1. Mapping Nanotechnology Innovations and Knowledge: Global and Longitudinal Patent and Literature Analysis Hsinchun Chen, Ph.D. Director, Artificial Intelligence Lab University of Arizona Acknowledgement: National Science Foundation (NSF)

2. Mapping Nanotechnology Innovations and Knowledge Preliminary entry Roco, Mihail C., Chen, Hsinchun 2007, Approx. 300 p., Hardcover ISBN: 978-0-387-71619-0 Springer-Verlag Not yet published. Available: February 2008 About this book: Reflects recent growth in nanoscale science and engineering Analyzes an industry expected to reach $1 trillion by 2015 Includes analysis of Patent Office databases in the US, Europe and Japan

3. Knowledge Mapping

4. 4 Invisible Colleges and Knowledge Mapping Invisible college, which consists of a small group of highly productive and networked scientists and scholars, is believed to be responsible for growth of scientific knowledge (Crane, 1972). “Knowledge Mapping” or “Science Mapping” techniques, based on content analysis, citation network analysis, and information visualization, has become an active area of research that helps reveal such an inter-connected, invisible college or network of scholars and their seminal publications and ideas (Chen, 2003).

5. 5 Online Resources for Knowledge Mapping Abstracts & Indexes: MEDLINE (medicine), TOXLINE (toxicology), BIOSIS (biology), COMPENDEX (engineering and technology), ERIC (education), etc. Commercial full-text journal articles and digital libraries: Thomson Scientific Web of Science, ACM Digital Library, The IEEE Computer Society Digital Library, etc. Free full-text articles and e-prints: Free Medical Journals, HighWire Press, arXiv.org service, etc. Citation indexing systems and services: Thomson Science Citation Index, Google Scholar, CiteSeer, etc. Electronic Theses and Dissertations (ETD): Networked Digital Library of Theses and Dissertations (NDLTD), etc. Patents: USPTO, EPO, JPO, etc. Business and industry articles and reports: Forrester, IDC, and Gartner, etc. Web sites, forums, blogs, social networking sites, etc.

6. 6 Units of Analysis and Representations Authors or inventors Publications and publication outlets Institutions Countries or regions Subject and topic areas Timeline

7. 7 Knowledge Mapping: Analysis Framework Text Mining –Natural Language Processing: automatic indexing, information extraction –Content Analysis: clustering algorithms, self-organizing map (SOM), multi-dimensional scaling (MDS), principal component analysis (PCA), co-word analysis, PathFinder network (PFNET) Network Analysis –Social Network Analysis: subgroup detection, discovery of pattern of interaction, roles of individuals –Complex Networks: network models, topological properties, evolving networks Information Visualization –Information Representations: 1D, 2D 3D, multi-dimensional, tree, network, temporal –User-interface Interaction: overview + detail, focus + context

8. 8 Co-authorship Network (Krempel)

9. 9 SOM-based Cancer Map (Chen et al.)

10. 10 ThemeView (PNL)

11. 11 Galaxy visualization (PNL)

12. Mapping Nanotechnology Innovations and Knowledge

13. 13 Nanotechnology Commercialization Timeline

14. 14 Worldwide Nanotechnology Market

15. 15 Nanotechnology –A fundamental technology. –Critical for a nation’s technological competence. –Revolutionizes a wide range of application domains. In recent years, nanotechnology research experienced rapid growth: –(Huang et al., 2003) used patent publications from the USPTO for the longitudinal analysis of this field. –Many communities have an interest in assessing the R&D status of nanotechnology.

16. 16 Assessing Nanotechnology Research Status Patent analysis –We developed a framework (Huang et al., 2003) to systematically assess nanotechnology’s research status using: Bibliometric analysis, Content map analysis, and Citation network analysis. Literature analysis –Bibliometric analysis is the major approach (Braun et al., 1997); other methods are seldom used in this kind of study. –There is a lack of research which conduct longitudinal analysis of nanotechnology's research status in recent years using scientific literature.

17. USPTO, EPO, and JPO Patent Analysis (Nature Nanotechnology, 2008, forthcoming)

18. 18 Research Objectives Assess the nanotechnology development status represented by USPTO, EPO, and JPO patents. Compare and contrast the differences in the nanotechnology patents in the three repositories. Background and Research Objectives

19. 19 Patent parsing Research Design Data acquisition USPTO database USPTO database Research status analysis Topic coverage Collected by keywords Content map Citation Network Patent publication Patent importance/ strength of a repository Patent importance/ strength of a repository Number of patents Average number of cites EPO database EPO database JPO database JPO database Knowledge diffusion Collected by keywords JPO dataset EPO dataset USPTO dataset Patent status checking EPO+JPO patent JPO patent Patent status We developed a framework to assess the R&D status of a a science and engineering domain based on the patents in the three repositories: USPTO, EPO, and JPO. Research Design

20. 20 Data: USPTO Patents Comparing with "full-text" search and "title-claims" search, “title- abstract” search provides fewer search results but with higher accuracy. From “title-abstract” search: –5,363 unique patents were collected. –Submitted by 2,196 assignee institutions, 8,405 inventors, and 46 countries. Dataset

21. 21 Data: USPTO Patents (cont.) Top 20 nanotechnology patent assignees (with average patent age) and countries based on “title-abstract” search of patents published from 1976 to 2004 Dataset

22. 22 Data: EPO Patents (cont.) Top 20 nanotechnology patent assignees (with average patent age) and countries based on “title-abstract” search of patents published from 1978 to 2004 Dataset

23. 23 Data: JPO Patents (cont.) Top 20 nanotechnology patent assignees based on “title- abstract” search of patents published from 1976 to 2004 Dataset

24. 24 Data: USPTO, EPO, and JPO Patents Dataset The numbers of nanotechnology patents published in USPTO, EPO and JPO by year (log scale)

25. 25 Basic Analysis- USPTO Patents by Country Top 20 nanotechnology patent assignee countries in USPTO (“title-abstract” search) and their patents by year, 1976-2004 (log scale) Basic Bibliographic Analysis

26. 26 Basic Analysis- EPO Patents by Country Top 20 nanotechnology patent assignee countries in EPO (“title-abstract” search) and their patents by year, 1978-2004 (log scale) Basic Bibliographic Analysis

27. 27 Basic Analysis- USPTO Patents by Country Group Assignee country group analysis by year, 1976-2004 (“title-abstract” search) (log scale) Basic Bibliographic Analysis

28. 28 Basic Analysis- EPO Patents by Country Group Assignee country group analysis by year, 1978-2004 (“title-abstract” search) (log scale) Basic Bibliographic Analysis

29. 29 Content Map Analysis (USPTO) USPTO Content Map (1976-1989) (“title-abstract” search) Content Map Analysis

30. 30 Content Map Analysis (USPTO) USPTO Content Map (1990-1999) (“title-abstract” search) USPTO Content Map (2000-2004) (“title-abstract” search) Content Map Analysis 4.18 5.39 6.03 6.51 6.93 7.33 7.75 8.23 8.86 9.32 10.07 NEW REGION -0.80 0.41 1.05 1.53 1.95 2.35 2.77 3.25 3.88 4.34 5.09 NEW REGION

31. 31 Findings –Content Map (USPTO) From 1976 to 1989, the major research topics of USPTO nanotechnology patents included: “carbon atoms,” “optical fibers,” and “thin films.” From 1990 to 1999, several new research topics appeared from 1990 to 1999, including: “aqueous solutions,” “composite materials,” “laser beams,” “nucleic acids,” “optical waveguide,” “organic colvents,” “reverse osmosis,” “self-assembled monolayer,” “semiconductor substrate,” “silicon carbide,” and “substrate surfaces.” From 2000 to 2004, the numbers of patents related to several topics had increased significantly, such as “aqueous solutions,” “composite materials,” “carbon nanotubes,” “nucleic acids,” “self-assembled monolayer,” and “thin films.” Some new topics also became major research topics in this time period, such as “atomic force microscope,” “clay materials,” “dielectric layers,” “nanocomposite materials,” “naphtha stream,” “polymeric materials,” and “semiconductor devices.” Content Map Analysis

32. 32 Citation Network Analysis- USPTO Countries Citation Network Analysis

33. 33 Citation Network Analysis- EPO Countries Citation Network Analysis

34. 34 Findings – Country Citation Network In the USPTO dataset, the United States is the most significant citation center on the network. Japan, Republic of Korea, the United Kingdom, China (Taiwan) and Germany are the secondary citation centers and constructed a cluster with close citations. In the EPO dataset, the United States, France, Japan, Germany, and the United Kingdom are large citation centers and construct a citation cluster on the network. In both repositories, the countries have close citation relationships. In EPO most assignee countries have more than one citing/cited country. In USPTO several countries only have citation relationship with the United States. Many of the countries that only had citations with the United States were relatively new in the nanotechnology domain. Citation Network Analysis

35. Thomson SCI Literature Analysis

36. 36 Research Methodology (cont.) Use content maps to study the active research topics and their relations in different time spans. –Technology topics are extracted from the papers’ abstracts using the Arizona Noun Phraser (Tolle and Chen, 2000). The topics are organized by the multi-level self-organization map algorithm (Chen et al., 1996; Ong et al., 2005), which positions similar topics closer together according to their co-occurrence patterns. Documents Topic Similarity Keyword Extraction Topics Visualization Arizona Noun Phraser Topic Relation Analysis SOM Algorithm Research Methodology

37. 37 Research Methodology (cont.) Use citation network analysis to study knowledge spillover patterns between countries/regions and between institutions. –Using network topological measures to infer the global characteristics of knowledge spillover in the nanotechnology field (Li et al., forthcoming). –Visualize the core citation network and identify the important patterns in the network: citations. Documents Country Citation Network Citation Extraction Paper Citation Relationships Paper Citation Relationships Topological Analysis Topological Analysis Citation Aggregation Institution Citation Network Institution Citation Network Visualization Core Network Extraction Research Methodology

38. 38 Data: Thomson SCI Nanotechnology Papers, 1976-2004 Paper collections –213,847 papers –120,687 first authors –24,468 institutions –4,175 journals/conferences –156 countries/regions –The identifiers of the papers that cited or were cited by the nanotechnology papers are also retrieved. Dataset

39. 39 Bibliographic Analysis I. Bibliographic Analysis

40. 40 Papers by Country/Region Top 20 countries/regions based on number of papers published from 1976 to 2004 (log scale) I. Bibliographic Analysis

41. 41 Top countries/regions (without USA) based on number of papers published from 1976 to 2004 (normal scale) Papers by Country/Region (cont.) I. Bibliographic Analysis

42. 42 Papers by Institution Top 20 institutions based on number of papers published from 1976 to 2004 (normal scale) I. Bibliographic Analysis

43. 43 Data: Productive Countries Top 20 countries/regions based on number of papers published from 1976 to 2004 Dataset

44. 44 Data: Productive Institutions Top 20 institutions based on number of papers published from 1976 to 2004 Dataset

45. 45 Content Map (1990-1999) II. Content Map Analysis

46. 46 Findings Nanotechnology papers published between 1990 and 1999 covered the topics related to –Tools E.g., “Scanning Tunneling Microscope,” “Transmission Electron Microscopy,” “Atomic Force Microscope,” and so forth. –Physical phenomena E.g., “Quantum Dots,” “Single Crystals,” “Self- Assembled Monolayers,” “Nanomolar Concentrations,” “Porous Silicon,” “Surface Morphologies,” and so forth. –Experiment environments E.g., “Electric Fields,” “Room Temperatures,” “X-Ray Diffraction,” “Temperature Dependences,” “Activation Energies,” and so forth. II. Content Map Analysis

47. 47 Content Map (2000-2004) -1.51 -0.30 0.33 0.81 1.23 1.63 2.05 2.53 3.16 3.62 4.37 NEW REGION II. Content Map Analysis

48. 48 Findings Nanotechnology papers published between 2000 and 2004 also covered the topics related to tools (e.g., “Scanning Tunneling Microscopy,” “Transmission Electron Microscopy,” “Atomic Force Microscope”), physical phenomena (e.g., “Quantum Dots,” “Self- Assembled Monolayers”), and experiment environments (e.g., “Aqueous Solution,” “X-Ray Diffraction”). –The topics on experiment environments became less active compared with the other two kinds of topics. There were some new topics like: “X-Ray Photoelectron Spectroscopy,” “Single-Wall Carbon Nanotubes,” “Carbon Nanotubes,” “Monte Carlo Simulations,” and “Chemical Vapor Deposition.” II. Content Map Analysis

49. 49 Country Citation Network (1976-2004) The country citation network (1976-2004) consists of –66 countries, –348 inter-country citation relations, and –9 self-citation relations. The country citation network contains one component. –Different countries’ knowledge influences each other directly or indirectly. Much larger clustering coefficient (0.693) than the random network (0.162). –Some countries tend to form communities from the paper citation perspective. l: average path length2.019 l rand : average path length of a random network1.779 C: clustering coefficient0.693 C rand : clustering coefficient of a random network0.162 D: network diameter4 N C : number of components1 Node C : number of nodes in the largest component 66 (100%) Link C : number of links in the largest component348(100%) III. Citation Network Analysis

50. 50 Country Citation Network (1976-2004) III. Citation Network Analysis

51. 51 Institution Citation Network Analysis The institution citation network consists of –1,237 institutions, –3,075 inter-institution citation relations, and –7 self-citation relations. The institution citation network consists of 20 components. The giant component contains 1,185 (95.8%) institutions and 3,041 (98.9%) relations. –Most institutions interact with others directly or indirectly. Smaller average path length (4.050) than the random network (4.440). –Knowledge can very easily transfer between institutions. Much larger clustering coefficient (0.069) than the random network (0.004). –Research institutions have a very high tendency to form citation clusters. l: average path length4.050 l rand : average path length of a random network4.440 C: clustering coefficient0.069 C rand : clustering coefficient of a random network0.004 D: network diameter11 N C : number of components2020 Node C : number of nodes in the largest component 1,185 (95.8%) Link C : number of links in the largest component3,041 (98.9%) III. Citation Network Analysis

52. 52 Institution Citation Network (1976-2004) III. Citation Network Analysis

53. India Nano Story

54. 54 Papers by Year The number of papers published from 1976 to 2007.

55. 55 Essential Institutions Top 10 institutions based on number of papers published from 1976 to 2004.

56. 56 Most Productive Researchers Top 10 first authors based on number of papers published from 1976 to 2004.

57. 57 Most Cited Researchers Top 10 first authors according to the number of cites received from all papers in SCI from 1976 to 2004.

58. The Nano Mapper System

59. 59 System Demo: Patent Number Search

60. 60 Search Results: Patent Detail

61. 61 System Demo: Patent Quick Search

62. 62 Search Results: Patent List

63. 63 System Demo: Patent Advanced Search

64. 64 System Demo: Patent Overall Statistics

65. 65 System Demo: Patent Trend Analysis

66. 66 System Demo: Patent Trend Analysis (cont.)

67. 67 System Demo: Citation Network Analysis

68. 68 System Demo: Content Map Analysis

69. 69 Take-home Messages Studying international competitive landscape: knowledge and innovations The power of the automated knowledge mapping approach Prioritized national nanotechnology research programs and directions Turning academic research (literature) into patents and commercial products Commercialization directions and priorities

70. Hisinchun Chen, Ph.D. hchen@eller.arizona.edu Artificial Intelligence Lab University of Arizona http://ai.arizona.edu hchen@eller.arizona.edu Hisinchun Chen, Ph.D. hchen@eller.arizona.edu Artificial Intelligence Lab University of Arizona http://ai.arizona.edu hchen@eller.arizona.edu