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
Oct 1999
Gio XIT 1
Trends
1998 : 1999
• Users of the Internet 40%  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]
An unstainable trend cannot be sustained [Herbert Stein]
new services
Oct 1999

1998
1999
7.2%  16.0%
6.3%  16.4% Centroid, in 1999
3.1% 10.3% ~1% of total market
2.6%  4.0%
1.4%  4.2%
8.0%  33.0% = $9.5Billion
%
–
–
–
–
–
–
segment
books
music & video
toys
travel
tickets
Overall
90
80
70
60
50
40
30
20
10
E-penetration
Toys
0
98 99 00 01 02 03 04
0.3 1 3 9 27 81 **
Year / % 
Gio XIT 2
Interactions
Research
&
Inno vation
Tool
building
General
Technology
Push
Information
Technology
Consumer
Product
building &
marketing
Pull
Business
needs
Government
responsibilities
Oct 1999
Gio XIT 3
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
Oct 1999
Gio XIT 4
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
Oct 1999
Gio XIT 5
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
Oct 1999
Gio XIT 6
Search techniques to add value
Yahoo
Junglee
AltaVista
Excite
Firefly
Cookies
Alexa
Google
catalogues and organizes useful web sites.
integrates diverse sources.
automatically surfs and indexes the web.
also tracks queries and classifies customers.
provides customer control over their profiles.
track users’ activities between sessions.
collects webpages and their usage.
ranks the reference importance of web pages.
...
Oct 1999
Gio XIT 7
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
Being
improved.
Rate?
• Inconsistent semantics
• context distinct / scope / view
• Naïve modeling of customers
• roles & growth
Search engines cannot solve all problems
Oct 1999
Gio XIT 8
The world wide information network
and its participants
_
….
_
External:
….
sources
and / or
sinks
_
….
_
_ ….
….
_
data,
meta-data,
knowledge
Oct 1999
_
….
_
_
…. _
_ ….
_
….
….
….
_
….
_
….
….
_
….
_
_
….
_
….
_
….
_
….
…. _
….
_
….
_
….
_
….
Internal:
transformers
and memory.
Gio XIT 9
Understand the Architecture for
Information Technology:
Component Classification
Customers
Customers
Customers
Customers
Customers
Services
Services
Services
Sources
Sources
Sources
Oct 1999
Gio XIT 10
Specifications for the components
Customer
models
Customers
Customers
Customers
Customers
Customers
Services
Services
Services
Sources
Sources
Sources
Oct 1999
Catalogs
Content
&
Methods
Metadata
Gio XIT 11
Functional Service Layers
Human-computer
Interaction
User interface
Client
Service
interface
Resource access
interface
Applicationspecific code
MEDIATION
Services
Domainspecific
code
Available Sources
Sourcespecific
code
Real-world
interface
Oct 1999
Gio XIT 12
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
Oct 1999
Gio XIT 13
Customer models
Customer is a person 6 one specific task
• arranging a vacation trip
• activity  location town  hotel by grade 
flight  public transport  rented car
•arranging a business trip
• location  hotel by plan  flight 
taxi or rented car
• getting a computer for Joe Cheap
• search CPU by price  modem  display
• getting a computer for Peter Fast
• search CPU by speed  storage  display  network
 Hierarchical
 alternatives at each level ( evaluate, commit, rollback )
Oct 1999
Gio XIT 14
Personal vs. Customer Model
Actual Person has multiple roles
 how to switch
 explicitly
 implicitly
 keep past contexts
Oct 1999
Switching rate will differ
• work versus fun
• adequacy of models
Gio XIT 15
Service layer
Multiple
domains !
Customer
Service
MEDIATION
Resource
access
Oct 1999
Shared
software,
standards ?
Gio XIT 16
Value-added intermediate services 1
Needs
Technologies extant and new
Describe customer Build interpretable workflow model with
model
meta-specifications for selection
Discover new
resources
Monitor and index public metadata,
describe resource capabilities, contents & methods
Select relevant
resources
Match available metadata and indices of resource
contents to leaf nodes in the customer model
Easy access to
resources
Wrap resources to make them compatible,
exploit wrapper templates, skip unavailable sources
Filter out
excessive data
Filters attached to the customer model;
balance relevant volume and precision
Oct 1999
Gio XIT 17
Value-added intermediate services 2
Needs
Technologies, extant and new
Identify articulations
*
Matching of related concepts,
use articulation rules to match nodes
Match level of detail
*
Automatic abstraction to match sources at
Integrate
information
articulation points within the customer model
Attach data instances to articulation points,
combine elements , link to customer model
Omit redundant
data, documents
Match data for content, omit overlap,
report inconsistencies in overlapping sources
Reduce customer
overload
Summarize according to customer model,
rank information at each level
Inform customer
Present information according to model
hierarchy, consider bandwidth
Oct 1999
Gio XIT 18
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
Oct 1999
Gio XIT 19
* 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
Oct 1999
Gio XIT 20
Mediator Service Design Principle
Transform Data into
Information
Match
User Model
Hierarchical
to
Resource Model
General network
(and maintain models)
Oct 1999
Gio XIT 21
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
Oct 1999
Customer:
• wants choices
• explanation
• background
Gio XIT 22
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
Oct 1999
Busy
Joe:
Speedy
Mike:
Greedy
Pete:
P1= P2, P3
P2, P1=P3
P1=P3, P2
Gio XIT 23
Mediation for Quality
User Model
f(S,C,T)
S= source
reliability
C= confidence
Assessments:
T=
S1=.8 S2=.9 S3=8
Estimates:
C1= 5+_1
T1=100+_160
S1
Oct 1999
C2= 8+_1
T2=70+_30
S2
BEST=
low cost
rapid response
reliable delivery
trustworthiness
C3= 10+_1
T3=50+_80
S3
Gio XIT 24
Computing Projections
For decision-making: not just past data
Next period alternatives
and subsequent periods
0.25
0.5
0.6
0.3
0.05
0.3
0.3
0.07
0.1
0.4
0.2
past
now
01.3
future
time
Integrate simulation results into information systems:
SQL
SimQL
Oct 1999
Gio XIT 25
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
Oct 1999
Gio XIT 26
Architecture instances
Applications . . . .
Mediators . . . . . .
Resources . . .
_
….
…. .
_
….
…. .
_
….
…. .
include computational resources
Oct 1999
Gio XIT 27
Assigning maintenance responsibility
a. Source data quality –
supplier database, files, or web pages
b. Interface to the source –
Sources
wrapper, supplier or vendor for supplier
c. Source selection –
expert specialist in mediator
d. Source quality assessment –
customer input to mediator
Services
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 –
Customers
client services with customer input
Oct 1999
Gio XIT 28
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
Clear models
temporal extensions
maintenance
}
Oct 1999
Gio XIT 29
Technology Transition
.
• Economic drivers have to be considered.
• Three party model
a
• Industry: need-based invention
• academia: formalization
• innovators: new technology
I
i
• New Service models provide new Opportunities
• supply innovative tools to industry
• supply specialized information to industry
Oct 1999
Gio XIT 30
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 ?
Oct 1999
Gio XIT 31
Research economy transfer paths
people
results
high
volume
Taxes
high-value
modest volume
Product suppliers (PS)
Products
Tool suppliers (TS) versus
Customers
Research
Teaching
Oct 1999
Government
Gio XIT 32
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
Oct 1999
Gio XIT 33
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 for research stores.
5 Research Venues and Technology Transfer.
6 Summary
Gio XIT 34
Oct 1999
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
Oct 1999
Gio XIT 35
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
Oct 1999
Gio XIT 36