How To Make Big Data Work? - standard.no JTC1/E3... · 11/14/2016 3 Wo Chang, JTC 1/WG 9 Convener...
Transcript of How To Make Big Data Work? - standard.no JTC1/E3... · 11/14/2016 3 Wo Chang, JTC 1/WG 9 Convener...
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11/14/2016 1Digital Norway: Standard Big Data Interoperable Ecosystem, November 9, 2016Wo Chang, JTC 1/WG 9 Convener 1
How To Make Big Data Work?
Approaches to Establish Interoperable Ecosystem
Wo Chang
JTC 1/WG 9 on Big Data, Convenor
National Institute of Standards and Technology, USA
November 9, 2016
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11/14/2016 2Digital Norway: Standard Big Data Interoperable Ecosystem, November 9, 2016Wo Chang, JTC 1/WG 9 Convener 2
How to Make Big Data Work?
Enterprise Computing Perspective
Computing Infrastructure Trend Perspective
Big Data Architecture Computing Stack Perspective
Big Data Architecture Analytics Stack Perspective
Big Data Architecture Integration Perspective
Approaches to Establish Interoperable Ecosystem
ISO/IEC JTC 1 Study Group on Big Data Report (year 2014)
ISO/IEC JTC 1/WG 9 Working Group on Big Data Activities (2015 – now)
Standard Big Data Interoperable Ecosystem Roadmap
ISO/IEC JTC 1/WG 9 Working Group on Big Data – Collaborations
How Can You Help?
Agenda
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11/14/2016 3Digital Norway: Standard Big Data Interoperable Ecosystem, November 9, 2016Wo Chang, JTC 1/WG 9 Convener 3
Enterprise computing is sometimes sold to business users as an entire platform
that can be applied broadly across an organization and then further customized by
users within each area. This means the analytics, reporting, database management
and other applications are standard across the system, while the application
packages being used and the data being accessed in each area will be different. In
this sense, enterprise computing is a departure from finding single software
solutions to specific business problems, such as inventory or accounting software.
Instead, enterprise computing is intended to offer integrated solutions to these
problems.
Source: https://www.techopedia.com/definition/27854/enterprise-computing
How To Make Big Data Work: Enterprise Computing Perspective
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11/14/2016 4Digital Norway: Standard Big Data Interoperable Ecosystem, November 9, 2016Wo Chang, JTC 1/WG 9 Convener 4
Distributed
Computing
Remote Procedure Calls
(RPC)
Common Object Request Broker
Architecture (CORBA)
Grid Computing Others…
Virtualization (multicores/GPUs)
Partial Virtualization
Full Virtualization Paravirtualization Others…
Cloud Computing
Software as a Service
Platform as a Service
Infrastructure as a Service
Others…
Containerization Microservices Orchestrations Others…
How To Make Big Data Work: Computing Infrastructure Trend Perspective
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11/14/2016 5Digital Norway: Standard Big Data Interoperable Ecosystem, November 9, 2016Wo Chang, JTC 1/WG 9 Convener 5
How To Make Big Data Work: Big Data Architecture Computing Stack Perspective
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11/14/2016 6Digital Norway: Standard Big Data Interoperable Ecosystem, November 9, 2016Wo Chang, JTC 1/WG 9 Convener 6
Source: http://1.bp.blogspot.com/-PKiTQa0mrn4/T_mGb6AI3yI/AAAAAAAAA8Q/TtH7xyjQ3FA/s640/analytics+tools+landscape.bmp
How To Make Big Data Work: Big Data Architecture Analytics Stack Perspective
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11/14/2016 7Digital Norway: Standard Big Data Interoperable Ecosystem, November 9, 2016Wo Chang, JTC 1/WG 9 Convener 7
Source: http://www.ongridventures.com/wp-content/uploads/2012/10/Big-Data-Landscape.jpg
How To Make Big Data Work: Big Data Architecture Integration Perspective
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11/14/2016 8Digital Norway: Standard Big Data Interoperable Ecosystem, November 9, 2016Wo Chang, JTC 1/WG 9 Convener 8
* JTC 1 Big Data Report: http://www.iso.org/iso/big_data_report-jtc1.pdf
Summary Key Findings:
Big Data systems are difficult to construct tools and applications
that integrate data from multiple Big Data sources. The systems
should be designed with security in mind from the ground up
rather than have it emerge as an afterthought.
Identified 16 potential standardization gaps to enable Big Data
systems interoperability.
Organizational Drivers to Provide:
1. Insight: enable discovery of deeper, fresher insights from all
enterprise data resources
2. Productivity: improve efficiency, effectiveness, and decision-
making
3. Speed: facilitate more timely, agile response to business
opportunities, threats, and challenges
4. Breadth: provide a single view of diverse data resources
throughout the business chain
5. Control: support tighter security, protection, and governance of
data throughout its lifecycle
6. Scalability: improve the scale, efficiency, performance, and cost-
effectiveness of data/analytics platforms
Approach: ISO/IEC JTC 1 Study Group on Big Data Report (Year 2014)
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11/14/2016 9Digital Norway: Standard Big Data Interoperable Ecosystem, November 9, 2016Wo Chang, JTC 1/WG 9 Convener 9
Approach: ISO/IEC JTC 1 /WG 9 Working Group on Big Data (2015 – now)
140+ from 22 NBs: Australia, Austria, Brazil, Canada, China, Finland, France, Germany, India, Ireland, Italy, Japan, Korea, Luxembourg, Netherlands, Norway, Russian Federation, Spain, Singapore, Sweden, UK, US
Current Projects
• ISO/IEC 20546 Information technology – Big data – Overview and vocabulary (CD)
• ISO/IEC 20547 Information Technology – Big data Reference architecture (5 Parts)
Part 1: (TR) Framework and Application Process (2nd WD)
Part 2: (TR) Use Cases and Derived Requirements (PDTR)
Part 3: (IS) Reference Architecture (3rd WD)
Part 4: (IS) Security and Privacy Fabric (under SC 27/WG 4)
Part 5: (TR) Standards Roadmap (2nd WD)
ISO/IEC Liaisons: SC 6/WG 7, SC 27, SC 29, SC 32, SC 36, SC 38, SC 39, ISO/TC 69, ISO/TC 204, ITU-T SG13, IIC
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11/14/2016 10Digital Norway: Standard Big Data Interoperable Ecosystem, November 9, 2016Wo Chang, JTC 1/WG 9 Convener 1010
Data Sources
- Sensors
- Simulations
- Modeling
- Etc.
Data Consumers
- End users
- Repositories
- Systems
- Etc.
Data
Scientist
BDRA Interface
Resource Management/Monitoring, Analytics Libraries, etc.
BDRA Ecosystem Components
Computing
Resources
Analytics
Resources
Distributed File System Services
Infrastructure Services
Database Services
Data Types Services
Support Infrastructure
Value-added Content Services
Security and Privacy Services
Visualization & BI Services
Analytics Services
Analytics Application
Approach: Standard Big Data Interoperable Ecosystem Roadmap
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11/14/2016 11Digital Norway: Standard Big Data Interoperable Ecosystem, November 9, 2016Wo Chang, JTC 1/WG 9 Convener 11
Identify and characterize existing multimedia Big Data deployment
Identify Big Media use cases
Identify MPEG tools relevant for Big Media
ISO/IEC JTC 1/SC 29/WG 11 (MPEG) on Big Media
Create AHG between SC 29/WG11 and WG9 to
Approach: ISO/IEC JTC 1/WG 9 Collaborations
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11/14/2016 12Digital Norway: Standard Big Data Interoperable Ecosystem, November 9, 2016Wo Chang, JTC 1/WG 9 Convener 12
ISO/TC69 – Applications of Statistical Methods
Apply standard statistical methodologies (CRISP, SEMMA, etc.)
Create AHG between TC69 and WG9 to:
Explore new Big Data statistical methods
Identify use cases (healthcare fraud, live twitter feeds, etc.)
Implement use cases using best practice Big Data computing ecosystem
Document findings
Standardize new Big Data statistical methodologies
Approach: ISO/IEC JTC 1/WG 9 Collaborations
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11/14/2016 13Digital Norway: Standard Big Data Interoperable Ecosystem, November 9, 2016Wo Chang, JTC 1/WG 9 Convener 13
ISO/TC204 – Intelligent Transportation
Create AHG between TC204 and WG9 to
Review SDOs in the Big Data area particularly architecture models, semantic definitions, metadata issues and APIs
Identify “Big Data topics” needed for transport data exchange and external data sources; gather and / or generate use cases related to big data topics for ITS
Examine TC204 work that support the Big Data areas and identify the gaps to fit into the foundation / architecture currently under development by SDOs (e.g., ISO/IEC, IEEE, SAE)
Examine security, privacy, ownership, and usage issues related to Big Data ITS applications
Recommend future work items (if any) to be developed by TC204
Recommend liaisons with SDOs for which collaboration is needed
Approach: ISO/IEC JTC 1/WG 9 Collaborations
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11/14/2016 14Digital Norway: Standard Big Data Interoperable Ecosystem, November 9, 2016Wo Chang, JTC 1/WG 9 Convener 14
Join and contribute to ISO/IEC JTC 1/WG 9 Working Group on Big Data
Contribute, review and comment ISO/IEC JTC 1/WG 9 documents
Provide Big Data use cases and requirements
Make available datasets and analytic tools to public
Others…
How Can You Help?