To see full paper -> http://ieeexplore.ieee.org/document/7425984/ Open innovation has been a paradigm for organizations to enhance innovation activities and create out of knowledge and expertise. Traditional open innovation model focuses on the use of external sources to develop product and services and reduce costs in terms of business strategy. To leverage flexibility of open innovation model, crowdsourcing-based idea platform concepts have emerged to cooperate, co-evolve in business ecosystem to collect ideas and convert them into innovative solutions. Crowdsourcing-based idea platform have specific limitations in idea selection and transformation as it costs lots of time and energy by building and exploiting big data framework. By applying linked data to crowdsourcing-based idea platform, this paper suggests improved collective intelligence-based idea platform by addressing how to cope with challenges of big data framework.

1. THANK YOU
COLLECTIVE INTELLIGENCE-BASED IDEA
PLATFORM WITH LINKED DATA
HyeYoung Lee
Innopolis Foundation, South Korea
Jan. 18th, 2016
To see full paper ->
http://ieeexplore.ieee.org/document/7425984/

2. AGENDA
1. Introduction
2. Open Innovation: Idea Platform
3. Crowdsourcing
4. Linked Open Data
5. Crowdsourcing based Idea Platform with Linked Data
6. Improved Crowd based Idea Platform Model
7. Conclusion

3. Introduction
• Paradigm to utilize external ideas and innovating with partners by sharing
risk and incentives
Open Innovation
• By utilizing ontology technique and incorporating idea
structuration, ideas can transform into rich knowledge
and value by crowdsourcing
Idea Selection &
Transformation
Traditional open innovation
One Flow
Crowdsourcing –based Idea Platform
Interactive Flow-Multitude Sources

4. Open Innovation: Idea Platform
• Traditional Open Innovation VS
• Crowdsourcing-based Open Innovation
Open Innovation
1. Goal achievement
2. Incubation
3. Crowd Participation
Idea Platform Types
Interactive
Communication

5. Crowdsourcing
Regulation Confidentiality
Structure Operation
Control
Risks
Crowdsourcing Risks
User-centered research and open
innovation model to provide
|
Co-creation
|
Exploration
|
Experimentation and evaluation within a
public-private-people partnership
Living Labs

6. Linked Open Data
• Data can be exposed, shared and connected explicitly as structured data
Standard: http://www.w3.org/DesignIssues/LinkedData.html
Linked Data
>> To share vocabulary semantics to interpret data easier
>> To make links to verify consistencies of data sources
Linked Open Data

7. Crowdsourcing based Idea Platform
with Linked Data
Crowdsourcing based Idea Platform Process
+
Linked Data Rule Application (RDF / URI)
=
Improved Crowdsourcing based Idea Platform Model
Linked Open Data -> provides benefits for Idea Data management
for classification and representation of idea data itself

8. Improved Crowd based
Idea Platform Model
Proposed Model
1) Idea collection from citizen in unstructured format
2) Idea structuration with RDF linked data format
3) Idea preprocessing and integration
4) Interpretation and publication on open innovation database
5) Crowdsourcing mobilization

9. Conclusion
• Combined approach of crowdsourcing and linked data
• Crowdsourcing supports public ideas to transform into knowledge
• To foster participatory idea platform and activate decision making of best
idea
• Cyclic process reflected in knowledge mobilization
Conclusion
• To overcome limitations of unproven idea discovery in seeking out
potential ideas for solutions
• Additional investigation utilizing framework like big data analysis
technologies, it would improve collective intelligence-based idea
platform
Further research direction

10. THANK YOU