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Extrapolating Trends for Information Technology

Extrapolating Trends for Information Technology. Gio Wiederhold Stanford University September 1999 Based on “ Trends for Information Technology ” 1999 www-db.stanford.edu/pub/gio/1999/miti.htm. 90 80 70 60 50 40 30 20 10 0. Centroid, in 1999 ~1% of total market.

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Extrapolating Trends for Information Technology

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  1. Extrapolating Trends for Information Technology Gio Wiederhold Stanford University September 1999 Based on “Trends for Information Technology” 1999 www-db.stanford.edu/pub/gio/1999/miti.htm

  2. 90 80 70 60 50 40 30 20 10 0 Centroid, in 1999 ~1% of total market % Ü 98 99 00 01 02 03 04 0.3 1 3 9 27 81 ** Year / % Ü T r e n d s 1998 : 1999 • Users of the Internet 40% Ü 52% of U.S. population • Growth of Net Sites (now 2.2M public sites with 288M pages) • Expected growth in E-commerce by Internet users[BW, 6 Sep.1999] segment 1998 1999 • books 7.2% Ü 16.0% • music & video 6.3% Ü 16.4% • toys 3.1% Ü 10.3% • travel 2.6% Ü 4.0% • tickets 1.4% Ü 4.2% • Overall 8.0% Ü 33.0% = $9.5Billion An unstainable trend cannot be sustained [Herbert Stein] Ü new services E-penetration Toys

  3. Interactions Research & Tool Inno - building Consumer vation Product Pull building & General marketing Technology Push Information Business Technology needs Government responsibilities

  4. Assumptions • Hardware technology will continue to lead and encourage broader usage • Communication technology will continue to lead and become more economical • User interfaces will improve and not be a barrier to the acceptance of technology • Government policies will not hinder open interaction - or not be able to

  5. The Problem of Information Growth: "We are drowning in information but starved for knowledge. This level of information is clearly impossible to be handled by present means. Uncontrolled and unorganized information is no longer a resource in an information society, instead it becomes the enemy." -- John Naisbitt, author of 1982 bestseller Megatrends . . . and it’s not getting better Dealing with this issue requires Precision: • Helpful for casual users • Essential for business

  6. Precision in: • Search for Information • recall versus precision • Relevance of Information for the Customer • modeling the customer • Meaning of the Information • resolving semantic mismatch • Timeliness of Information • resolving temporal mismatch Service model to achieve these objectives services add value by increasing precision

  7. Search techniques to add value Yahoo catalogues and organizes useful web sites. Junglee integrates diverse sources. AltaVista automatically surfs and indexes the web. Excite also tracks queries and classifies customers. Fireflyprovides customer control over their profiles. Cookies track users’ activities between sessions. Alexacollects webpages and their usage. Googleranks the reference importance of web pages. . . .

  8. Problems for search engines and progress • Unsuitable source representations • part classification: HTML --- XML • print formats: postscript, adobe PDF • non-text: images, sound, video • hidden in databases behind CGI scripts • Inconsistent semantics • context distinct / scope / view • Naïve modeling of customers • roles & growth • Search engines cannot solve all problems Being improved. Rate?

  9. _ _ …. …. _ _ …. …. _ _ …. _ …. …. _ _ _ _ …. …. …. …. _ _ …. _ _ …. …. _ _ _ …. _ data, meta-data, knowledge _ …. …. …. …. …. _ _ _ _ …. …. …. …. The world wide information network and its participants External: sources and / or sinks Internal: transformers and memory.

  10. Understand the Architecture forInformation Technology: Customers Component Classification Customers Customers Customers Customers Services Services Services Sources Sources Sources

  11. Catalogs Content & Methods Specifications for the components Customers Customer models Customers Customers Customers Customers Progress Services Services Services Sources Sources Sources Metadata

  12. Human-computer Interaction User interface Application- specific code Service interface Domain- specific code MEDIATION Services Resource access interface Source- specific code Real-world interface Functional Service Layers Client Available Sources

  13. Modeling: sources • Models provide abstractions • abstractions represent a point of view • Models of databases are schemas and E-R models • well established • constraints - references, uniqueness • scopes remain implicit • Information systems have meta-data • XML has DTD’s • under discussion, still limited • Focus on resources Meta data

  14. Customer models • Customer is a person 6 one specific task • arranging a vacation trip • activity ˆ location town ˆ hotel by grade ˆ • flight ˆ public transport ˆ rented car • arranging a business trip • location ˆ hotel by plan ˆ flight ˆ • taxi or rented car • getting a computer for Joe Cheap • search CPU by price ˆ modem ˆ display • getting a computer for Peter Fast • search CPU by speed ˆstorage ˆ display ˆ network • Hierarchical • alternatives at each level ( evaluate, commit, rollback )

  15. Personal vs. Customer Model Actual Person has multiple roles • how to switch • explicitly • implicitly • keep past contexts • Switching rate will differ • work versus fun • adequacy of models

  16. Service layer Multiple domains ! Customer Service MEDIATION Shared software, standards ? Resource access

  17. Value-added intermediate services 1 Needs Technologies extant and new Describe customer model Discover new resources Select relevant resources Easy access to resources Filter out excessive data Build interpretable workflow model with meta-specifications for selection Monitor and index public metadata, describe resource capabilities, contents & methods Match available metadata and indices of resource contents to leaf nodes in the customer model Wrap resources to make them compatible, exploit wrapper templates, skip unavailable sources Filters attached to the customer model; balance relevant volume and precision

  18. Automatic abstraction to match sources at articulation points within the customer model Attach data instances to articulation points, combine elements , link to customer model Match data for content, omit overlap, report inconsistencies in overlapping sources Summarize according to customer model, rank information at each level Present information according to model hierarchy, consider bandwidth Value-added intermediate services 2 Needs Technologies, extant and new Identify articulations * Match level of detail * Integrate information Omit redundant data, documents Reduce customer overload Inform customer Matching of related concepts, use articulation rules to match nodes

  19. Abstraction layers differ: Example in medical research • Individual patient records • Family based genetic traces • Disease-based summaries • Genetically-linked disease data • Ligand-based genomic segments • Aggregated gene sequences • 3-D configurations of segments • Drug-gene interactions All have their own hierarchies, roots

  20. Combining the models * • Identify articulations • Match customer and resource terms • semantic mismatches • thesauri, matching rules • Match level of detail • Match customer and resource values, summarize numbers, result ranks • completeness, unit mismatches, text • indicate constraints in models • textual abstraction • input for visualization

  21. Mediator Service Design Principle Transform Data into Information Match User Model Hierarchical to Resource Model General network (and maintain models)

  22. Customer: • wants choices • explanation • background Result modes for ranking Databases: • Completeness • All the answers Prolog • Correctness • The first answer Optimization • The best one • Assumes all factors are known, no human decision

  23. Ranking Qualitative Significant Differences: in terms of the customer model Plan 1. UA59 dep.Wash.Dulles 17:10, arr. LAX 19:49 Plan 2. AA75 dep.Wash.Dulles 18:00, arr. LAX 20:10 Plan 3. UA119 dep.Wash.Dulles 9:25, arr. LAX 12:00 Busy Joe: P1= P2, P3 Speedy Mike: P2, P1=P3 Greedy Pete: P1=P3, P2

  24. Estimates: C1= 5+_1 T1=100+_160 C3= 10+_1 T3=50+_80 C2= 8+_1 T2=70+_30 S1 S2 S3 Mediation for Quality • User Model • f(S,C,T) • Assessments: • S1=.8 S2=.9 S3=8 • BEST= • low cost • rapid response • reliable delivery • trustworthiness S= source reliability C= confidence T=

  25. Computing Projections For decision-making: not just past data Next period alternatives and subsequent periods 0.25 0.25 0.5 0.5 0.6 0.6 0.3 0.3 0.05 0.05 0.3 0.3 0.3 0.3 0.07 0.07 0.1 0.1 0.4 0.4 time 0.2 0.2 01.3 past now future Integrate simulation results into information systems: SQL SimQL

  26. Extending the support into the future Must manage multiple projected futures --- Novel tools needed to help the decision maker: • 1. Assess the likelihood of a branch being taken (if not controlable) • 2. Compute probabilities into the future, up to desired/final endpoints • 3. Compute results at each node, by backtracking from the endpoints • and considering the probabilities • 4. Compare the associated costs and benefits for the alternatives • at any future time • 5. Recalculate to get new, better values, less uncertainty • Trim or summarize unlikely branches to reduce the complexity • Prune to the current state and delete all but one actual path

  27. _ _ _ …. …. …. …. . …. . …. . Architecture instances Applications . . . . Mediators . . . . . . Resources . . . include computational resources

  28. Assigning maintenance responsibility a. Source data quality – supplier database, files, or web pages b. Interface to the source – wrapper, supplier or vendor for supplier c. Source selection – expert specialist in mediator d. Source quality assessment – customer input to mediator e. Semantic interoperation – specialist group providing input to the mediator f. Consistency and metadata information – mediator service operation or warehouse g. Informal, pragmatic integration – client services with customer input h. User presentation formats – client services with customer input Sources Services Customers

  29. Summary To sustain the trend 1. The value of the results has to keep increasing precision, relevance not volume 2. Value is provided by experts, encoded as models of diverse resources, customers Problems to be addressed mismatches quality temporal extensions maintenance } Clear models

  30. Technology Transition . • Economic drivers have to be considered. • Three party model • Industry: need-based invention • academia: formalization • innovators: new technology • New Service models provide new Opportunities • supply innovative tools to industry • supply specialized information to industry a i I

  31. Understanding the other parties Motivation is profit and loss avoidance of • Industry: investment -- • payoff to stockholders / retain value / stable • Academia: prestige -- (leads to continuing funding) • visibility, not stability or reliability • Innovative businesses: leverage -- not sustainable • low downside cost, high upside risk, • change expected and needed • Government research: • technology dissemination & shelving service ?

  32. Tool suppliers (TS) versus Product suppliers(PS) high volume high-value modest volume Taxes people results Customers Research Government Teaching Research economy transfer paths Products

  33. Operating Systems • Microsoft Windows, personal computer and WS. • proprietary product, no obligations to hardware, • rapidly adapted to new requirements • UNIX, an open systems, consensus and takes time. • SUN servers • LINUX clients and servers, free, low entry cost • …. • Mainframe operating systems, little growth expected • VMS (COMPAQ) reliable 24 hour / 7 day

  34. 1 Pre-competitive development. • 2 Integration and Marketing • 3. Problem: Asynchrony. • 3.1 Industry-driven.research. • 3.2 Curiosity-driven research. • 3.3 Fundamental research • 3.4 Transition windows • 4 Transition agents. • 4.1 Link academic researchers to industry • 4.2 Link academic and industrial research. • 4.3 Startup companies. • 4.4 Incubator services. • 4.5 Research stores. • Commercial Technology Transfer Company. • Governmental Technology Transfer Institute. • Other candidate organization models forresearch stores. • 5 Research Venues and Technology Transfer. • 6 Summary

  35. Alternative solutions • A Super Database • unwieldly • obsolete before it is established • Distributed, free standing databases (today) • awkward for sharing information (much knowledge derives from the intersections) • hyperlinks and shared references allow navigation • Distributed databases with a single standard allowing interoperation • standards follow progress, cannot lead it • Distributed databses with published formats • requires rapid adaptation to keep up with resources (but the number of resources per project will be limited) with mediators to isolate projects from resources

  36. Paying • Free goods (as information), supported by advertisers • The referred service pays for references made • After contact and selection direct by credit card • at some processing overhead and delay • Customer trust for tolerable losses • Audited ba mediator, violators are blacklisted only • Escrow for substantial value: more delay • Very small transactions use wallets • a. Risk is assumed by the vendor: • b. Risk is assumed by the customer: • Subscriptions for long-term interactions

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