Where is Nano Going

1
Where is Nano Going?
Explorations in Research and Innovation Systems
Assessment

• Philip Shapira and Alan Porter
• Center for Nanotechnology in Society (CNS-ASU)
• Program in Research and Innovation Systems
  Analysis (RTTA 1/RISA 1)
• Technology Policy and Assessment Center
• School of Public Policy, Georgia Institute of
  Technology
• Atlanta, GA 30332-0345, USA
• Prepared for Presentation at National Science
  Foundation, First Year Review of the Center for
  Nanotechnology in Society (CNS-ASU), Arizona
  State University, Tempe, AZ, August 24, 2006.
• Acknowledgements This presentation draws on
  research directed by Philip Shapira, Alan Porter,
  and Jan Youtie, with research assistance provided
  by David J. Schoeneck, Li Tang, Sharyn Finney,
  and Luke McCloud. This research was undertaken at
  Georgia Tech through the Center for
  Nanotechnology in Society (CNS-ASU), supported by
  the National Science Foundation (Award No.
  0531194).

2
Where is Nano Going?

• OVERVIEW
• Review RTTA 1 / RISA 1 Objectives
• Refining Nano Search Terms
• Year 1 report
• Early Descriptive Results
• Research Directions
• Years 2-4
• Reference Refining Search Terms for
  NanoTechnology Briefing Paper (A. Porter, Y.
  Youtie, P. Shapira, August 2006)

3
RTTA Program 1Research Innovation Systems
Analysis (RISA)
4
RISA 1 Research Program Assessment Key Questions

• What?
• Core nano thrusts (in theme domains) emergent
  sub-topics interconnections
• Frontier activity assessment 1) hot topics
  those with high rates of increase 2) new
  topics concepts/tools first identified in the
  past year
• Emerging applications (esp. in privacy, human
  identity)
• Who?
• Leading research institutions
• Leading researchers
• Leading industrial companies
• Emergence of knowledge networks and clusters
• Where?
• Regional concentrations in the US
• International comparisons US vs. China, Japan,
  EU publishing patenting
• When?
• Assessments and projections topical emphases,
  networks, clusters, industrial outcomes as
  take-offs for discussion and scenario-building
• How?
• Datamining (e.g. bibliometric and patent
  analyses) using VantagePoint
• Other secondary data sources (national, regional,
  industrial, corporate)
• Selected primary sources (interviews, expert
  consultation)
• RISA analysis, networking and linkages, clusters,
  modeling, discontinuities

5
RISA 1 Research Program Assessment Data Sources
Research Exploration (Publications) (Organization
s)
Early Innovation (Patents) (Venture
Cap) (SBIR) (Start-Ups) (Incumbents)
Visions and Roadmaps (Reports) (Scenarios) (Soc
Sci Pubs) (Sci-Fi Lit)
Expert Consultation
Assessment
Current / Near-Term Applications
Potential Mid-Term Applications
Privacy and Security Human Identity
6
What is Nanotechnology?

• Science, engineering and technology of
  understanding and controlling matter at c. 1-100
  nm scale
• To develop materials, devices, and systems that
  have novel properties and functions due to
  nanoscale
• Argued to be a transformative general technology
  with fundamental technological, economic and
  societal consequences
• 1 nm 1 billionth of a meter

7
Refining Nanotechnology Search Parameters

• Bibliometric robustness
• Detailed and specific search terms required
• Usable across different data sets
• Reproducible and updatable
• Real time feed into RTTA processes
• Multi-purpose
• Probe nano-research activity patterns zoom in
  on given topics or players
• Identify topical networks (connections)
• Forecast plausible nanotechnology development
  paths
• Point to possible applications
• Identify potential impacts

8
Preparatory Work

• Fall 2005
• Explored alternative approaches
• Reviewed CREA, PFI (NCSU), Kostoff, EU PRIME
  search strategies, etc.
• Explored relations with Nanobank
• Tapping rich data resources
• But limited and delayed accessibility
• Also using a different, bootstrap search approach
  
• Decide to use composite Boolean search
• Search for term occurrence in key fields
• Sometimes modify to require co-occurrence with
  nano-related terms
• Use in conjunction with index (classification)
  codes especially for patents

9
Steps in Refining Nano Search Terms

• Developed a pilot field scope
• drawing upon and combining search terms and
  insights from prior efforts to define
  nanotechnology search terms
• Asked multiple nanotechnology experts to review
• received recommendations to delete, modify, add,
  or confirm terms
• Further evaluated candidate terms
• by testing and assessing results against the
  publication and patent data.

10
Nano Search Timeline

• 2006
• Jan March Developed field scope search terms
  (based on review of earlier work)
• Feb Apr Asked for expert input. 19
  Nanoscientists substantively reviewed our
  proposed search algorithm
• April Revised finalized algorithm
• May -- August Search Download
• July Present Clean Consolidate

11
Nanotechnology Research Foci Key Concepts
12
Which Terms to Include?

• Nanoscientists review and our explorations
  generated many candidate terms
• NSE terminology is dynamic tracking change is
  interesting in its own right
• Search on a candidate term
• Substantial hit rate or not?
• Examine sample of NOT metasearch records
• Screen for co-occurrence with nano-related
  keywords Instant tallies in EI Village
• Browse sample of snippets criterion of 70
  relevance
• Option to download into VantagePoint and examine
  coverage
• Decide 1) include 2) include, but restrict to
  co-occur with inclusive Molecular Environment
  terms 3) include, if co-occur with restrictive
  Molecular Environment terms or 4) exclude.

13
(No Transcript)
14
Multi-stepSearch and Cleaning Process
Search terms to include for data download
Develop thesauri Geo IDs
Data download
Search terms to exclude in data mining
Raw data
Cleaning and consolidation
Cleaned data
15
Which Databases to Search?

• Web of Science Science Citation IndexISI Web
  of Knowledge, accessed via Georgia Tech
  Electronic Library
• EI Compendex and INSPECEngineering Village 2
  website via Georgia Tech Electronic Library
  access
• EKMS searched MicroPatent, INPADOC, and their
  proprietary U.S. Patent Citation database

16
Exclusions in Data Cleaning

• In VantagePoint, remove duplicates and records
  that appear likely not to reflect NSE
• Exclude any that contain certain terms, e.g.
  nplankton, nanoAlga, Nanofauna, nano2 (e.g.,
  NaNO2), nanoa_, etc.
• Exclude records that contain ONLY one of these
  terms (and no other nano terms), e.g.
  nanometer, nanosecond, nanomolar, nanogram,
  nanoliter

17
Searching Issues

• Search term forms and term length limits vary by
  search engine
• Assess coverage for each database re wildcards,
  hyphenation, spaces, etc.
• Desired patent data requires combination of
  results from 4 sources Micropatent INPADOC
  Micropatent-INPADOC XML (for addresses) EKMS
  Patent Citations (by and to)

18
Search Performance

• Recall High
• Encompassing NSE Search Algorithm
• Given that bounds on NSE are quite permeable, no
  right answer
• Precision Good
• We apply post-search duplicate removal
  exclusions
• That makes comparison of algorithms directly in
  the database search engines impossible

19
Search Results 1990-2006 (partial year)

• Research Publications Web of Science Science
  Citation Index (SCI)
• 420,774 article abstracts
• Representing 2.7 of SCI over the period and
  4.1 of SCI for this 2005-06 period
• Patents Combined MicroPatent INPADOC
  International coverage
• USPTO, EPO (EU), JPO (Japan), WIPO (World
  Intellectual Property Office), Germany, Great
  Britain, France INPADOC to cover about 70
  countries.
• 61,174 discrete patents (one per patent family)

20
Nano Research Publications, 1990-2006 (August),
from Web of Science Science Citation
Indexfull-year normalized 2006 data would be
55,800
21
(No Transcript)
22
Ongoing Steps

• Data are available in VantagePoint for mining
  3 file variations lite, enhanced lite, and full
  abstract records (including SCI Cited References)
• Clean the data consolidate name variations of
  people and of organizations
• Perform duplicate removal exclusions on INSPEC
  and Compendex data
• Merge INSPEC, Compendex, and SCI data
• Process Patent Citation data

23
Possible Extensions

• Search business data resources for corporate
  information (new firms, incumbent activities)
• Search social sciences research about nano

24
Research Directions (Years 2)

• Drivers and characteristics of nano development
• Mapping leading thrusts, hot topics, key
  institutions
• Convergence and GPT
• Extension of data sources (esp. to firm-data)
• Emergence of nano districts
• Which regional locations will lead in nano
  development and why? And in which fields?
• Potential nano applications
• CNS-ASU themes (FPS HIEB)
• Triangulate with scenario activities

25
Nano publications 1990-2006 (estimated)
Georgia Tech TPAC / CNS-ASU Analysis of SCI
Publications refined nano definition results
subject to revision
26
Nano Districts
Georgia Tech TPAC / CNS-ASU Analysis of SCI
Publications refined nano definition results
subject to revision
27
Global Nano Patent (Awards)1990 2006
(estimated) Micropatents INPADOC data
Georgia Tech TPAC / CNS-ASU patent analysis
refined nano definition results subject to
revision
28
CNS-ASU _at_ Georgia Tech RISA 1

• Senior Team Members
• Philip Shapira
• Alan Porter
• Jan Youtie
• Maurizio Iiacopetta
• Junior Team Members (Current)
• Dave Schoeneck
• Li Tang (GRA)
• Jue Wang (GRA)
• Tanner Osman (GRA)
• 2 undergrads Sharyn Finney, Luke McCloud

29
Research Collaborations

• Drivers and characteristics of nano development
• CNS-ASU / RTTAs
• CNS-UCSB (C. Newfield)
• UCLA/Harvard/NBER (Stu Graham)
• Emergence of nano districts
• CNS-ASU RTTA 1 / RISA 3 Workforce
• EU PRIME Nanodistricts
• Potential nano applications
• CNS-ASU scenario, thematic, and other groups