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The following links have been tagged schema by users just like you, because these resources are off-site we cannot guarantee the accuracy or quality of any third-party information.
- Why is the
Star Schema a
Good Data
Warehouse
Design?: Database
design for
data
warehouses is
based on the
notion of the
snowflake
schema and its
important
special case,
the star
schema. The
snowflake
schema
represents a
dimensional
model which is
composed of a
central fact
table and a
set of
constituent
dimension
tables which
can be further
broken up into
subdimension
tables. We
formalise the
concept of a
snowflake
schema in
terms of an
acyclic
database
schema whose
join tree
satisfies
certain
structural
properties. We
then define a
normal
form...Mark
Levene, George
Loizou
- Why is the
snowflake
schema a good
data warehouse
design: Database
design for
data
warehouses is
based on the
notion of the
snowflake
schema and its
important
special case,
the star
schema. The
snowflake
schema
represents a
dimensional
model which is
composed of a
central fact
table and a
set of
constituent
dimension
tables which
can be further
broken up into
subdimension
tables. We
formalise the
concept of a
snowflake
schema in
terms of an
acyclic
database
schema whose
join tree
satisfies
certain
structural
properties. We
then define a
normal
form...M
Levene, G
Loizou
- The Relation
between
Ontologies and
Schema-languag
es:
Translating
OIL-specificat
ions in
XML-Schema: (2000)Currentl
y computers
are changing
from single
isolated
devices to
entry points
in a world
wide network
of information
exchange and
business
transactions
called the
World Wide Web
(WWW).
Therefore
support in
data,
information,
and knowledge
exchange
becomes the
key issue in
current
computer
technology.
Ontologies
provide a
shared and
common
understanding
of a domain
that can be
communicated
between people
and
application
systems.
Therefore,
they may play
a major role
in
supporting...M
Klein, D
Fensel, Fv van
Harmelen, I
Horrocks
Source: (2000) - The management
of changing
types in an
object-oriente
d database: (1986), pp.
483-495.Andrea
Skarra,
Stanley Zdonik
Source: (1986), pp. 483-495. - Design and
implementation
of a
generalized
laboratory
data model: BMC
Bioinformatics
, Vol. 8, No.
1.
(2007)BACKGROU
ND:Investigato
rs in the
biological
sciences
continue to
exploit
laboratory
automation
methods and
have
dramatically
increased the
rates at which
they can
generate data.
In many
environments,
the methods
themselves
also evolve in
a rapid and
fluid manner.
These
observations
point to the
importance of
robust
information
management
systems in the
modern
laboratory.
Designing and
implementing
such systems
is non-trivial
and it appears
that in many
cases a
database
project
ultimately
proves
unserviceable.
RESULTS:We
describe a
general
modeling
framework for
laboratory
data and its
implementation
as an
information
management
system. The
model utilizes
several
abstraction
techniques,
focusing
especially on
the concepts
of inheritance
and meta-data.
Traditional
approaches
co-mingle
event-oriented
data with
regular entity
data in ad hoc
ways. Instead,
we define
distinct
regular entity
and event
schemas, but
fully
integrate
these via a
standardized
interface. The
design allows
straightforwar
d definition
of a
"processing
pipeline" as a
sequence of
events,
obviating the
need for
separate
workflow
management
systems. A
layer above
the
event-oriented
schema
integrates
events into a
workflow by
defining
"processing
directives",
which act as
automated
project
managers of
items in the
system.
Directives can
be added or
modified in an
almost trivial
fashion, i.e.,
without the
need for
schema
modification
or
re-certificati
on of
applications.
Association
between
regular
entities and
events is
managed via
simple
"many-to-many"
relationships.
We describe
the
programming
interface, as
well as
techniques for
handling
input/output,
process
control, and
state
transitions.CO
NCLUSIONS:The
implementation
described here
has served as
the Washington
University
Genome
Sequencing
Center's
primary
information
system for
several years.
It handles all
transactions
underlying a
throughput
rate of about
9 million
sequencing
reactions of
various kinds
per month and
has handily
weathered a
number of
major pipeline
reconfiguratio
ns. The basic
data model can
be readily
adapted to
other
high-volume
processing
environments.M
ichael Wendl,
Scott Smith,
Craig Pohl,
David Dooling,
Asif
Chinwalla,
Kevin Crouse,
Todd Hepler,
Shin Leong,
Lynn
Carmichael,
Mike Nhan,
Benjamin
Oberkfell,
Elaine Mardis,
Ladeana
Hillier,
Richard Wilson
Source: BMC Bioinformatics, Vol. 8, No. 1. (2007) - Rondo: a
programming
platform for
generic model
management: (2003), pp.
193-204.Sergey
Melnik, Erhard
Rahm, Philip
Bernstein
Source: (2003), pp. 193-204. - Automatic Web
Information
Extraction in
the ROADRUNNER
System: (2002), pp.
264-277.Valter
Crescenzi,
Giansalvatore
Mecca, Paolo
Merialdo
Source: (2002), pp. 264-277. - A survey of
approaches to
automatic
schema
matching: VLDB Journal:
Very Large
Data Bases,
Vol. 10, No.
4. (????
2001), pp.
334-350.Schema
matching is a
basic problem
in many
database
application
domains, such
as data
integration,
E-business,
data
warehousing,
and semantic
query
processing. In
current
implementation
s, schema
matching is
typically
performed
manually,
which has
significant
limitations.
On the other
hand, previous
research
papers have
proposed many
techniques to
achieve a
partial
automation of
the match
operation for
specific
application
domains. We
present a
taxonomy that
covers many of
these
existing...Erh
ard Rahm,
Philip
Bernstein
Source: VLDB Journal: Very Large Data Bases, Vol. 10, No. 4. (???? 2001), pp. 334-350. - Automatic
extraction of
informative
blocks from
webpages: (2005), pp.
1722-1726.Sand
ip Debnath,
Prasenjit
Mitra, Lee
Giles
Source: (2005), pp. 1722-1726. - ViPER:
augmenting
automatic
information
extraction
with visual
perceptions: (2005), pp.
381-388.Kai
Simon, Georg
Lausen
Source: (2005), pp. 381-388.
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