32N2386-Reference Model_for_BigDatax - ISO/IEC JTC1 SC32 ...

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Nov 15, 2013 (3 years and 4 months ago)

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Next Generation Analytics &
Big Data

(A
Reference Model
for Big Data)

Jangwon

Gim

Sungjoon

Lim

Hanmin

Jung


ISO/IEC JTC1 SC32 Ad
-
hoc meeting

May 29, 2013,
Gyeongju

Korea

32N2386

Contents


Background


Brief history
of discussions


Case
s
tudy


Procedure
for d
eveloping standardizations for
Big D
ata


Reference model for
Big
Data


Conclusions

2

Discussion of Big Data


Data analytics


Data analysis


Baba: Vocabulary, Use
-
case, and so on



Stabilize Architecture


Define Interfaces


Standardization opportunities


Jim: The aspect of Big Data is “There is many different forms”


Krishna: Refers to Wikipedia definition


Keith
Gorden
: Volume, Complex, Velocity


Keith W. Hare: Open Big Data




Volume, Variety, Velocity, Value, Veracity

Any combination is OK.




3

Background


Emerging Technologies For Big Data


In 2012, The hype cycle of Gartner



Diverse definitions of technologies and services, having different views of data











4

Background


Big Data on hype cycle















A
general and common reference model for Big Data is
needed

5

Brief history of discussions


6

Issue

Date

Summary

16

November

2011
.

[SC
32
N
2181
]

ISO/IEC

JTC

1
/SC

32

N
2181
,

“Resolutions

and

topics

from

the

recent

JTC

1

me
eting

of

particular

interest

to

SC

32

participants”,

SC
32

Chair



Jim

Melton

12 January 2012.

[SC
32
N
2198
]

ISO/IEC

JTC

1
/SC

32

N

2198
,

“Analysis

of

2012

Gartner

Technology

Trends”,

䩔C
1

SWG
-
P

-

䵡物M

W敮Tt



Convener





6

T敬ec潭oun楣a瑩潮t

慮d

楮f潲ma瑩潮

exch慮ge

be瑷敥n

syst敭s




SC

32

Data

management

and

interchange



SC

39

Sustainability

for

and

by

Information

Technology

19 March 2012.

[SC
32
N
2199
]ISO/IEC

JTC

1
/SC

32

N

2199
,

“Discussion
:

SC

32

Response

to

2011

JTC

1

Resolution

33
”,

SC
32

Chair



Jim

Melton

6 June 2012.

[SC
32
N
2241
]

Ad
-
hoc

on

“Next

gen

analytics”

-

Keith

Hair

-

Chair

The view of Next
-
Generation Analytics of SC32


Referencing from

[SC32N2241
]













Need a reference model for Big Data to enhance interoperability

7

Next
-
Generation Analytics

Social Analytics

From Baba

Architectural

Mechanisms

Metadata

Raw Storage

Case Study (1)


Korea Institute of Science and Technology (KISTI)


Dept. of Computer Intelligence Research

8

Case Study (2)


Architecture of InSciTe Adaptive Service

9

Case Study (3)


Semantic Analysis


Text Data to Ontology


10

Case Study (4)


Semantic Analysis


Ontology Schema



11

Case
Study (5)


Semantic Analysis


Example
of Semantic Analysis


12

Case Study (6)


InSciTe
Service Functions


(Hybrid Vehicle)

13

Technology
Navigation

Technology

Trend

Core Element

Technology

Convergence
Technology

Agent Level

Agent Partner

Integrated

Roadmap

Report

Case
Study (7)


In 2013, About 10 Billion triples from diverse sites will be extracted

14

Sites

The number of Count

Freebase

1,015,762,951

Yago

224,949,079

DBPedia

449,383,705

DBLP

81,986,947

baseKB

147,549,529

Etc

(
WhoisWho,NYTimes,LinkedObervedData
,…)

2,296,838,760

Total

4,216,470,971

Case Study (8)


In 2013, System Architecture of InSciTe Adaptive Service

15


Procedure for developing a
reference model for
Big
Data

4. Deriving use
-
cases for applying the Big Data

3. Defining a concept model / a reference model /

a framework for Big Data

2. Establishing visions and strategies for achieving the goal
of Big Data

1. Eliciting requirements and analyzing the environment of
Big Data

16

We are here

A lifecycle of Big Data

17

1.

2
.

3.

4.


Collection/Identification


Repository/Registry


Semantic
Intellectualization


Integration


Data
Curation


Data Scientist


Data Engineer

Data

Insight

Action

Decision


Workflow


Data Quality

Big Data


Analytics / Prediction


Visualization

Reference Model for Big Data


A Reference Model for Big Data

18

Data Layer

Platform Layer

Data Semantic Intellectualization

Data Integration

Data Quality
Management

Big Data

Management

Data
Curation

Service Layer

Analysis & Prediction

Security

Data
Visualization

Service Support

Layer

Workflow
Management

Interface

Data Collection

Data Identification

(Data Mining & Metadata Extraction)

Data Registry

Data Repository

Interface

Interface

Reference Model for
Big Data


A Reference Model for Big Data

19

Data Layer

Platform Layer

Data Semantic Intellectualization

Data Integration

Data Quality
Management

Big Data

Management

Data
Curation

Service Layer

Analysis & Prediction

Security

Data
Visualization

Service Support

Layer

Workflow
Management

Interface

Data Collection

Data Identification

(Data Mining & Metadata Extraction)

Data Registry

Data Repository

Interface

Interface

9075

13249

11179

19763

???

Conclusions


Summary


Analyzing the circumstance of Big Data


Building a framework for Big Data


Define detail procedure to create the Big Data



Discussion


Possible suggestions


New Working Group for the reference model of Big Data


New Work Items could be derived from the model


New Study Group



Future work


Discussion
of the concept of NWI


2013. 11. Interim meetings


Propose extended the reference model of Big Data (NWI)


2014. 5 Plenary meeting




20