Information value and conceptual modelling:

a systemic survey of economic, social and technological issues 

Carlo Batini, Gianluigi Viscusi Università di Milano Bicocca

(batini, viscusi)@disco.unimib.it

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Extreme synthesis of the Tutorial When you give more than you get, you are blessed

Graffito on the climb to Brunelleschi’s Dome

in Florence (640 steps),

When you get more than you give, you are rich

Adapted for Adam Smith (1723-1790)

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Tutorial on Information Value - ER 2012

0. Introduction to the Tutorial (10 minutes)

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The fil rouge starts with this book and related research……

A book in the area of conceptual data base design.The Entity Relationship model is adopted.

1994

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...proceeds with this second book..

The book is an investigation of data quality dimensions, models, methodologies, and techniques

2006

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…ends with this third book

A methodology for strategic and operational planning of initiatives related to service oriented informations systems for eGovernment, considering the quality of service, and economic, social, organizational, legal and, finally, technological issues

2010

Origins of Information Value (Shannon 1948)

•  Definition of Information in Shannon’s Communication Theory.

•  Information conveyed by a message is proportional to the inverse of the probability of the message

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Assign a value (whatever it means) to these four information

•  An e-mail at Christmas: «Merry Christmas and Happy New Year»

•  A phone call from the lottery: «Congratulations! You won 100.000 €!»

•  An e-mail from VLDB: Your paper has been accepted!

•  An e-mail from VLDB: Your paper has been rejected!

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LOW

HIGH

HIGH

HIGH

Value of Information depends

on the receiver

The infological problem (Langefors 1974)

•  Infological problem, determining which information the system should provide in order to satisfy users’ information needs

•  Datalogical problem, i.e., determining how the information and system should be structured using IT

•  Infological equation:

I = i(D, S,t)

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The infological problem (Langefors 1974)

I = i(D, S,t) where: •  I is the information produced by the system; •  D is the data made available by system processes; •  S is the recipient’s prior knowledge and expertise (world

view); •  t is the time period during which the interpretation

process occurs; and •  i is the interpretation process that produces information

for a recipient based on both the data and the recipient’s prior knowledge and experience.

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The infological problem (Langefors 1974)

•  Langefors’ equation recognized that information is not simply the result of algorithmic processing.

•  Information included the result of prior knowledge and experience of the individual receiving the results of the processing data.

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The infological problem (Langefors 1974)

•  No two individuals would receive exactly the same information from one data processing.

•  Individuals having similar prior experience and knowledge could possibly share meaningful interpretations of the same data.

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Reaction of economists

•  Information theory based upon the work of Shannon has fascinated economists.

•  Perhaps the main reason for this has been that in his theory Shannon gave a measurement to a piece of information.

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Reaction in decision and risk theory - 1

•  Considering just the probabilities of outcomes without considering their consequences is not adequate in describing the importance of uncertainty to a decision maker.

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Reaction in decision and risk theory - 2

For example, if –  losing all your assets in the stock market

and –  having whale steak for supper

have the same probability, then the information associated with the occurrence of either event is the same. But, the economic utility is quite different!!!

Reaction in decision and risk theory - 3

•  It is necessary to be concerned not only with – the probabilistic nature of the

uncertainties that surround us, but also with –  the economic impact

that these uncertainties will have on us.

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Reaction in Social Sciences

•  Value of information lies in contributing to the quality of life.

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Public/Social value Economist October 2011

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Types of value •  Intrinsic value •  Extrinsic value •  Public value •  Social value •  Economic value

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And also … •  Ethical value •  Emotional value •  Epistemic value •  Artistic value •  Scientific value •  Xxx Value

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2. Extrinsic v.

2. Intrinsic v.

4. Social v.

3. Public v.

7. in Decision Analysis

8. IV and Info. Quality

5. Economic v.

5. of an Infor- mation product

5. of an Infor mation system

6.1 Conc. Modeling as a tool for IV

6.3.2 of Open Linked Data

6.3.1. of ontologies

6.2 IV and abstractions

Map at a glance of concepts discussed in the Tutorial

1. Paradigms

9.Open Issues

10. References

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2. Extrinsic v.

2. Intrinsic v.

4. Social v.

3. Public v.

5. Economic v.

5. of an Infor- mation product

5. of an infor mation system

7. in Decision Analysis

6.3.2 of Open Linked Data

6.3.1. of ontologies

6.1 Conc. Modeling as a tool for IV

6.2 IV and abstractions

8. IV and Info. Quality 9.Open

Issues

Sections addressing conceptual modeling issues

1. Paradigms

10. References

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2. Extrinsic v.

2. Intrinsic v.

4. Social v.

3. Public v.

5. Economic v.

5. of an Infor- mation product

5. of an infor mation system

7. in Decision Analysis

6.3.2 of Open Linked Data

6.3.1. of ontologies

6.1 Conc. Modeling as a tool for IV

6.2 IV and abstractions

8. IV and Info. Quality

9.Open Issues

Sections discarded for lack of time but included in the material

1. Paradigms

10. References

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2. Extrinsic v.

2. Intrinsic v.

4. Social v.

3. Public v.

5. Economic v.

5. of an Infor- mation product

5. of an infor mation system

7. in Decision Analysis

6.3.2 of Open Linked Data

6.1 Conc. Modeling as a tool for IV

6.2 IV and abstractions

Distribution of topics

1. Paradigms

Viscusi

Batini

Contents •  0. Introduction to the tutorial •  1. Paradigms involved in the tutorial

•  information value •  conceptual modeling

•  2. Types of information value –  Intrinsic and extrinsic value –  Economic, public and social value

•  3. Public value in Depth •  4. Social Value in Depth •  5. Economic value in Depth •  6. Information value and Conceptual Modeling

1.  Conceptual modeling as a tool to compute Information Value 2.  Information abstraction and information value 3.  Information value in ontologies

1 Economic value of ontologies as a production technology 2 Public value of open linked data

•  7. Information Value in Decision Analysis 8. Information Value and Information Quality

•  9. Open issues in Information Value •  10. References

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Batini

Viscusi

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