1. Bieber, Catanio & Zhang, NJIT ©2003 1 Ubiquitous Metainformation and the W Y W W Y W I Principle Michael Bieber*, Joe Catanio*, Li Zhang** *Information Systems Department **Computer Science Department College of Computing Sciences New Jersey Institute of Technology http://web.njit.edu/~bieber November 2003 This talk ties together much of our current research.. It also gives a vision of where the WWW is heading.

2. Bieber, Catanio & Zhang, NJIT ©2003 2 Thinking Exercise Close your eyes. Think about your favorite Web site, or one that you rely on for information... Focus on an element you’re interested in –a text string, icon, element within a table or an animation...

3. Bieber, Catanio & Zhang, NJIT ©2003 3 The W Y W W Y W I Principle What you want, when you want it Wanting to point to something and say: –Tell me more about this! –What is this? –How can I use this? What do I need to know to use it? –Can I modify this? –How does this differ from similar ones? –What is the next step? This is all metainformation & people should get it!

4. Bieber, Catanio & Zhang, NJIT ©2003 4 Ubiquitous Metainformation Goal: Metainformation widespread in everyday systems How: provide tools for developers Relationship Analysis –systematically determining metainformation Metainformation Engine –automatically generating metainformation WYWWYWI –widespread accepted design philosophy

5. Bieber, Catanio & Zhang, NJIT ©2003 5 Outline Examples Metainformation (what to provide) Relationship Analysis (how to find metainformation) Metainformation Engine (how to automate it) Virtual Documents (many real world documents) Related Work WYWWYWI (what it will take)

6. Bieber, Catanio & Zhang, NJIT ©2003 6 Two Examples Purchasing System Digital Library screen shot of our prototype later...

7. Bieber, Catanio & Zhang, NJIT ©2003 7 Sample Screen from Purchasing System: All text with no links...

8. Bieber, Catanio & Zhang, NJIT ©2003 8 But we could want metainformation about almost any element...

9. Bieber, Catanio & Zhang, NJIT ©2003 9 V0000304390 {vendor} Vendor Details {Vendor IS} Vendor Reliability {Vendor IS} Vendor Agreements {Vendor IS} Other Possible Vendors {Purchasing Data Warehouse} Your Purchasing History {Purchasing IS} All Screens with this Vendor {CASE Workbench}

10. Bieber, Catanio & Zhang, NJIT ©2003 10 Author and Document Owner {Metadata Repository} Define this concept {Agricultural Thesaurus}

11. Bieber, Catanio & Zhang, NJIT ©2003 11 Metainformation The full context about and around an element Provides a fuller understanding metadata element relationships

12. Bieber, Catanio & Zhang, NJIT ©2003 12 Metainformation metadata (about selected element) content relationships (based on display content) structural relationships (based on element type or “class”) annotation relationships (user-declared, knowledge-sharing) metainformation-based navigation (user-directed) Roberto Galnares’ dissertation

13. Bieber, Catanio & Zhang, NJIT ©2003 13 Author and Document Owner {Metadata Repository} Define this concept {Agricultural Thesaurus}

14. Bieber, Catanio & Zhang, NJIT ©2003 14 Author and Document Owner {Metadata Repository} metadata content relationship annotation structural relationships Define this concept {Agricultural Thesaurus} content relationship

15. Bieber, Catanio & Zhang, NJIT ©2003 15 V0000304390 {vendor} Vendor Details {Vendor IS} Vendor Reliability {Vendor IS} Vendor Agreements {Vendor IS} Other Possible Vendors {Purchasing Data Warehouse} Your Purchasing History {Purchasing IS} All Screens with this Vendor {CASE Workbench} all are structural relationships

16. Bieber, Catanio & Zhang, NJIT ©2003 16 Outline Examples Metainformation (what to provide) Relationship Analysis (how to find metainformation) Metainformation Engine (how to automate it) Virtual Documents (many real world documents) Related Work WYWWYWI (what it will take)

17. Bieber, Catanio & Zhang, NJIT ©2003 17 Relationship Analysis (RA) What metainformation could we provide? RA: a systematic methodology to determine relationships (& metadata and new destination elements) –New systems analysis technique –Fills a major hole in software engineering –Analysts gain deeper understanding of a system –Yields richer analyses and designs –Relationships become links Joe Catanio’s dissertation

18. Bieber, Catanio & Zhang, NJIT ©2003 18 Relationship Analysis (RA), cont. approach: brainstorming with domain experts for existing systems: –pick elements from screen shots for new systems: –pick entities from use cases Ask questions from RA taxonomy

19. Bieber, Catanio & Zhang, NJIT ©2003 19 RA Taxonomy based on Guilford’s Structure of Intellect theory [1950] –describing intellect and creativity refined by Rao & Turoff’s Hypertext Morphology [1991] – for systems analysis

20. Bieber, Catanio & Zhang, NJIT ©2003 20 RA Taxonomy

21. Bieber, Catanio & Zhang, NJIT ©2003 21 RA Taxonomy

22. Bieber, Catanio & Zhang, NJIT ©2003 22 RA: Brainstorming Questions RA Template

23. Bieber, Catanio & Zhang, NJIT ©2003 23 Outline Examples Metainformation (what to provide) Relationship Analysis (how to find metainformation) Metainformation Engine (how to automate it) Virtual Documents (many real world documents) Related Work WYWWYWI (what it will take)

24. Bieber, Catanio & Zhang, NJIT ©2003 24 Metainformation Engine “Just in time” metainformation –required for virtual documents (e.g., query results) Automatically: –generates link anchors –generates links to services providing metainformation: metadata, content, structural, annotation relationships –incorporates metainformation-based navigation Provides lightweight systems integration through linking to everyday systems Roberto Galnares’ dissertation

25. Bieber, Catanio & Zhang, NJIT ©2003 25 V0000304390 {vendor} Vendor Details {Vendor IS} Vendor Reliability {Vendor IS} Vendor Agreements {Vendor IS} Other Possible Vendors {Purchasing Data Warehouse} Your Purchasing History {Purchasing IS} All Screens with this Vendor {CASE Workbench}

26. Bieber, Catanio & Zhang, NJIT ©2003 26 To Integrate: (1) wrapper: parses screens to identify elements (2) provide metadata/structural rel’ship rules (3) identify glossaries for content relationships User’s Web Browser Vendor IS Wrapper Purchasing D.W. Wrapper Purchasing IS Wrapper CASE Workbench Wrapper Service Wrapper (i) Vendor Information System Purchasing Data Warehouse Purchasing Information System CASE Workbench Service (i) ME Relationship Engine ME Broker ME Desktop Metainformation Engine ME Lexical Analysis existing system or Web service uses Java, XML, Xpath, etc.

27. Bieber, Catanio & Zhang, NJIT ©2003 27 User’s Web Browser Vendor IS Wrapper Purchasing D.W. Wrapper Purchasing IS Wrapper CASE Workbench Wrapper Service Wrapper (i) Vendor Information System Purchasing Data Warehouse Purchasing Information System CASE Workbench Service (i) ME Relationship Engine ME Broker ME Desktop Metainformation Engine ME Lexical Analysis To Integrate: (1) wrapper: parses screens to identify elements (2) provide metadata/structural rel’ship rules (3) identify glossaries for content relationships existing system or Web service uses Java, XML, Xpath, etc.

28. Bieber, Catanio & Zhang, NJIT ©2003 28 V0000304390 {vendor} Vendor Details {Vendor IS} Vendor Reliability {Vendor IS} Vendor Agreements {Vendor IS} Other Possible Vendors {Purchasing Data Warehouse} Your Purchasing History {Purchasing IS} All Screens with this Vendor {CASE Workbench} Relationship Rules element type (“vendor”) link display label (“Vendor Details”) relationship metadata for filtering links –semantic relationship type (“elaboration”) –relationship keywords destination system (“Vendor Info System”) exact command(s) for destination system (“retrieve_full(ID, details)”) conditions –user types and tasks, expertise required, access restrictions

29. Bieber, Catanio & Zhang, NJIT ©2003 29 Relationship Rules Mechanism for implementing access to: –Metadata –Structural relationships –Content relationships –Annotation relationships –Metainformation navigation

30. Bieber, Catanio & Zhang, NJIT ©2003 30 Metadatum Rule element type ( “vendor”) metadatum link display label (“Vendor Name”) metadatum’s metadata for filtering links –semantic relationship type (“name”) –metadatum keywords destination system (“Vendor Info System”) exact command(s) for destination system (“ select(vendor_table, vendor_ID, vendor_name) ”) conditions –user types and tasks, expertise required, access restrictions

31. Bieber, Catanio & Zhang, NJIT ©2003 31 Annotation Rule (display comments) element type ( “generic_element”) link display label (“ view comments on this”, element_type) ”) relationship metadata for filtering links –semantic relationship type (“annotation”) destination system (“Annotation System”) exact command(s) for destination system (“display_annotations(element_ID)”) conditions check_condition(“Core Annotation Service”, existence_check(“annotations”, element_ID)) = true)

32. Bieber, Catanio & Zhang, NJIT ©2003 32 Prototype: Digital Library Integration

33. Bieber, Catanio & Zhang, NJIT ©2003 33 Interesting Issues Information overload! –Must filter and rank order list of links –Too many anchors –Requires good user interface design Semantics –Systems/services should use same element types Unique persistent identifiers –For every screen, document, element of interest

34. Bieber, Catanio & Zhang, NJIT ©2003 34 Outline Examples Metainformation (what to provide) Relationship Analysis (how to find metainformation) Metainformation Engine (how to automate it) Virtual Documents (many real world documents) Related Work WYWWYWI (what it will take)

35. Bieber, Catanio & Zhang, NJIT ©2003 35 Virtual Documents from user interaction, queries, customizations Metainformation must be added “just in time” Example –do a decision support analysis (“# vehicles needed”) –add comments to calculation results –bookmark screen (“make it a favorite”) –close screen –follow bookmark later (“system regenerates screen”) –system must re-locate comment anchors “just in time”

36. Bieber, Catanio & Zhang, NJIT ©2003 36 Virtual Documents Re-generate virtual documents –without re-entering parameters –then wrapper parses to add metainfo anchors Re-identify elements –Location can shift –content can change (e.g., stock price) Re-locate anchors Li Zhang’s dissertation

37. Bieber, Catanio & Zhang, NJIT ©2003 37 Outline Examples Metainformation (what to provide) Relationship Analysis (how to find metainformation) Metainformation Engine (how to automate it) Virtual Documents (many real world documents) Related Work WYWWYWI (what it will take)

38. Bieber, Catanio & Zhang, NJIT ©2003 38 Related Work Web Services Semantic Web Microsoft SmartTags/NBC-Interactive’s QuickClick, etc. Link Services and Hypermedia Engines

39. Bieber, Catanio & Zhang, NJIT ©2003 39 Web Services The Metainformation Engine (ME) is a kind of Web service –a metainformation/linking service ME can integrate with existing Web services –include Web services in set of links –supplement Web services with links

40. Bieber, Catanio & Zhang, NJIT ©2003 40 Semantic Web Advocates the use of ontologies (groups of related terms) to define concepts and their relationships Goal: machine-readable semantic description / processing Recognizes the need to accommodate diverse knowledge representations and conflicting definitions. The ME could use ontologies to: –standardize element types –Find related elements and provide links to their metainformation

41. Bieber, Catanio & Zhang, NJIT ©2003 41 Microsoft SmartTags / NBC-Interactive’s QuickClick, etc. Set of links generated automatically –Based on known keywords –Can add additional links manually No structural linking

42. Bieber, Catanio & Zhang, NJIT ©2003 42 Microsoft Smart Tag critiques Users find too many links annoying Content providers do not want their documents altered Manipulation: Companies can pay to have competitors name recognized and linked to their sites Provides content based links (word recognition) not structural linkages (element recognition)

43. Bieber, Catanio & Zhang, NJIT ©2003 43 Link Services and Hypermedia Engines SFX (links to referenced articles) Link Services –Chimera, Microcosm Distributed Link Service, DHM: manual linking or automated through keyword search requiring modifications for integration Hypermedia Engines with minimal modifications –Microcosm Universal Viewer, Freckles: manual linking –OO-Navigator: SmallTalk only Web Database Applications, e.g., e-shopping –database queries only, normally single links

44. Bieber, Catanio & Zhang, NJIT ©2003 44 Outline Examples Metainformation (what to provide) Relationship Analysis (how to find metainformation) Metainformation Engine (how to automate it) Virtual Documents (many real world documents) Related Work WYWWYWI (what it will take)

45. Bieber, Catanio & Zhang, NJIT ©2003 45 What you want, when you want it What will it take? WYWWYWI mindset for developers & public –Allow metainformation (user-directed) navigation –a design philosophy for developers –demanded by the general public –this requires exposure! Developer Tools Ubiquitous Access

46. Bieber, Catanio & Zhang, NJIT ©2003 46 What you want, when you want it What will it take? WYWWYWI mindset for developers & public Developer Tools –Relationship Analysis –Metainformation Engine –Wrappers for everyday systems –Annotation/knowledge-sharing services (linking, comments, guided tours, etc.) Ubiquitous Access

47. Bieber, Catanio & Zhang, NJIT ©2003 47 What you want, when you want it: What will it take? WYWWYWI mindset for developers & public Developer Tools Ubiquitous Access –Repositories of relationship rules –Thesauri and glossaries

48. Bieber, Catanio & Zhang, NJIT ©2003 48 Interesting Issues Access privileges to others’ metainformation Right to third party authoring/linking Quality of metainformation –Rating metainformation –Bogus metainformation (such as advertisements)

49. Bieber, Catanio & Zhang, NJIT ©2003 49 Metainformation –broader conceptualization Relationship Analysis (how to find metainformation) Metainformation Engine (how to automate it) –Lightweight systems integration through linking Virtual Documents –Re-generation, re-identification, re-location WYWWYWI: a design philosophy –What you want, when you want it Research Contributions Thank you! Questions, please?