emerging database teshnologies

8/7/2019 Emerging Database Teshnologies

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Dinesh Rao


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1. Mobile Database.

2. Multimedia Database.

3. GIS ( Geographic Information Systems ).

4. Genome Data Management


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1.Mobile Database


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` Portable devices and wireless technology led to mobile computing.

` Portable computing devices and wireless communication allowed

the client to access data from any where and any time.

` There are some HW and SW problems that must be solved to make

maximum exploitation of mobile computing. i.e. Database recovery.

` Hardware problems are more difficult. Wireless coverage.

Battery.

Changes in network topology.

Wireless Transmission Speed.


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Mobile Computing Architecture


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In a MANET, co-located mobile units do not need tocommunicate via a fixed network, but instead, form their ownusing cost-effective technologies such as Bluetooth.

In a MANET, mobile units are responsible for routing their owndata, effectively acting as base stations as well as clients.

MANET must be robust enough to handle changes in networktopology. Such as arrival or departure of mobile unites.

MANET can fall underP2P architecture.

Mobile Ad-Hoc Network (MANET)


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Communication latency

Intermittent connectivity

Limited battery life

Changing client location

All of these Characteristics impact data management in mobile

computing.

Characteristics ofMobile Environments - 1


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The server may not be able to reach the client or vise

versa.

We can add proxies to the client and the server to cacheupdates into when connection is not available.

After the connection is available proxy automatically

forward these updates to its destination.



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The latency involved in wireless communication makesscalability a problem.x Since latency increases the time to service each client request,

so the server can handle fewer clients.

Servers can use Broadcasting to solve this problem.

Broadcast well reduces the load on the server, as clients

do not have to maintain active connections to it.x For example weather broadcasting



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` Client mobility also poses many data management

challenges: Servers must keep track of client locations in order to efficiently

route messages to them. Client data should be stored in the network location that

minimizes the traffic necessary to access it.

The act of moving between cells must be transparent to the

client.

` Client mobility also allows new applications that are

location-based.



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Mobile databases can be distributed under two possible

scenarios:1. The entire database is distributed mainly among the wired

components, possibly with full or partial replication. Management is done in fixed hosts, with additional functionalities.

2. The database is distributed among wired and wireless

components.

Management is done in both fixed hosts and mobile units.

Data Management Issues


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Data distribution and replication (Cache)

Transactions models

Query processing (where data is located?)

Recovery and fault tolerance Mobile database design

Location-based service

Division of labor

Security

Data Management Issues


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Application: IntermittentlySynchronized Databases

Insert\Update Data


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2.Multimedia Database


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` In the years ahead multimedia information systems

are expected to dominate our daily lives.


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` DBMSs have been constantly adding to the types of

data they support.

` Today many types of multimedia data are available in

current systems. Text.

Graphics.

Images.

Animation.

Video. Audio.


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` Multimedia data may be stored, delivered, and utilized

in many different ways.

` Applications may be categorized based on their datamanagement characteristics. Repository applications.

x A large amount of multimedia data as well as metadata is stored for retrieval

purposes.

Presentation applications.

x Simple multimedia viewing of video or audio data.

Collaborative work using multimedia information.

x Which engineers may execute a complex design task by merging drawings,

fitting subjects to design constraints, and generating new documentation,

change notifications, and so forth.

Nature ofMultimedia Applications


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y Multimedia applications dealing with thousands

of images, documents, audio and video

segments, and free text data depend criticallyon:y Appropriate modeling of the structure and content of

data.

y Designing appropriate database schemas for storing andretrieving multimedia information.

Data Management Issues - 1


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` Multimedia information systems are very complex and

embrace a large set of issues:

Modeling:x Complex Objects, dealing with large number of types of data (Graphics).

Design:

x Conceptual, logical, and physical design of multimedia has not been

addressed fully, and it remains an area of active research.

Storage:

x Multimedia data on standard disk devices presents problems of representation,compression, mapping to device hierarchies, archiving, and buffering during

the input/output operation.

x DBMS has presented the BLOB type (BinaryLarge Object).



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Multimedia information systems are very complex and

embrace a large set of issues (cont.):

Queries and retrieval: The database way of retrieving information is based on query languages

and internal index structures.

Performance :

Multimedia applications involving only documents and text, performance

constraints are subjectively determined by the user.

Applications involving video playback or audio-video synchronization,physical limitations dominate.



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Documents and records management

Knowledge dissemination

Education and training Marketing, advertising, retailing, entertainment, and

travel

Real-time control and monitoring

Multimedia Database Applications


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3.Geographic InformationSystems (GIS)


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` Geographic information systems(GIS): A systematicintegrationofhardwareandsoftwarefor

capturing,storing,displaying,updatingmanipulatingand

analyzingspatialdata.


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y GIS can be divided into two formats:y Vectordata represents geometric objects such as points, lines,

and polygons.

y Rasterdata is characterized as an array of points, where each

point represents the value of an attribute for a real-worldlocation.

y Informally, raster images are n-dimensional array where each entry

is a unit of the image and represents an attribute


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` There are several aspects of the geographical

objects need to be considered:Location.

Temporality.

Complex Spatial Features.

Object ID.

Data Quality.

Characteristics of Data in GIS


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y The geographic context, topologic relations and

other spatial relationships are fundamentally

important in order to define spatialintegrityrules.

Characteristics of Data in GIS


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y TopologyIntegrity.y Dealswith thebehavioroffeaturesandthespatial

relationshipbetween

them.

y Semantic Integrity.y Dealswith themeaning.

y User Defined Integrity.

y Businessrules.y Temporal.

y Punctualand Durable.

Constraints in GIS


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` Briefly discuss the common conceptual models

for storing spatial data in GIS.

` Some conceptual data models: Rasterdatamodel:x Used for analytical applications.

Vectordatamodel:x Analysis is done using a well defined set of tools.

Conceptual Data Models forGIS


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Conceptual Data Models forGIS

Some conceptual data models (cont.):

Networkmodel:

Define how lines connect to each other in a point. Rules are stored in a connectivity table.

Example of everyday application, optimizing a school bus route.

TIN datamodel: TriangularIrregular Network.

Is a vector-based approach.

models surfaces by connecting sample points as vector

of triangles.


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DBMS Enhancements forGIS

Until the mid 1990s, GIS system was based mainly on file-based

systems.

No transfer standards was defined, which limited vendors in terms of

sharing.Involved in a geo-structure and attributes was stored in DBMS.

The spatial features was kept in a file and linked to the attributes.

Could not take FULL advantage of commercial RDBMS.

Database extensions has been released by vendors like DB2 spatial

extender, and OracleSpatial and OracleLocator to support GIS data.

These extensions allowed theuser to store, manage, and retrievegeo-objects.


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GISStanders and Operations

Spatial Analysis Standard:Distance.

Returns the shortest distance between any two points in two

geometries.Buffer.

Returns a geometry that represents all points whose

distance from the given geometry is less than or equal to

distance.Convex Hull.

Union.

And more.


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GISStanders and OperationsCREATE TABLE STATES (Sname VARCHAR(50) NOT NULL,State_shape POLYGON NOT NULL,

Country VARCH

AR(50)

NOT NULL,PRIMARY KEY (Sname),

FOREIGN KEY (Country) REFERENCES COUNTRIES (Cname));

SELECT SnameFROM STATSWHERE (AREA (State_shape) > 50000)


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Future ofGISThere are some challenges in developing GIS

applications:Data Source.

Data Model.

Standards.

Mobile GIS.

Specialized DBMS forGIS.


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4.Genome DataManagement


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Biological Sciences and Genetics(1):The biological sciences encompass an enormous variety ofinformation. Environmental science gives us a view of how specieslive and interact in a world filled with natural phenomena. Histologyand cell biology delve into the tissue and cellular levels and provideknowledge about the inner structure and function of the cell. This

wealth of information that has been generated, classified, and storedfor centuries has only recently become a major application ofdatabase technology.Genetics has emerged as an ideal field for the application ofinformation technology. In a broad sense, it can be taught of as theconstruction of models based on information about genes which

can be defined as units of heredity

and population and the seekingout of relationships in that information.


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Biological Sciences and Genetics(2):

The study of genetics can be divided into three branches:

1. Mendelian genetics is the study of the transmission of traits

between generations.

2. Molecular genetics is the study of the chemical structure and

function of genes at the molecular level.3. Population genetics is the study of how genetic information

varies across populations of organisms


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Biological data exhibits many special characteristics that makemanagement of biological information a particularly challenging

problem. The characteristics related to biological information, and

focusing on a multidisciplinary field called bioinformatics that has

emerged. Bioinformatics addresses information management of

genetic information with special emphasis on DNA sequence

analysis.Applications of bioinformatics span design of targets for drugs, study

of mutations and related diseases, anthropologicalinvestigations on migration patterns of tribes and therapeutictreatments.

Characteristic 1: Biological data is highly complex when comparedwith most other domains or applications.

Characteristic 2: The amount and range of variability in data is high.Characteristic 3: Schemas in biological databases change at a rapid

pace.


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Characteristic 4: Representations of the same data by different biologists

will likely be different (even using the same system).

Characteristic5: Most users of biological data do not require write access

to the database; read-only access is adequate.

Characteristic 6: Most biologists are not likely to have knowledge of theinternal structure of the database or about schema design.

Characteristic 7: The context of data gives added meaning for its use in

biological applications.

Characteristic 8: Defining and representing complex queries is extremely

important to the biologist.

Characteristic 9: Users of biological information often require access toold values of the data particularly when verifying previously

reported results.


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GenBank

As of release 135.0 in April 2003, GenBank contains over31

billion nucleotide bases of more than 24 million sequences from

over100,000 species with roughly1400 new organisms being

added eachmonth.

The database size in flat file format is over100GB

uncompressed and has been doubling every15 months.

International collaboration with the European MolecularBiology

Laboratory (EMBL) in the U.K. and the DNA Data Bank of Japan

(DDBJ) on daily basis.


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Other limited data sources (e.g. three-dimensional structure and

Online Mendelian Inheritance in Man (OMIM), have been added

recently by reformatting the existing OMIM and PDB databases

and redesigning the structure of the GenBank system to

accommodate these new data sets.

The system is maintained as a combination of flat files,

relational databases, and files containing Abstract Syntax

Notation One (ASN.1)

The average user of the database is not able to access thestructure of the data directly for querying or other functions,

although complete snapshots of the database are available for

export in a number of formats, including ASN.1.


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DATABASE

NAME

MAJOR

CONTENT

INITIAL

TECHNOLOGY

CURRENT

TECHNOLOGY

DB PROBLEM

AREAS

PRIMARY DATA

TYPES

GenBank DNA/RNA

sequence,

protein

Text files Flat-file/ASN.1 Schema browsing,

schema evolution,

linking to other dbs

Text, numeric, Some

complex types

OMIM Disease phenotypes

and genotypes,etc

Index cards/text files Flat-file/ASN.1 Unstructured, free

text entries linking toother dbs

Text

GDB Genetic map linkage

data

Flat file Relational Schema expansion /

evolution, complex

objects, linking to

other dbs

Text, Numeric

ACEDB Genetic map linkage

data, sequence

data(non-human)

OO OO Schema expansion

/evolution, linking to

other dbs

Text, Numeric

HGMDB Sequence and

sequence variants

Flat File-application

specific

Flat File-application

specific

Schema expansion

/evolution, linking to

other dbs

Text

EcoCyc Biochemical

reactions and

pathways

OO OO Locked into class

hierarchy, schema

evolution

Complex types, text,

numeric


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Thanks