Tech Mining: Concept, Methods and Applications in Science Policy & Technology Management

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1 Tech Mining: Concept, Methods and Applications in Science Policy & Technology Management Alan Porter Director of R&D, & Co-Director, Technology Policy & Assessment Center Georgia Tech

2 Agenda 1. Competitive World 2. Information Resources + Software Tools 3. Case Examples 4. Discussion: How to access and use research knowledge better?

3 SciSIP President s Science Advisor (Marburger): Science of Science Policy US National Science Foundation Program: Science of Science & Innovation Policy Empirical grounding for R&D policy: Data + Analytics + Visualizations

Innovation Challenges Radical Innovation Discontinuous change implies unfamiliar realms Increasingly science-based technologies (challenge to predict breakthroughs) Open

4 Innovation Challenges Radical Innovation Discontinuous change implies unfamiliar realms Increasingly science-based technologies (challenge to predict breakthroughs) Open Innovation Leveraging the knowledge economy Seek external R&D knowledge & collaboration Case example: 35% of Procter & Gamble s recent innovation based on major external contributions

5 The Need: A way to formulate wise ST&I Policy and Technology Management Information is key Internal R&D information + External R&D intelligence

6 The Problem Information overload

7 The Solution Access the best ST&I information resources Apply powerful Tech Mining (software) tools (e.g., TDA Thomson Data Analyzer)

8 Six information types Technical Information Science, Technology & Innovation ( ST&I ) Databases (e.g., Web of Science; CSCD, Thomson Innovation) Contextual Information Business, competition, customer, policy, popular content Databases (e.g., Thomson One) Internet Sources (e.g., Googling) Technical Expertise Internet Sources (e.g., blogs, website profiling) Business Expertise

9 How do you deal with all this information? Tech Mining Alan L. Porter and Scott W. Cunningham John Wiley & Sons Inc., 2005

10 The Tech Mining Process Tech Mining

11 13 MOT Issues 39 MOT Questions ~200 Innovation Indicators R&D Portfolio Mgt R&D Project Initiation Engr Project Initiation New Product Development Strategic Planning Track/forecast emerging or breakthrough technologies etc. What? What s hot? Fit into tech landscape? New frontiers at fringe? Drivers? Competing technologies? Likely development paths? Who? Who are available experts? Which universities or labs lead? MOT Issues, Questions, and Indicators Mapping of topic clusters within the technology 3-D trend charts for topic clusters Ratio of conference to journal papers (benchmarked) Scorecard rate-of-change metrics for topic clusters Time slices to show evolution of topical emphases Topic growth modeling (S-curve) fit & extrapolation Profile table of main players Pie chart: Company vs. Academic vs. Government publishing Spreading (or constricting) # of players by topic

12 Application Examples R&D Portfolio Management Research Evaluation Research Profiling Tracking R&D over time Research Network Analyses Monitoring Research Knowledge Flows Geo-mapping ST&I Indicators

13 NSF Proposal Assignment System: First Stage

14 Research Program Evaluation: EPA STAR Endocrine Disruptors (1 of 2 programs assessed, for NAS Committee evaluation) EPA provided reports on papers resulting from the projects (funding started in 1996) We searched databases (especially Web of Science) for research in the target domains, and for citations generally and to the EPA project papers Compared co-authoring patterns before & after the EPA funding [effect of funding on teaming] Found major disjunction only ~5% of the projectbased papers appeared in the target research domains!

15 Organizational Self-Profiling Georgia Tech For 6 years; >20,000 research abstracts from Web of Science, INSPEC, Compendex, MEDLINE Also NSF awards; research projects database Research Locator Quickly, on demand Research Profiler A unit: change over time Marriage Broker Identify capabilities to bolster a proposal Story Teller Help make the case for your capabilities and teaming (networking)

16 Case Examples Nanopatenting: Life Cycle Analyses [Simone Alencar, Adelaide Antunes, et al.] Nanopatenting search (Derwent) Combine two sources of information Patent sub-classes Text mining on uses Categorize technology targets into 3 life stages Nano raw materials Nano intermediates Nano products Use to examine organizational and national patenting emphases Identify strategic differences among US, Japan & Germany

17 Case Examples Discerning Patent Aims along the Value Chain [by Alencar, Antunes & Porter] Main IPC [# patents] H01L-Semiconductor Devices; Electric Solid State Devices Not Otherwise Provided [2870] C01B-Non-Metallic Elements; Compounds Thereof [2716] A61K-Preparations For Medical, Dental, Or Toilet Purposes [1863] B82B-Nano-Structures; Manufacture Or Treatment Thereof Chemistry [1615] Main uses description in the nanopatents Electron device Semiconductor device Solar cell carbon nanotube fuel cell catalyst Cancer (treatment, medication) Cosmetics drugs Carbon nanotube Electron device catalyst Position along the Nano Value Chain Nanointermediate Nanointermediate Nano-products Nano-raw material Nano-products Nanointermediate Nano-products Nano-products Nano-products Nano-raw material Nanointermediate Nanointermediate

18 National Benchmarking: Relative Research Emphases (WOS)

19 Biotechnology Research Institute 16 Quick Profile: 750 Articles (MEDLINE) Key Topics Breakout: - Over time (3-D plot) - Key Researchers (table) Molecular Sequence Data Models, Molecular Biodegradation, Environmental Cloning, Molecular Key Topics Top Authors Related Topics Prime Years Molecular Sequence Data[237] Cygler, Miroslaw [48]; Thomas, David Y [46]; Ni, Feng [25] Intellectual Product [237]; Amino Acid, Peptide, or Protein [225]; Laboratory Procedure [130] Models, Molecular[94] Biodegradation, Environmental[68] Cloning, Molecular[56] Cygler, Miroslaw [50]; Li, Yunge [19]; Schrag, Joseph D [18] Hawari, Jalal [31]; Greer, Charles W [18]; Halasz, Annamaria [18] Thomas, David Y [18]; Cygler, Miroslaw [10]; Lau, Peter C K [10] Intellectual Product [94]; Amino Acid, Peptide, or Protein [93]; Spatial Concept [73] Biodegradation, Environmental [68]; Organic Chemical [64]; Bacterium [48]; Hazardous or Poisonous Substance [32] Laboratory Procedure [56]; Amino Acid, Peptide, or Protein [53]; Intellectual Product [46]

20 Science Citation Index Nano Publications in Environment & Energy: By Region Regional Entities Publication Year Subject Category % since 2004 Top 5 Items EU[2185] 36% of 2185 Environmental Sciences [801]; Energy & Fuels [592]; Engineering, Chemical [512]; Water Resources [469]; Chemistry, Physical [341] USA[1528] 37% of 1528 Environmental Sciences [708]; Engineering, Environmental [377]; Energy & Fuels [369]; Engineering, Chemical [292]; Water Resources [214] China[481] 63% of 481 Environmental Sciences [242]; Energy & Fuels [175]; Chemistry, Physical [116]; Engineering, Environmental [93]; Electrochemistry [78] SE Asia Tigers[474] 52% of 474 Environmental Sciences [204]; Energy & Fuels [197]; Electrochemistry [140]; Engineering, Environmental [120]; Water Resources [104]

21 One Pagers

22 Science Overlay + Other Mapping Two base science maps Overlay various topical research sets over these Cohesion maps Network maps Collaboration maps; Common interest maps; Factor maps (term consolidation) Within TDA, so maps are fully interactive

23 Base Science Map (Science, Social Sciences, & Arts & Humanities) Based on co-citation of 244 Subject Categories by 30,261 sample of USAauthored articles in Web of Science Biomed Sci clustered into 21 Macro-disciplines Rafols/Porter, 2008 Reproductive Sci Agri Sci Geosciences Clinical Med Ecol Sci Chemistry Env Sci & Tech Health Sci Civil Engr Mtls Sci Ethical & Social Issues Soc/Psych & Rltd Cognitive Sci Math, Interdisciplinary Engr Sci Physics Literature & Arts Policy Sci Ind Engr/Mgt Sci Computer Sci

24 Synthetic Science Biology Overlay Mapping: Which research communities to engage in a Synthetic Biology workshop? Medical Tech Infectious Diseases Agri Sci Env Sci Geo Sci Clinical Med Eco Sci Biomed Sci Health Sci Ethical & Social Issues Behav Sci Math across Disciplines Chemistry Engr Sci Mtls Sci Soc/Psych Literature & Arts Physics Social Sciences Ind Engr/Mgt Sci Comp Sci Pajek

25 Nano in Social Sciences Articles Cited SCs (from SSCI + Scopus, pre-2005) Overlay on the 244 Subject Category Web of Science map (normalized to total cites) Relative Nano in Social Sciences Citation Emphases: pre-2005 Reproductive Sci Biomed Sci Agri Sci Geosciences Clinical Med Ecol Sci Env Sci & Tech Chemistry Health Sci Civil Engr Mtls Sci Cognitive Sci Ethical & Social Issues Engr Sci Soc/Psych & Rltd Math, Interdisciplinary Physics Literature & Arts Policy Sci Ind Engr/Mgt Sci Computer Sci

26 Nano in Social Sciences Articles Cited SCs (from SSCI + Scopus for ) (Rafols/Porter, Aug 31, 2008). NOTE: Enhanced research knowledge bases in the social sciences, compared to the earlier period. Relative Nano in Social Sciences Citation Emphases: Reproductive Sci Biomed Sci Agri Sci Geosciences Clinical Med Ecol Sci Chemistry Env Sci & Tech Health Sci Civil Engr Mtls Sci Ethical & Social Issues Soc/Psych & Rltd Cognitive Sci Math, Interdisciplinary Engr Sci Physics Literature & Arts Policy Sci Ind Engr/Mgt Sci Computer Sci

27 Co-citation Map of the most cited authors by 307 nano social science papers Perception Ethics Governance Visions Evolutionary Economics Science Mapping

28 Science Overlay Mapping Base Map Infectious diseases Agriculture Geoscience Clinical medicine Ecology Environ. Sci. General medicine Chemistry Biological Sciences Neurosciences Materials Sci Computer Sciences Engineering GLOBAL MAP OF SCIENCE Physics Leydesdorff&Rafols (2007, submitted) Pajek

29 Nano Sample Profile (~900 records) Agriculture Geoscience Infectious diseases Ecology Environ. Sci. General medicine Chemistry Clinical medicine Biological Sci. Engineering Neurosciences Materials Sci. Computer Sci. Physics Nanotech-related publications in the map of science (1991) Pajek

30 Nano Sample Profile (~900 records) Agriculture Geoscience Infectious diseases Ecology Environ. Sci. General medicine Chemistry Clinical medicine Biological Sci. Engineering Neurosciences Materials Sci. Computer Sci. Physics Nanotech-related publications in the map of science (2005) Pajek

31 Map of Science Quantum Dot 1995 Size (area) of nodes is proportional to: Log (1+Number of citations per category) Rafols Pajek

32 Map of Science Quantum Dot 2005 Rafols Pajek

33 Tracking Change over Time Polymer Biomaterials : fibrous structural proteins : skin (68 patents)

34 Polymer Biomaterials : fibrous structural proteins : skin (470 patents)

35 Geo-coded Mapping Georgia Tech TPAC / CNS-ASU Analysis of SCI Publications; refined nano definition; results subject to revision

36 Tech Mining for ST&I Indicators Construction: Sao Paulo & Brazil [Leandro Faria et al., UFSC]

38 An Increasingly Competitive World: Georgia Tech High Tech Indicators point to China ~#1 Change in Competitiveness China Japan United States 70 Germany Technological Standing Singapore South Korea 30 Malaysia Taiwan Ireland Venezuela Philippines Indonesia Mexico Thailand Argentina Hungary Brazil Czech Rep. India Poland Israel Note: Coverage for Venezuela added 1996 Poland added in 1996 Ireland added 1999 Israel added in 1999 Czech Republic added in INPUT-Average

39 Aged Nano Citations in 2000 and 2004 relative to Nano Articles (1 st Author)

40 Summing Up & Looking Ahead Mine field-structured text like data for patterns! Using TDA + other software Patterns speak to ST&I policy intelligence: benchmarking, trends, assessing technology maturation, etc. Answer who, what, where & when questions for policy decision processes [Generate One-Pagers ] Aim to standardize questions & answers Then semi-automate the analytical processes: QTIP Quick Technology Intelligence Process

41 Resources Thomson Reuters Information Thomson Data Analyzer //scientific.thomsonreuters.com/products/tda/ Tech Mining by Alan Porter and Scott Cunningham, Wiley, Chesbrough, H. W. (2003), Open Innovation The New Imperative for Creating and Profiting from Technology, Harvard Business School Press. "Connect and Develop: Inside Procter & Gamble's New Model for Innovation," Harvard Business Review, Vol. 84, No. 3, March 2006,

An Open Innovation Machine Through Rapid Technology Intelligence Processes

An Open Innovation Machine Through Rapid Technology Intelligence Processes Paul Frey President Nils Newman Director, New Business Development Most innovations fail. And companies that don t innovate die.