, sensor data, sequenced data) Information Retrieval, Filtering, Enrichmentuser driven, supporting team- and groupwork, integrative, intelligent, imperative, and declarative

  7. Roles to Support (I) User supporting issues: author, theme, content, presentation, reader / usage Authoring Tools • multimedia, activity-oriented, supporting group- and teamwork • acquisition / authoring new and legacy material Information and Knowledge Handling Tools • indexing, extraction, structuring • classification, abstraction • separation / integration • distributing, storing

  8. Roles to Support (II) Filtering & IR Tools • searching, exploration • navigation, inspection • evaluation Enrichment & Adaptation Tools • user oriented • usage oriented • situation oriented • device oriented

  9. Roles to Support (III) Presentation Tools • at different granularity levels • documents, pages, modules • content and meta data semantics • manipulation and navigation • for different application contexts(travel, settlement) • for different activities, tasks, and workflows (creating, filtering, using, learning)

  10. Roles to Support (IV) Usage Tools • documents and document manipulation • guidance to the answer • evaluation of solution • personalized memory • personalized information pipelining • communication, distribution, and mobility

  11. Clearly Multidisciplinary • Computer Science • Embedded Systems Engineering • Linguistics (multi-language, analysis-generation) • Communication Science • Library / Museum / Archive sciences • Information Science • Psychology (cognitive, social)

  12. Needed for DL (I) Basic research is needed (PITAC report) • separate topics (focused projects) • integrated topics (large projects) Demonstrators / pilots are needed • integrated but focused (what will be shown!) • proof of concept

  13. Needs for DL (II) Sustainable proto-products are needed • open system approach, but still focused • have to scale somewhat Products are needed • integrated but application driven / exploitable • have to scale • have to be robust /reliable / serviceable etc. • ready for start-up financing

  14. Example: TREVI Personalized • information filtering • linking • delivery for the News Domain

  15. Example: TREVI

  16. Example: TV-ONLINE • personalized profiles • personalized rankings • collaborative filtering • recommendations • automatic generation of individual schedules.

  17. Example: TV-ONLINE

  18. Example: cyber:gallery • exhibiting and selling art on the Internet • applying virtual reality paradigms • supporting searching and navigation • supporting personalized galleries/museums and guided tours

  19. Example: cyber:gallery

  20. Example: Videocube • visualization of scenes and camera movement in videostreams • access to structure and content • direct manipulation of meta data and data (technical and semantic levels)

  21. Example: Videocube

  22. Example: Lyberworld • information visualization at the user interface • supporting analysis clustering, partitioning • supportinguser information profiles

  23. Example: Lyberworld

  24. Conclusion • come up with focused but integrated solutions • advanced research and development of technologies using informing organisms • pre-products and products will naturally follow those results

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