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Detection of emerging research fronts in solar cell research
Yuya Kajikawa1-3, Shinji Fujimoto2, Yoshiyuki Takeda4,Ichiro Sakata1,2,5 and Katsumori Matsushima1
ISSI2009
1Innovation Policy Research Center (IPRC), the University of Tokyo (UT)
2Department of Technology Management for Innovation, UT3Integrated Research System for Sustainability Science (IR3S)
4Department of Project Management, Faculty of Social Systems Science, Chiba Institute of Technology
5Todai Policy Alternative Research Institute, UT
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We are drowning in the information sea.
Time
Volume of Knowledge
Information flood & New roles of leading university
Society Policy
Knowledge
National competence?Sustainable
Society?
Universities
Driving Engine for Movements
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Time
Volume of Knowledge
Detection of emerging field
Emerging
DevelopingTechnology
Market
Science
Science and Technology Roadmap
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What is a Roadmap?
“road map” is a layout of paths or routes that exists (or could exist) in some particular geographical space.
road map is used to know where we are, came from, will go.
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ITRS (International Technology Roadmap for Semiconductors) 2007 Edition
What is a S&T Roadmap?
Example 1 quantitative roadmap
Science and Technology (S&T) roadmap offers a map about a certain S&T domain to show where we are, came from, will go.
“A consensus articulation of scientifically informed vision of attractive technology futures”
~Branscomb (Former Science and Technology Adviser for U.S. President)
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PV2030
What is a S&T Roadmap?Example 2 qualitative roadmap
NEDO (New Energy and industrial technology Development Organization), JPN
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Time
Volume of Knowledge
Our Approach
Emerging
DevelopingTechnology
Product
Science
Science and Technology Roadmap
Citation Network Analysis
Case study in solar cell research.
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Data
Clustering Visualization
Citation Network Analysis
Identification of characteristics of clusters
Query: All papers in 63 journals categorized as Energy and Fuels in JCR. 152,514 papers1. Energy & Fuels (E&F)
2. Solar cell (SC) Query: solar cell* 15,600 papers
Data & Method
Period: 1970-2006
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Citation network analysis
Q = SUM((probability of the existence of a link between nodes in the cluster)-(theoretical value of the probability in random network))
∑=
−=
M
s
ss
ld
llQ
1
2
2
Modularity Q
Newman & Girvan, Phys. Rev. E (2004).
M:number of modulel: total number of linksls: number of links in module sds: total number of links of nodes in module s
Newman-Girvan method
MethodClustering
Clustering is stopped at Qmax
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Citation network analysis
Adai et al. J. Mol. Biol. (2004).
MethodVisualization Large Graph Layout (LGL)
Locally-optimized spring model
Links within the same cluster are colored with the same color.
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#1 Combustion12,128 papers, 1995.7
#2 Coal11,904 papers, 1994.1
#3 Battery8,123 papers, 1997.9
#4 Petroleum5,017 papers, 1994.5
#5 Fuel cell1,704 papers, 2002.1
#6 Wastewater1,619 papers, 1999.3
#7 Heat pump1,413 papers, 1997.3
#8 Engine1,204 papers, 1999.0
#9 Solar cell1,131 papers, 2000.6
#10 Power system813 papers, 1996.7
from 152,514 papsers(1970-2005, connected component = 53,033 papers) # Rank, Cluster name
Cluster size, Average years publication
Academic Landscape of Energy and FuelsResults & Discussions
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from 16,199papers(1959-2006, connected component = 13,682 papers)
#1 Silicon4,634 papers, 1995
#2 Compounds3481 papers, 1998
#3 Dye-sensitized2,267 papers, 2003
#4Organics1,390 papers, 2002
Academic Landscape of Solar Cell Research
# Rank, Cluster nameCluster size, Average years publication
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from 16,199papers(1959-2006, connected component = 13,682 papers)
#1 Silicon4,634 papers, 1995
#2 Compounds3481 papers, 1998
#3 Dye-sensitized2,267 papers, 2003
#4Organics1,390 papers, 2002
#1.1 a-Si1,497 papers, 1997
#1.4 Polycrystalline1,497 papers, 1997
#1.2 High-efficiency cells1,149 papers, 1997
#1.3 Modeling1,003 papers, 1985
#1.5 Limitation and modification of efficiency369 papers, 2000
#2.1 Cu(In,Ga)Se2888 papers, 2001
#2.2 CdS/CdTe873 papers, 1998
#2.3 Irradiation effects798 papers, 1993
#2.4 CuInS2316 papers, 2000
#2.5 Textured ZnO260 papers, 1999
#3.1 Photosensitizer737 papers, 2002
#3.2 Electrolyte715 papers, 2004
#3.3 Modeling498 papers, 2003#3.4 Fabrication
205 papers, 2003
#4.1 Plastic solar cell448 papers, 2004
#4.2 Heterojunction373 papers, 2002
#4.3 Cyanine328 papers, 1997
#4.4 Conjugated polymer120 papers, 2004
# Rank, Cluster nameCluster size, Average years publication
Academic Landscape of Solar Cell Research
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PV2030
Citation network analysis supporting S&T Roadmapping
NEDO (New Energy and industrial technology Development Organization), JPN
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PV2030
Citation network analysis supporting S&T Roadmapping
Plastic solar cell
Conjugated polymer
SiCompound
Electrolyte
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Result (Technology Layer) > visualization in 2008
#1, cell design, 517patents, 1991.6
#2, metal contacts, 438patents, 1991.7
Only clusters whose #patents ≧ 100 were named.
#3, battery & converter, 436patents, 1994.9
#4, panel, 368patents, 1994.9
#5, diode, 223patents, 1994.4
#6, CIS, 149patents, 1994.6
#7, solar concentrator, 104patents, 1988.7
Citation Network Analysis of Patents
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A B
C D
Exist Not Exist
Exist
Not Exist
Patents
Papers
Science-linkage
Too applied or lack of science
Chances for industry or basic research
Relationship between Science and technology
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Solar cell
battery
#4, panel#7, solar concentrator
#5, diode#2, metal contacts
#3, battery & converter
#1, cell design#6, CIS
#1, silicon#2, compounds#3, dye-sensitized#4, polymer
Paper clustersPatent clusters
Gap between Science and technology
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can be used as a tool for technological forecasting, and its feasibility is demonstrated in solar cell research.
successfully illustrated academic landscape of the energy and solar cell domains and emerging research fields there.
can detect emerging fields whose parts are not listed in the previous S&T roadmap.
can extract different research front between papers and patents.
Citation network analysis
Conclusion
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•not S&T roadmap itself but its trend•Citation bias (self citation bias, prominent paper bias, etc.)•Query dependent results (we must know what query should be used to know what we want to know its details.)
Limitation
Future works
•Data cleansing•Comparison between text-mining and link-mining.
Limitations and future works
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Development of methodology for academic overviewing and implementation of the system to assist technology roadmapping. Grant for Industrial Technology Research (NEDO)PI: Yuya Kajikawa2009-2011
Society Policy
Knowledge
Universities
Toward a university as a hub of S&T policy-making
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Thank you for your listening!
Correspondence: Yuya Kajikawa, Ph. D
Innovation Policy Research Center (IPR-CTR)
University of Tokyo, Japan
Any questions, comments, suggestions, and proposals are welcome!
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Prior role of S&T roadmap
Accelerating Innovation!Vision
Trend
Past Future
S&T roadmap
Present
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Efficient Roadmapping using Citation Network Analysis
Vision
Trend
Past Future
S&T roadmap
Present
Papers
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Domain Experts
ComputerBased
WorkshopSurveyCausal modelsScenariosDelphi
Text mining
Link mining
Methodology of S&T Roadmapping
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Information collection & analysis
Example of Expert-based Roadmapping
“T-Plan” by R. Phaal in Cambridge
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1. Developing a tool supporting roadmapping by using computer based approach.
2. Illustrating an academic landscape of solar cellresearches and emerging research fields within them to support roadmapping.
Research Purpose