IIS WS 2015/16
Intelligent Information Systems
- WS 2015/16 -
Prof. Dr. Rainer Manthey
Wednesday
Lecture 10:30 – 12:00 a.m.
Exercises 12:45 – 14:15 p.m.
(MA-INF 3203)
© 2015 Prof. Dr. Rainer Manthey
Intelligent Information Systems
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Chap. 2: Datalog and SQL
Intelligent Information Systems
WS 2015/16
Organisation and
Motivation
Chapter 1
© 2015 Prof. Dr. Rainer Manthey
Intelligent Information Systems
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Vita Rainer Manthey
1973
1973 Kiel
Kiel
1953
1953 Wilhelmshaven
Wilhelmshaven
University of Kiel
Informatics/Mathematics
Student
(Diploma 1979)
Research assistant (PhD 1984)
1992
1992 Bonn
Bonn
University of Bonn
Professor
© 2015 Prof. Dr. Rainer Manthey
European Computer-Industry
Research Centre (ECRC)
Researcher/
1984
1984 München
München Teamleader
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Modules Offered by the IDB Group
IDB (Intelligent Databases) Group:
Prof. Dr. Rainer Manthey
PD Dr. Andreas Behrend
Sahar Vahdati, MSc
WS
Intelligent
Information
Systems
WS+SS
(MA-INF 3203)
Seminar
Selected Topics in
Intelligent IS
SS
(MA-INF 3210)
Temporal
Information
Systems
Intelligent
Information
Systems II
(MA-INF 3302)
(MA-INF 3104)
Lab
Intelligent Information
Systems
(MA-INF 3313)
© 2015 Prof. Dr. Rainer Manthey
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IDB: Perspectives for the Next Three Years
Prof. Dr. Rainer Manthey:
• SS 2016: „Sabbatical“ semester, i.e., research only, no teaching!
• 28.2.2019: Day of retirement
• => 5 semesters of teaching left (after this semester):
WS 16/17, SS 17, WS 17/18, SS 18, WS 18/19
• => Supervision of master thesises: 1.10.2016 – 30.9.2018
PD. Dr. Andreas Behrend:
• PD/Habilitation: Full qualifications for any kind of
academic teaching (incl. thesis supervision), independent teaching schedule
• Position at Uni Bonn ends at 31.12.2017 (at latest)
• => At most 3 semesters of teaching left (after this semester):
SS 16, WS 16/17, SS 17
© 2015 Prof. Dr. Rainer Manthey
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Organisation
Intelligent Information Systems
WS 2015/16
Organisation
© 2015 Prof. Dr. Rainer Manthey
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Weekly Schedule
(nearly) every Wednesday during this semester
10:00
11:00
10:30 – 12:00
Lecture
12:00
Long break (45 mins)
13:00
12:45 – 14:15
Exercises
14:00
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Schedule WS 2015/16
Wednesday
October
21
28
November
Begin of exercises
4
11
18
25
December
2
Dies academicus
9
16
January
Xmas break
13
20
27
February
13 lectures
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3
10
End of exercises
12 exercises
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Exercises and Exams: „Rules of the Game“
• Exercises:
• In the same room every Wednesday, following the lecture after 45 minutes break,
for the entire auditorium, no small groups.
• Exercises held by Prof. Manthey and/or Mrs. Sahar Vahdati.
• Goals:
• To make you fit for the exam!
• To provide some „hands on“ experience with theoretically introduced concepts.
• Participation will not be checked, but is strongly recommended!!
• No prerequisites for getting admission to exams!
• No „homework“ to be delivered, but motivation/encouragement for individual
activity provided in exercises.
• No individual feedback possible.
•
Exams:
• Written exams for both exam dates (MSc CS: 6 credits, MSc MI: 4 credits)
• Exam dates to be determined:
Most likely end of February + end of March
• Registration in BASIS (MSc CS only):
three-weeks period in December – to be announced
• Registration using special forms for all others: same period
(forms available in exercises or by download)
© 2015 Prof. Dr. Rainer Manthey
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IIS Homepage
http://www.iai.uni-bonn.de/III//lehre/vorlesungen/IntelligentIS/WS15/
Slides for download
© 2015 Prof. Dr. Rainer Manthey
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No Book, just Slides!
There is no textbook which could be recommended for this lecture . . .
. . . just the slides serve as a substitute instead
(representing a compromise between a good
background presentation and too much text)
© 2015 Prof. Dr. Rainer Manthey
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A Word of Warning
But:
Only a small fraction of
the attendees will have a
chance to get a place in
seminars (and labs) or to
get a master thesis in this
area!
IIS 2014: 101 participants in the exam !!
© 2015 Prof. Dr. Rainer Manthey
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Background
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Background
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Information Systems: The DB-centered View
Information System
 External media
of communication
 Applicationspecific
methods
Database System
This is the most commonly agreed view on the concept of an IS in informatics –
provided people agree on the meaning of DBS!!
© 2015 Prof. Dr. Rainer Manthey
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Databases and Database Systems
Database System
DBMS
DB
....
Databases
Users and
application programmes
© 2015 Prof. Dr. Rainer Manthey
DBMS: Data Base Management System
(Many powerful application-independent
services: schema mgt, query optimization,
storage mgt, transaction mgt, etc.)
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IDBS rather than IIS
This lecture will be more accurately concerned with
Intelligent Database Systems
rather than with
Intelligent Information Systems
The naming of the module is more a matter of convention rather than precision!
© 2015 Prof. Dr. Rainer Manthey
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Query Languages vs. Programming Languages
Imperative
programming
language
Declarative
query
language
DBMS
DB
Data Dictionary
Interpreter
• „Real“ DBMS support a separate kind of DB-specific „programming language“ for
accessing and manipulating data in the DB: query language
• In contrast to the external imperative programming languages, a query language is
usually a declarative language, the performance of which is optimised by the DBMS.
• „Programs“ of the query language may be stored in the data dictionary within the DB.
© 2015 Prof. Dr. Rainer Manthey
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Relational Data Model and SQL
• The most widely used data model nowadays
is the relational model (introduced around 1970).
Relations are the mathematical basis for data
represented in tables (rows/columns).
• All relational DBMS support a predominant
declarative query language based on logical and
algebraic operators:
SQL (Structured Query Language)
© 2015 Prof. Dr. Rainer Manthey
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Background in Relational Databases and SQL: Strictly Necessary !
Material for self-study
(in case your background is
weak, dated, or missing):
• Extra slides via IIS
homepage
• Cheap and easy tutorials
from the Schaum‘s series
A good background in relational databases and
in SQL is expected from everybody attending
this lecture!! SQL will frequently be used during
the semester, even though we are going to learn
a different relational language!
© 2015 Prof. Dr. Rainer Manthey
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Motivation
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Motivation
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Intelligent Database or Intelligent Database System?
DBS
DB
DBMS
....
?
Where is „intelligence“ located?
In the DB or in the DBMS?
Or even outside the DBS?
© 2015 Prof. Dr. Rainer Manthey
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IDBS: „Intelligent Services“ in a DBMS
DBS
DBMS
DB
generic
specific
Certainly required: „Intelligent“ behaviour of the DBS,
i.e., generic (application-independent) services
inside the DBMS, able to „simulate intelligence“
© 2015 Prof. Dr. Rainer Manthey
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IDBS: „Knowledge“ Inside a DB
DBS
DD
DBMS
DB
generic
specific
Also certainly required: „Knowledge“ about the resp. application domain in the DD
(Data Dictionary)
„Knowledge“: Rules from the application domain as a basis for
drawing intelligent conclusions from stored data
© 2015 Prof. Dr. Rainer Manthey
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IDBS: „Traditional“ Approach with External System Components
Inference System, Agent System, Expert System
Knowledge Base,
Rule Base
DBS
„loose coupling“
DB
DBMS
Preferred by many: Move „Intelligence“ and „Knowledge“ out of the DBS
© 2015 Prof. Dr. Rainer Manthey
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IDBS: Our Approach – „In database-Intelligence“!
DBS
DB
DBMS
„tight coupling“
Approach favoured by our research group (and thus in this lecture):
• Try to reach as much „intelligence“ as possible using existing DB technology!
• Identify weaknesses of this technology and think about reasonable
extensions, without leaving the DB context!
© 2015 Prof. Dr. Rainer Manthey
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At the Core of IIS: Theory and Practice of Deductive Databases
This approach – which is a special one –
explains the drawing on the title slide of
this lecture.
Therefore:
Theory and Practice of the established
research area of „Deductive Databases“
will be at the core of this lecture.
The essence of this area of research can be
described as follows:
How to analyse data using stored queries
(in SQL: views) that serve as declarative
analytical programs?
© 2015 Prof. Dr. Rainer Manthey
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Datalog and SQL
• Research in deductive databases has a nearly 40-years history (as old as SQL), but
has been using a different declarative language (not SQL!) most of the time, strongly
influenced by the logic programming language PROLOG:
Datalog
• Nearly all publications in this area have been using Datalog – that‘s why we will use
Datalog during this lecture, too (and you will have to learn it!).
• Many results of DDB research have been transferred to the SQL world recently!
That‘s why SQL will also be appearing throughout the lecture in various places.
SQL:
•
•
•
•
•
Datalog:
used in industry and commerce
supported by many DBMS products
standardized
user-friendly („controlled English“)
rich set of syntactic features
© 2015 Prof. Dr. Rainer Manthey
•
•
•
•
•
used in academia only
just few academic protoypes
no standards
mathematical style
minimalistic syntax
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Datalog vs. SQL: Comparison in a Nutshell
SQL views
Datalog rules
s(X)  p(X,Y).
s(X)  r(Y,X).
t(X,Y,Z)  p(X,Y), r(Y,Z).
w(X)  s(X), not q(X).
CREATE VIEW s AS
(SELECT a FROM p)
UNION
(SELECT b FROM r);
CREATE VIEW t AS
SELECT a, b, c
FROM p, r
WHERE p.b = r.a,
CREATE VIEW w AS
(TABLE s)
MINUS
(TABLE q);
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Datalog Basics on a Single Slide
Constants
Facts
p(1,a).
p(2,b).
p(3,c).
q(2).
q(5).
Rules
s(X)  p(X,Y).
s(X)  r(Y,X).
Variables
t(X,Y,Z)  p(X,Y), r(Y,Z).
w(X)  s(X), not q(X).
r(a,1).
r(a,2).
r(b,3).
Conjunction
Negation
Relation Names
p, q, r: Base relations
© 2015 Prof. Dr. Rainer Manthey
s, t, w: Derived relations
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Structure of the Course
This is how the lecture will be structured – the number of lectures might be slightly varying
in „real life“
1. Organisation and Motivation
1 lecture
2. Deduction in Datalog and SQL
3. Semantics of Deductive Databases
4. Efficient Query Evaluation in DDBs
3 lectures
4 lectures
4 lectures
5. Perspectives
1 lecture
Timetable:
•
•
•
•
•
relevant for
exam
Chapter 1: today
Chapter 2: Oct/Nov
Chapter 3: Nov/Dec
Chapter 4: Jan/Febr
Chapter 5: Febr
© 2015 Prof. Dr. Rainer Manthey
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Static Analysis Followed by Dynamic Analysis
WS:
Intelligent
Information
Systems
(MA-INF 3203)
SS:
Intelligent
Information
Systems II
(MA-INF 3104)
© 2015 Prof. Dr. Rainer Manthey
Focussing on foundations of declarative languages
and applying queries and views for analysing
Static scenarios (i.e., individual DB states)
Continuing IIS by adding the deductive analysis of
updates and transactions and thus analysing
Dynamic scenarios (i.e., sequences of changes
of DB states)
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Static Analysis: A Motivational Case Study (1)
As a case study,
we will use a
well-known
noble family:
In the next lecture, we will
discuss a typical example of
a relational database providing
a lot of opportunities for
static analysis of data using
stored queries:
Genealogical Databases
Genealogy is the discipline of
exploring family relationships
between persons and their
ancestors/descendants.
© 2015 Prof. Dr. Rainer Manthey
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Static Analysis: A Motivational Case Study (2)
?
How to „put a family tree into a (relational) database“?
© 2015 Prof. Dr. Rainer Manthey
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Static Analysis: A Motivational Case Study (3)
Is this a
„good“
DB schema?
One possible relational format for family trees:
just two tables!
© 2015 Prof. Dr. Rainer Manthey
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Static Analysis: A Motivational Case Study (4)
• A lot of implicit data about
the resp. family are „hidden“
in the family tree data!
• There is plenty of well-known
genealogical terminology, such
as forms of being relatives or
relatives-in-law, each of which
can be specified by means of
DB queries.
• Applying such declarative
specifications to the stored
data is a typical example of
static analysis of a database.
e.g.:
How to specify the concept of being an uncle of somebody in SQL?
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