An Analysis of References from US Patents to NIST ......The analysis is based primarily on locating technical outputs – such as patents, scientific journal articles, standards documents,

NIST GCR 16-009

An Analysis of References from US

Patents to NIST-Supported

Technical Outputs

Anthony Breitzman Sr, Ph.D.

Patrick Thomas, Ph.D.

1790 Analytics, LLC

This publication is available free of charge from:

http://dx.doi.org/10.6028/NIST.GCR.16-009

NIST GCR 16-009

Prepared for

U.S. Department of Commerce

Economic Analysis Office

National Institute of Standards and

Technology Gaithersburg, MD 20899

By

Anthony Breitzman, Sr. Ph.D.

Patrick Thomas, Ph.D.

1790 Analytics, LLC

This publication is available free of charge from:

http://dx.doi.org/10.6028/NIST.GCR.16-009

September 2016

U.S. Department of Commerce

Penny Pritzker, Secretary

National Institute of Standards and Technology

Willie May, Under Secretary of Commerce for Standards and Technology and Director

An Analysis of References from US

Patents to NIST-Supported

Technical Outputs

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Disclaimer

This publication was produced as part of contract SB1341-14-SE-0422with the National

Institute of Standards and Technology. The contents of this publication do not necessarily

reflect the views or policies of the National Institute of Standards and Technology or the

US Government.

Table of Contents

I. Introduction .................................................................................................................. 1

II. Project Design ............................................................................................................. 1

III. Methodology .............................................................................................................. 3

Citing Document Set: Granted US Patents ..................................................................... 3

Cited Document Set: NIST Technical Outputs ............................................................... 4

Cited Document Category 1: Patents Assigned to NIST ............................................. 4

Cited Document Category 2: Patents with a NIST Government Interest .................... 4

Cited Document Category 3: NIST-Funded Peer Reviewed Papers ........................... 5

Cited Document Categories 4-11: NIST Grey Literature ............................................ 7

Summary of Document Sets .......................................................................................... 11

IV. Results ....................................................................................................................... 11

Organization-Level Results ........................................................................................... 11

Overall NIST Citation Counts ................................................................................... 11

Trends in NIST Citation Counts ................................................................................ 12

Benchmarking NIST Citation Counts ........................................................................ 13

Patents Citing NIST Technical Outputs .................................................................... 17

Document-Level Results ............................................................................................... 19

V. Conclusions ................................................................................................................ 22

VI. Appendix: Figures and Tables ................................................................................ 24

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Executive Summary

This report outlines the results of an analysis – carried out by 1790 Analytics on behalf of

NIST’s Economic Analysis Office – designed to evaluate the technological impact of technical

outputs associated with NIST.

The analysis is based primarily on locating technical outputs – such as patents, scientific

journal articles, standards documents, conferences papers, and other forms of grey literature –

associated with NIST funding. We then trace forward from these technical outputs to determine

how they have influenced subsequent technological developments, specifically those

developments described in patents assigned to all organizations.

The idea behind this analysis is that patents that reference NIST technical outputs as prior art

build in some way on these NIST outputs. By determining how frequently NIST technical

outputs have been cited by subsequent patents, it is thus possible to evaluate the extent to which

NIST funded activities have helped form the foundation for a wide range of technologies.

The main findings of this report are:

Between January 1995 and July 2015, there were a total of 34,241 citations from US

patents to NIST-supported technical outputs. This is an impressive figure, especially

given the fact that NIST had only 201 US patents assigned to it through the end of

2014. It suggests that NIST’s influence extends far beyond just its own patented

inventions, and that the agency’s activities help form the foundation for technological

developments made by a wide range of other organizations.

We divided the citations from US patents to NIST into four broad categories, based on

the type of NIST technical output cited. The four categories are: patents assigned to

NIST; patents in which NIST has a government interest; peer reviewed papers funded

by NIST; and NIST grey literature.

14,538 (43%) of the 34,241 citations from US patents to NIST outputs are to peer

reviewed papers authored by NIST-supported researchers; 9,062 (26%) are to patents

in which NIST has a government interest (i.e. patents resulting from research funded

by NIST in an external organization); and 2,173 (6%) are to patents assigned to NIST.

The remaining 24% of citations from US patents to NIST technical outputs are to NIST

grey literature. The largest of these grey literature categories is software, standard

reference databases and algorithms, which accounts for 2,914 (8%) of citations from

US patents to NIST documents. Other grey literature categories that receive significant

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numbers of citations are Official NIST Publications (1,671 citations, or 5%);

Educational Networking (1,267 citations, 4%); and Other NIST Publications (1,740

citations, 5%). The final four grey literature categories together account for only 2.5%

of citations from US patents to NIST documents.

In terms of trends over time, there was a more than a ten-fold increase in citations from

US patents to NIST technical outputs between 1995 and 2014.

Citations to each of the NIST document types (patents assigned to NIST; patents in

which NIST has a government interest; peer reviewed papers funded by NIST; and

NIST grey literature) all increased significantly between 1995 and 2014. The largest

increases were associated with NIST peer reviewed papers and NIST government

interest patents.

Over the same time period, the overall number of citations provided by US patents also

increased significantly. This was due to increases in the number of patents issued each

year, and also in the mean number of prior art references listed on patents. We therefore

benchmarked citations to NIST against citations to comparable document sets in order

to account for these broader changes in the citation landscape.

We benchmarked citations to NIST patents (both those assigned to NIST, and those in

which NIST has a government interest) using our quantitative, normalized patent

metrics. These metrics reveal that NIST-supported patents (especially those with a

NIST government interest) have a stronger impact, are more generally applicable, and

are more original than peer patents of the same age and technology.

The highest impact NIST-assigned patent (in terms of our normalized Citation Index

metric) is US #5,356,756, which was issued in 1994. This patent describes materials

processing for thin films, designed for use in sensors, electronic devices and sample

analysis. It has been cited as prior art by 110 subsequent patents, more than seven times

as many citations as expected for a patent of its age and technology.

The highest impact patent in which NIST has a government interest is US #7,330,404.

This patent has been cited by 127 subsequent patents since it was issued in 2008, which

is more than 40 times as many citations as expected given its age and technology. It

describes a transducer for use in optical storage (for example in disk drives), and is

assigned to Seagate Technology.

We benchmarked citations to NIST peer reviewed papers against citations from the

most prolific patenting companies to papers in journals published by the leading

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publishers. Between 2000 and 2014, citations to NIST papers from all patents increased

at a faster rate than citations from the patents of leading companies to papers in leading

journals. This is an impressive finding, given that the comparison set is highly selective,

and only includes leading companies and journal publishers.

The most highly cited NIST peer reviewed paper was published in Science in 1995, and

describes sequencing of the H.influenzae genome (the first example of a free-living

organism having its entire genome sequenced). It has been cited by 277 subsequent

patents (and over 5,000 papers, according to Google Scholar).

We benchmarked citations from US patents to NIST grey literature against citations

from US patents to grey literature from Massachusetts Institute of Technology (MIT).

Overall, citations to NIST grey literature grew almost nine-fold between 2000 and

2014. This is higher than the growth rate associated with citations to MIT grey

literature, although the difference is only slight. Even so, outperforming a prestigious

institution such as MIT on this metric is an impressive feat.

The most highly cited items of NIST grey literature are the Federal Information

Processing Standards (FIPS) publications outlining the Advanced Encryption Standard

(FIPS 197); the Secure Hash Standard (FIPS 180); and the Digital Signature Standard

(FIPS 186). These standards documents have been cited by hundreds of subsequent US

patents.

We also analyzed the US patents that cite NIST technical outputs as prior art, focusing

on the distribution of these patents by technology, industry, and assignee.

More than one-fifth of the 34,000+ citations to NIST come from patents related to

Computer Hardware & Software; and more than one-third are from that category plus

Communications. Other major citing categories are Measuring & Testing, and

Semiconductors & Electronics.

A large number of citations from Computer Hardware & Software and

Communications patents are to FIPS documents such as the Secure Hash Standard

(FIPS 180) and the Advanced Encryption Standard (FIPS 197). Also highly cited are

various NISTIRs and NIST special publications, which often describe the contents of

the FIPS documents.

IBM and Microsoft cite NIST most extensively, followed by Calcitec (a medical

devices firm), 3M and Micron Technology. Both IBM and Microsoft build heavily on

NIST grey literature, as do Intel, Cisco and Hewlett-Packard. Meanwhile, Calcitec

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builds primarily on NIST peer reviewed papers, as do the University of California and

Michigan State University, plus the US Department of Commerce (which includes

citations from NIST’s own patents to NIST papers). NIST’s patents are cited most

heavily by 3M, Western Digital and Cree.

In terms of industries, Universities cite NIST technical outputs most extensively,

followed by Semiconductor companies, Software companies, and Communications

companies. Other industries that cite NIST outputs extensively are Medical

Equipment/Instruments, Computer Systems and Electronics.

Overall, the analysis presented in this report reveals that there has been a significant

increase over time in citations from US patents to NIST technical outputs. These

citations are from patents owned by organizations across a broad range of industries,

describing a wide variety of technologies. Our analysis also demonstrates how the

increase in citations to NIST outstrips citations to comparable document sets. This

suggests that NIST’s technical outputs have had a strong, and growing, impact on

technological developments.

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I. Introduction

This report outlines the results of an analysis designed to evaluate the technological

impact of technical outputs associated with the National Institute of Standards and

Technology (NIST). NIST funds a wide range of technical activities and research,

resulting in many different types of published outputs. However, NIST itself has

relatively few patents assigned to it. In order to assess NIST’s influence on technological

developments, it is thus necessary to look beyond simply the agency’s portfolio of

granted patents.

The analysis presented in this report is designed to provide a detailed evaluation of

NIST’s technological impact. It is based primarily on locating technical outputs – such as

patents, scientific journal articles, standards documents, conferences papers, and other

forms of grey literature – associated with NIST funding. We then trace forward from

these technical outputs to determine how they have influenced subsequent technological

developments, specifically those developments described in patents assigned to all

organizations. In this way, it is possible to discern NIST’s impact on innovations

developed by organizations of all types and sizes, across all technologies and industries.

This report contains three further sections. The first of these sections provides an

overview of the project design, and the evaluation techniques used in the analysis. The

second section outlines the methodology used to carry out the analysis, including how the

various data sets were constructed. The third section contains the results of the analysis,

examining the impact of NIST funded technical outputs on subsequent technological

developments.

II. Project Design

The analysis presented in this report centers upon connections between generations of

research that are made by prior art references listed on patent documents. The purpose of

these prior art references is to detail the state of the art at the time of the patent application,

so that the applicant can demonstrate how the new invention is original over and above this

prior art. These references may consist of many different types of documents. A large

number of the references are to earlier patents and published patent applications; while

others are to scientific journal articles and conference proceedings; and others are to

standards, technical reports, magazines and newspapers.

The responsibility for adding prior art references differs across patent systems. In the US

system, it is the duty of patent applicants and their attorneys to reference (or ‘cite’) all prior

art of which they are aware that may affect the patentability of their invention. Patent

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examiners may then reference additional prior art that limits the claims of the patent for

which an application is being filed.

Patent citation analysis centers upon the links between generations of research that are

made by these prior art references. In basic terms, this type of analysis is based upon the

idea that the prior art referenced in patents has had some influence, however slight, upon

the development of these patents. The prior art is thus regarded as part of the technical

foundation for the later inventions.

In assessing the influence of individual documents – whether patents, papers or other forms

of grey literature – citation analysis centers on the idea that highly cited documents (i.e.

those cited by many later patents) tend to contain technological information of particular

interest or importance. As such, they form the basis for many new innovations and research

efforts, and so are cited frequently by later patents. While it is not true to say that every

highly cited document is important, or that every infrequently cited document is necessarily

trivial, many research studies have shown a correlation between patent citations and

measures of technological and scientific importance. For background on the use of patent

citation analysis, including a review of validation studies supporting its use, see Breitzman

A. & Mogee M. “The many applications of patent analysis”, Journal of Information

Science, 28(3), 2002, 187-205. For a detailed study of various hypotheses surrounding the

motivations of inventors in citing non-patent references, see Branstetter, L. and Oguara, Y.

“Is Academic Science Driving a Surge in Industrial Innovation? Evidence from Patent

Citations”, NBER Working Paper 11561, August 2005.

Patent citation analysis has also been used extensively to trace technological developments.

For example, in the analysis presented in this report, we examine citations from patents to

earlier technical outputs resulting from NIST funded activities. The idea behind this

analysis is that the patents have built in some way on these NIST technical outputs. By

determining how frequently NIST funded technical outputs have been cited by subsequent

patents, it is thus possible to evaluate the extent to which NIST funded activities have

helped form the foundation for a wide range of technologies.

It should be noted that the analysis presented in this report is based on prior art references

from US patents to NIST funded technical outputs, such as patents, journal articles,

conference papers, standards and software. The analysis does not consider references from

journal papers to NIST funded papers (or from journal papers to NIST funded patents,

although references from papers to earlier patents are very rare). This is purposeful, since

our primary focus is on how NIST activities have influenced innovations developed across

a range of industries. Such innovations are particularly likely to be protected by patents.

Meanwhile, scientific papers may describe more early-stage and exploratory research, so

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references from them to NIST papers may be mainly a reflection of the scientific, rather

than technological, impact of the agency’s activities.

III. Methodology

While the previous section outlines the general idea behind the analysis described in this

report – i.e. tracing citation links from US patents to earlier NIST funded technical outputs

– this section describes the methodology used to implement the analysis. In particular, it

focuses on how these two document sets – US patents and NIST funded technical outputs

– were collated, and how citation links between them were located.

Citing Document Set: Granted US Patents

In order to perform citation linkage analyses such as the one described in this report, 1790

Analytics maintains our own internal patent databases. Currently, we have every granted

US patent and published US patent application from 1969 to date in our US patent database

(which was used in this project). We also have every patent from 1978 to date in our EPO

(European Patent Office) database; and every PCT (Patent Cooperation Treaty) application

from 1978 to date in our WIPO (World Intellectual Property Organization) database.

Our patent databases contain detailed information on all patents, including inventors,

assignees, titles, abstracts, patent classifications, and application and issue dates. In

addition, our databases contain all prior art references listed on the front page of patents,

including references to earlier patents, and to other non-patent literature. It is this detailed

prior art reference information that makes possible large-scale citation studies such as the

one outlined in this report.

One other important feature of our patent databases is our corporate thesaurus, which

accounts for the many different names under which organizations own patents. As an

example, the pharmaceutical firm Sanofi has been assembled through the merger and

divestiture of companies that were themselves built through acquisition. Sanofi has patents

under 200+ different company names, and fewer than 10% of its patents are assigned to a

name that contains ‘Sanofi’ within the string. Our corporate thesaurus automatically

accounts for these subsidiaries and provides us with a complete patent inventory for each

organization. This is an important element of the analysis presented in this report,

particularly with regard to the results showing organizations whose patents reference NIST

technical outputs most extensively.

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Cited Document Set: NIST Technical Outputs

There are four main categories of NIST technical outputs included in the analysis described

in this report: patents assigned to NIST; patents in which NIST has a government interest;

peer reviewed papers funded by NIST; and NIST grey literature (which is further divided

into eight sub-categories). Below, we outline the processes involved in compiling each of

these sets of technical outputs, categorizing them (in the case of NIST grey literature), and

locating prior art references to them from US patents.

Cited Document Category 1: Patents Assigned to NIST

Collating Documents – NIST provided us with a list of patents assigned to the agency, so

this was the most straightforward document set to collate from our perspective.

Locating Prior Art References from US Patents – prior art references to patents are listed

in the form of patent numbers. For example, US Patent #9,012,542 references nine earlier

granted US patents as prior art, and these patents are identified by their patent numbers

(#2,388,169; #3,450,667 etc). This patent also references five published US patent

applications, and three foreign patents, all of which are again listed by their patent numbers.

Patent numbers (for both granted patents and published patent applications) are unique

identifiers, and are typically listed in a standard format. As a result, it is possible to

construct databases containing all citation links between generations of patents, such as the

database we maintain at 1790. The citation links consist of pairs of citing-cited patent

numbers, with both of these numbers being unique identifiers. Given access to such a

database, it is relatively straightforward to take a starting set of patent numbers (i.e. the

cited half of the pair), and locate subsequent patents that reference these patents as prior

art (i.e. the citing half of the pair). In this analysis, we carried out such a process, with the

starting set consisting of the patent numbers associated with the patents assigned to NIST.

Cited Document Category 2: Patents with a NIST Government Interest

Collating Documents – US patents have on their front page a section entitled ‘Government

Interest’. This section details the rights that the government has in a particular invention.

These typically exist where a government agency funds research at an external organization

(such as a for-profit company or a non-profit organization), and the government has certain

rights to the patents resulting from this research. For example, US Patent #9,024,298,

which is assigned to Xerox Corporation, contains the following statement in its

Government Interest field:

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This invention was made with United States Government support under Cooperative

Agreement No. 70NANBOH3033 awarded by the National Institute of Standards and

Technology (NIST). The United States Government has certain rights in the

invention.

We searched the Government Interest field of all US patents, and identified those patents

that refer to NIST. These searches included various forms of the full agency name –

National Institute of Standards and Technology – plus the NIST acronym.

Locating Prior Art References from US Patents – we identified the patent numbers for

the NIST government interest patents. We then searched in our databases for subsequent

US patents that reference these NIST government interest patents as prior art. As in the

case of NIST assigned patents, this was a relatively straightforward process involving

matching patent numbers, which are unique identifiers.

Cited Document Category 3: NIST-Funded Peer Reviewed Papers

Collating Documents – NIST provided us with a list of 50,000+ peer reviewed papers

authored by NIST personnel. These papers were downloaded by NIST personnel from the

Web of Science1.

Locating Prior Art References from US Patents – prior art references to items other than

patents are typically referred to as Non-Patent References (NPRs). These NPRs can be to

any published document, from scientific journal articles, conference papers and standards

documents, all the way to comic strips and brochures. They are much more difficult to

work with than prior art references to patents, since they are in free text. Also, inventors

are not required to use a standard referencing format for listing NPRs, in contrast to an

author submitting a manuscript for publication in a scientific journal. In addition, there is

no equivalent to a journal editor or reviewer ensuring that the references are complete,

since this is typically not a major concern of the patent examiner. As a result of these

various factors, NPRs are thus free text that can be in any format, and may be incomplete.

Author names may be present or absent, and journal names can be in many different

formats (for example, there are more than 30 variant spellings of the journal title Journal

Of Thoracic And Cardiovascular Surgery found in patents, including misspellings of

thoracic and different ways of abbreviating cardiovascular).

1 This document set consists primarily of peer reviewed journal articles, but it does also contain some papers

from conference proceedings, some of which will be peer reviewed and some not. We define this category

as peer reviewed papers to make it distinct from the so-called ‘grey literature’ categories consisting of white

papers and internal NIST publications such as NISTIRs, standards recommendations etc.

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We have built a number of tools designed specifically to address these issues with NPRs.

We applied these tools here to locate prior art references from patents to peer reviewed

papers authored by NIST funded researchers. This process involved matching the NPRs

listed on all US patents against the 50,000+ NIST papers downloaded from the Web of

Science.

These Web of Science records are in a standard format, listing the year, journal, first author,

first page, and title for each NIST funded paper. We thus processed NPRs into the same

format, parsing them in order to isolate these various reference elements. We then applied

our journal thesaurus to the journal element of each paper. This thesaurus contains more

than 50,000 variant names for journals. For example, the Journal of the American Medical

Association may appear as J. Am. Med. Assoc., Jrnl Am. Med Assoc., J of Am Med Assoc.,

JAMA, or one of more than a dozen other variants.

At this point, we had two lists – one containing NPRs, and one containing NIST papers –

each with the various bibliographic elements (year, journal, author, page, title) all extracted

and standardized. We then matched these two lists, and scored the quality of each match

according to the following scoring system:

Score Fields Matched

10 Year, Journal, Author, Page

9 Year, Journal, Author6, Page

8 Year, Journal10, Author, Page, Title15

7 Year, Journal, Author6, Title15

6 Journal, Author, Title15, Page

5 Journal, Author, Full Title

4 Year, Journal, Author, Volume OR Title

The highest scoring match is thus one where the year, journal name, first author and first

page number all match perfectly. In the second-highest scoring match, the year, journal

name and first page number all match, along with six characters of the first author name

(Auth6). For example, a name like Petropoulos may be misspelled in multiple ways, but a

match of six characters is likely to mean a correct match. Similarly, in the third-highest

scoring match, ten characters of the journal name (Journal10) and fifteen characters of the

title (Title15) must match in order to achieve this score.

Under this scoring system, matches with a score of 8-10 are automatically considered to be

correct. Matches with a score of 4-7 are considered to be possible correct matches, and

were confirmed or discarded via human inspection.

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Cited Document Categories 4-11: NIST Grey Literature

Collating Document Set – whereas NIST provided us with a list of peer reviewed papers

associated with its funding, there was no similar list of NIST grey literature available (and

such a list would be extremely difficult and time-consuming to construct). The process for

locating NIST grey literature cited by US patents was thus somewhat different from the

process used to locate other NIST technical outputs cited by patents. Specifically, the

process for other technical outputs involved two steps – i.e. first identifying the universe

of NIST outputs, and then matching these outputs to references in US patents. Meanwhile,

the process for identifying citations to NIST grey literature only involved a single step –

i.e. references from US patents to grey literature were located directly, without first

defining the universe of this literature.

Locating Prior Art References from US Patents – we identified grey literature cited in US

patents by searching the non-patent references in these patents for keywords related to

NIST, such as NBS, Nat*Bur*St*, Nat*Inst*St*, FIPS, Fed*Inf*Proc*St*, NIST* etc. We

also accounted for possible term confusion, for example searching for NIST* and not

machinist* or administration.

Categorizing Cited NIST Grey Literature – NIST personnel expressed significant interest

regarding which types of grey literature produced by the agency have been particularly

influential upon subsequent technological developments. We thus categorized NIST grey

literature into eight subcategories, as defined by NIST personnel. This was a complicated

process, and involved a series of iterations using combinations of keywords and manual

review in order to categorize NIST grey literature satisfactorily.

The eight categories of grey literature (numbered 4-11, following on from the three

categories of NIST technical outputs already discussed), are outlined below. The

constituent elements of each category are listed, along with examples of technical outputs

associated with the category.

Category 4 – Educational Networking

a. Conferences

b. Seminars

c. Webinars

d. Workshops

e. Symposiums

f. Presentations

g. Short Courses

h. Proceedings

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Examples:

Holleyman, Robert W. "On the Export of Software with Encryption Capabilities ",

testimony presented at Key Escrow Meeting, NIST, Gaithersburg, MD, Sep. 6, 1995, pp.

1-7.

Sweat et al. Characterization of natural and induced variation in the LOV1 gene, a CC-

NBS-LRRR gene conferring victorin sensitivity and disease susceptibility in Arabidopsis.

MPMI. 2008. 21(1): 7-19.

Self-Organizing Neural Network Character Recognition on a Massively Parallel Computer,

Wilson et al, NIST, International Joint Conference on Neural Networks, Proceeding, II, pp.

325 329, Jun. 1990, San Diego, Calif.

Category 5 - Software/Standard Reference Databases/Algorithms

a. Materials and Property Data

b. Standard Reference Data

c. Software (ex: NSRL)

d. Databases (excluding SRDs)

e. FIPS

f. NIST WebBook

g. Documentation/Publications Regarding SRMs (that do not have a NIST-

assigned publication number)

h. Joint Partnership Publications Regarding Standards (ex: ANSI/NIST Doc

category)

i. NIST Standard Reference Data Series (NIST NSRDS)

Examples:

NIST, “Advanced Encryption Standard (AES)”, FIPS Publication 197, 52 pages, Nov 26,

2001.

http://www.nsrl.nist.gov/, National Software Reference Library, printed from website May

15, 2012, 1 page.

Grother, Patrick J. “NIST special database 19 handprinted forms and characters database.”

National Institute of Standards and Technology (1995).

Category 6 – Standard Reference/Resource Materials/General Information

a. Measurement and Testing Methodology

b. Standard Reference Materials (SRMs)

c. Website Citation (ex: NIST Home Page)

d. Tables

e. Dictionaries

f. Stand-Alone Pictures

g. Fact Sheets

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Examples:

Periodic Table. NIST. 2003.

Photograph of the NIST Micro Microwave Oven, NISTmicropic.jpg, Mar. 1, 2011.

Semicon West 2001, Website:

http://www.nist.gov/public_affairs/factsheet/semiconwest01.htm.

Category 7 - Official NIST Publications (not peer-reviewed journal)

a. NIST Special Publications (NIST SP-XXX)

b. NIST Technical Notes (NIST TN)

c. NIST Grant/Contract Reports (NIST GCR)

d. NIST Handbook

e. NIST Interagency/Internal Reports (NISTIR)

Examples:

Ross, U.S. Department of Commerce, Nat'l Bur. Stands, Publication NSRDS-NBS59 (Jan.

1977).

Bearden, J. A.; X-ray Wavelengths and X-ray Atomic Energy Levels. US Dept of

Commerce, Nat'l Bur. Stands. NSRDS 14, pp. 1-47 (Sep. 1967).

Burr et al., Ed., “Electronic Authentication Guideline,” Version 1.0.2,

http://csrc.nist.gov/publications/nistpubs/800-63/SP800-63V1(sub)—0(sub)—2.pdf, Apr.

2006, 64 pages.

Category 8 - Joint Partnership Publications (not peer-reviewed journal)

a. DARPA

b. NSA

c. Colorado School of Mines

d. JILA

e. JQI

f. HML

g. IBM

Examples:

Federal Aviation Administration (FAA), "Draft Burnthrough Test Standard for Aircraft

Insulation," FAA on World Wide Web (http://www.fire.tc.faa.gov/burnthru.html), p. 16,

(Mar. 24, 1999).

Technisches Messen , vol. 51, 1984, Issue No. 3, pp. 83 95 Federal Physical Technical

Institute (Physikalisch Technischen Bundesantalt) or the Nat'l Bur. Stands.

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Category 9 - Other NIST (non peer-reviewed) publications

a. Circulars

b. Internal Reports

c. Recommendations

d. Proposals

e. Bulletins

f. Press Releases

Examples:

US Dept of Commerce, NIST, FY 2010 Small Business Innovation Research Program

Solicitation, NIST-10-SBIR, Oct. 30, 2009-Jan. 22, 2010.

Proctor, F.; "Validation of Standard Interfaces from a Machine Control", 1996, NIST,

NIST Internal Report, pp. 659-664.

Snoke, Hubert R., Building Mat ls & Structures, Report BMS 70, Nat'l Bur. Stands, 1941,

p. 15.

Category 10 - Communication/Correspondence/Inquiries

a. Questions, answers, and requests for comments on FIPS

b. FFOs, solicitations, private communications

Examples:

Peter L. Bender, Nat'l Bur. Stands, private communication, 1978

Leonard E. Miller, Apr. 2002, NIST.

Category 11 - Other

a. NIST news clips – when NIST is mentioned in a newspaper, article, etc.

b. Articles reporting NIST technical outputs

Examples:

English translation of Official Letter of Taiwan Patent Office (Nat'l Bur. Stands) in Taiwan

Appln. No. 82100814.

Messmer, Ellen, "NIST proposes standard for electronic signatures", Network World, p. 4,

Jul. 1991.

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Summary of Document Sets

As a result of the processes outlined above, we compiled two data sets, the first consisting

of granted US patents, and the second containing NIST funded technical outputs referenced

as prior art by these patents. These NIST outputs are categorized as follows:

Category Number Category Definition

1 NIST-Assigned Patents

2 NIST Government Interest Patents

3 NIST-Authored Peer-Reviewed Publications

4 Educational Networking

5 Software/Standard Reference Databases/Algorithms

6 Standard Reference/Resource Materials/General Information

7 Official NIST Publications (not peer-reviewed journal)

8 Joint Partnership Publications (not peer-reviewed journal)

9 Other NIST (non peer-reviewed) publications

10 Communication/Correspondence/Inquiries

11 Other

These document sets, and the citation links between them, form the basis for our analysis

of the impact of NIST funded research on subsequent technological developments. The

results of this analysis are outlined in the following section of the report.

IV. Results

We report the results of our analysis at two different levels of granularity. First, we report

organization-level results, examining the overall impact of NIST funded technical outputs,

both in absolute terms, and in the context of the broader citation landscape. We then outline

results at the level of individual NIST technical outputs, highlighting those published items

that have had a particularly strong impact on subsequent technological developments.

Organization-Level Results

Overall NIST Citation Counts

Between January 1995 and July 2015, there were a total of 34,241 citations from US patents

to NIST-supported technical outputs. This is an impressive figure, especially given the fact

that NIST had only 124 US patents assigned to it through the end of 2014. It suggests that

NIST’s influence extends far beyond just its own patented inventions, and that the agency’s

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activities help form the foundation for technological developments made by a wide range

of other organizations.

Figure 1 contains a breakdown of the 34,241 citations from US patents, according to the

category of NIST document receiving each citation. This figure reveals that 14,538 (43%)

of the citations are to peer reviewed papers authored by NIST-supported researchers. The

next largest category is NIST government interest patents, which received 9,062 (26%) of

the citations. These are patents assigned to organizations other than NIST, but in which

NIST has some rights having provided funding for the research that led to the patented

inventions. The number of citations to NIST government interest patents is more than four

times higher than the number of citations to patents actually assigned to NIST (2,173, or

6%). This reflects that fact that NIST supports a great deal of research carried out by other

organizations, rather than only funding researchers within the agency.

The remaining 24% of citations from US patents to NIST documents are to various types

of grey literature. The largest of these grey literature categories is software, standard

reference databases and algorithms, which accounts for 2,914 (8%) of citations from US

patents to NIST documents. Other grey literature categories that receive significant

numbers of citations are Official NIST Publications (1,671 citations, or 5%); Educational

Networking (1,267 citations, 4%); and Other NIST Publications (1,740 citations, 5%). The

final four grey literature categories together account for only 2.5% of citations from US

patents to NIST documents.

Figure 2 is based on the same data as Figure 1, but presents it in the form of a pie-chart.

Also, in this figure, all of the grey literature categories are combined for ease of

presentation. As such, Figure 2 is a basic overview of citations from US patents to NIST

technical outputs in the four main categories: peer reviewed papers; government interest

patents; assigned patents; and grey literature.

Trends in NIST Citation Counts

Figure 3A shows trends over time in citations from US patents to NIST technical outputs.

Specifically, this figure shows the number of citations to NIST each year from 1995 to

2014, along with the number of unique US patents citing NIST each year (the two are not

equivalent, since one patent may reference multiple NIST documents as prior art). The first

point to note in Figure 3A is the growth in the number of citations from US patents to

NIST. There was a more than a ten-fold increase in these citations between 1995 and 2014.

The second point to note is the widening gap between the two lines in this figure, especially

in recent years. In the 1990s, patents that cited NIST typically cited a single NIST

document, so the number of citations and the number of citing patents were almost

identical. More recently, the two numbers have started to diverge, to the point where, in

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2014, there were 3,000 unique patents that cited NIST, and these patents provided more

than 4,500 citations to NIST (i.e. an average of more than 1.5 citations per citing patent).

Beyond these overall trends, it is informative to examine whether there is any difference in

the citation trends across different types of cited NIST technical outputs. Figure 3B shows

the number of citations to the four main types of NIST outputs (peer reviewed papers;

government interest patents; assigned patents; and grey literature) from US patents issued

each year from 1995 through 2014. This figure reveals that the sharp increase in citations

to NIST outputs shown in Figure 3A can also be seen for each of the four document types.

Having said this, while citations to each of the NIST document types have increased over

time, the largest increases are associated with peer reviewed papers and government

interest patents.

The trend lines in Figures 3A and 3B suggest that the influence of NIST documents has

increased markedly over the past two decades. However, it should be noted that the overall

number of citations provided by US patents has also increased significantly over the same

time period. This is due to increases in the number of patents issued each year, and also in

the mean number of prior art references listed on patents. Also, over time, the corpus of

NIST technical outputs has grown, so there are many more such outputs available to be

cited. In subsequent figures, we attempt to account for these various factors, and thus place

the growth of citations to NIST technical outputs in the context of the wider citation

landscape.

This wider landscape may differ for the various types of cited document. For example,

trends over time in citations to patents may be different to trends in citations to journal

articles. Also, as shown in Figure 3B, there are differences in the rate of growth in citations

to the different types of NIST technical outputs. Given these factors, we examine each type

of NIST technical output (i.e. patents, peer reviewed literature, grey literature) separately,

as outlined below.

Benchmarking NIST Citation Counts

To assess NIST patents (both those assigned to the agency and those with a NIST

government interest) within the wider citation landscape, we employed our citation-based

patent metrics. These metrics are used across many of our projects, and form the basis for

the Patent Power Scorecards published annually in IEEE Spectrum magazine (an example

of these scorecards is available at http://spectrum.ieee.org/static/interactive-patent-power-

2015). The metrics – which are described below – assess different characteristics of patents,

notably their impact, generality and originality.

http://spectrum.ieee.org/static/interactive-patent-power-2015

http://spectrum.ieee.org/static/interactive-patent-power-2015

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As discussed earlier, one widely used method of assessing the impact of a patent is to count

how many times it has been cited by subsequent patents. However, using raw citation

counts to assess patent impact is often problematic, since older patents are likely to be more

highly cited, simply because they have had more time to accrue citations from later patents.

Citation rates also differ across technologies. In order to overcome these two problems, we

normalize citation counts by issue year and technology (as defined by Patent Office

Classifications) to produce a Citation Index for all granted patents.

The Citation Index is derived by dividing the number of citations received by a patent by

the mean number of citations received by all patents from the same Patent Office

Classification (POC) and issue year. For example, the number of citations received by a

patent issued in 2005 with a primary POC of 351/210 is divided by the mean number of

citations received by all patents issued in 2005 with the same primary POC.

The expected Citation Index for an individual patent is one. The extent to which a patent’s

Citation Index is greater or less than one reveals whether it has been cited more or less

frequently than expected, and by how much. For example, a Citation Index of 1.5 shows

that a patent has been cited 50% more frequently than expected. Meanwhile a Citation

Index of 0.7 reveals that a patent has been cited 30% less frequently than expected.

Patent generality is based on the premise that technologies with applications across a range

of industries are likely to be of greater interest than technologies with only a narrow range

of applications. For example, a new material that is used in many different industries is

regarded as more general than a material that is only used in a single application.

This metric is operationalized via citation links. Specifically, patents cited as prior art by

subsequent patents from numerous technologies are regarded as having more general

applicability than patents that are only cited by subsequent patents from the same

technology. We normalize generality by both issue year and technology (as defined by

Patent Office Classifications), to derive a Generality Index with an expected value of one.

Patents with a Generality Index greater than one are more general than peer patents drawn

from the same technology and issue year, while patents with a Generality Index below one

are less general than their peers.

Patent Originality is the analog of Patent Generality, and looks backwards in time, rather

than forwards. It is based on the premise that patents that build upon a wide range of

technologies are likely to be more original than patents that draw only upon earlier

developments in the same technology (which may represent incremental improvements on

that technology). This indicator is once again operationalized via citation links.

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Specifically, patents that cite as prior art earlier patents from numerous technologies are

regarded as more original than patents that only cite patents from the same technology.

We again normalize originality by both issue year and technology (as defined by Patent

Office Classifications) to derive an Originality Index with an expected value of one. Patents

with an Originality Index greater than one are more original than peer patents drawn from

the same technology and issue year, while patents with an Originality Index below one are

less original than their peers.

Figure 4 shows the Citation Index, Generality Index and Originality Index for patents

assigned to NIST and for patents in which NIST has a government interest (i.e. those

patents resulting from research that NIST funded in external organizations). The metrics

are shown for two separate time periods – i.e. NIST-related patents issued in 2005-09 and

NIST-related patents issued in 2010-2014.

The Citation Index for NIST-assigned patents is below one for both time periods,

suggesting that these patents have not had a particularly strong impact on subsequent

technological developments. However, the number of patents assigned to NIST is very

small (only 22 patents were granted to NIST in 2005-09 and 100 in 2010-2014), so not too

much importance should be attached to this finding.

The Citation Index for NIST government interest patents is much more impressive,

exceeding 1.6 in both time periods. This shows that the NIST government interest patents

have been cited more than 60% more frequently than expected, given their relative age and

technology. In turn, this suggests that they have had a strong impact on subsequent

innovations. Given that the number of NIST government interest patents is much higher

than the number of NIST-assigned patents, this finding is much more noteworthy.

A similar pattern can be seen for NIST-assigned patents and NIST government interest

patents in terms of their Generality Index. Again, NIST-assigned patents perform relatively

poorly on this metric, with a Generality Index below one in both time periods, albeit based

on a small number of patents. Meanwhile the Generality Index for NIST government

interest patents is much higher, and exceeds two in the most recent time period. This

suggests that the NIST government interest patents have a broad applicability across a

range of technologies.

The results for the two sets of patents are much more similar in terms of their Originality

Index. In both cases, the Originality Index exceeds one for both time periods, but not by a

wide margin. This suggests that both the NIST-assigned patents and the NIST government

interest patents are more original than expected, but not by a significant degree.

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Overall, the patent citation metrics in Figure 4 support the idea that NIST-supported

patents, especially those with a NIST government interest, have had a strong, wide-ranging

impact on subsequent technology developments. As such, the increases in citations to NIST

patents reported in Figure 3B appear to be associated with this strong impact, rather than

simply being a reflection of changes in the underlying citation landscape.

Placing citations to NIST’s peer reviewed papers and grey literature in a wider context is

more difficult than it was for citations to NIST-supported patents. There are no equivalent

normalizations measuring how many times a paper of a certain age, and from a given

subject area, can be expected to have been cited in subsequent patents. Given this lack of

available normalizations, we had to devise suitable comparisons in order to place the

citations to NIST literature in a wider context.

In evaluating citations to NIST published documents, we examined peer reviewed papers

and grey literature separately. For peer reviewed papers, one obvious approach would have

been to compare citations to NIST’s papers against citations to papers produced by other

agencies or institutions. However, this would have required identifying complete paper sets

for those institutions, and then doing a match similar to that described in the methodology

section above. That is a costly endeavor, and is well beyond the scope of this project.

In recognition of the time and budget constraints, our comparison set for NIST peer

reviewed papers was instead drawn from one of our existing projects. Each year, we

produce a report for the Institute of Electrical and Electronics Engineers (IEEE). In this

project, we identify the 40 companies with the largest number of US patents granted in the

most recent year. These companies include IBM, Siemens, Canon etc. We then locate and

disambiguate prior art references from the patents of these companies to papers published

in journals from the leading publishers, specifically Elsevier, Wiley, Springer, American

Chemical Society, American Institute of Physics, IEEE, IOP Publishing, and Optical

Society of America.

In the current analysis, we used the annual citation counts from this IEEE project as a

benchmark against which to compare citation counts to NIST peer reviewed papers. It is

worth noting that more than 65% of NIST’s peer reviewed papers are published in a journal

from one of these leading publishers, so this seems like a reasonable comparison set.

Figure 5A contains an index (base year = 2000), showing the growth in the number of

citations from the IEEE analysis, plus the growth over the same period in the number of

citations from all US patents to NIST peer reviewed papers. This figure reveals that

citations from the leading companies to the leading publishers increased more than six-fold

between 2000 and 2014. While impressive, this increase is still lower than that associated

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with NIST papers. Between 2000 and 2014, the number of citations from US patents to

NIST papers increased seven-fold.

The IEEE analysis is based on a highly select set of citing and cited documents – i.e.

citations from patents owned by leading companies to papers published in leading

academic journals. Hence, the fact that citations to NIST papers have grown faster than

citations to papers in the leading journals is highly impressive. If we were to add journals

from other less renowned publishers, we suspect that the outperformance of NIST papers

would be even more marked (however, we do not have data on citations to these journals

readily available).

With respect to NIST grey literature, finding a reasonable benchmark was also problematic.

NIST produces a wide variety of types of grey literature, from standards documents, to

official definitions, to software, to reference materials. There are no comparable

organizations that produce as wide a variety of grey literature as NIST. The best

comparison we could locate was Massachusetts Institute of Technology (MIT). Like NIST,

MIT produces a broad range of technical reports, thesis drafts, software, and guides.

Moreover, it is one of the most respected and entrepreneurial universities, with many of its

students and faculty creating hi-tech startup companies. As such, MIT’s technical outputs

are likely to be closely related to the applied technologies described in patents.

MIT should thus be a suitable (and indeed demanding) comparison for NIST with regard

to grey literature. Figure 5B shows an index (base year = 2000) for citations each year from

all US patents to grey literature produced by NIST and MIT. Overall, citations to NIST

grey literature grew almost nine-fold between 2000 and 2014. This is higher than the

growth rate associated with citations to MIT grey literature, although the difference is only

slight. Even so, outperforming a prestigious institution such as MIT on this metric is an

impressive feat.

Patents Citing NIST Technical Outputs

Having examined overall trends in citations to NIST, and their distribution across different

NIST document types, we now look in more detail at the patents that cite NIST technical

outputs as prior art. We focus in particular on the distribution of these patents by

technology, industry, and assignee.

Figure 6 shows citations to the four main types of NIST documents by the technology area

of the citing patents. This technology area is defined based on 1790’s technology

concordance, which maps patents to technologies based on their primary patent

classification. Figure 6 reveals that more than one-fifth of the 32,000+ citations to NIST

come from patents related to Computer Hardware & Software; and more than one-third are

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from that category plus Communications. Other major citing categories are Measuring &

Testing, and Semiconductors & Electronics.

It is also interesting to note the distribution of citations across different technologies and

NIST document types. For example, Measuring & Testing and Semiconductors &

Electronics patents cite NIST peer reviewed papers extensively. The same is true for

Biotechnology, Ceramics, and Chemicals patents. Meanwhile, Computer Hardware &

Software and Communications patents build much more extensively on NIST grey

literature.

Figure 7 contains the same data as Figure 6, but divides the citations to NIST grey literature

into the eight sub-categories outlined in the methodology section of the report. This figure

reveals that a large number of citations from Computer Hardware & Software and

Communications patents are to Category 5 (Software/Standard Reference

Databases/Algorithms). Many of these citations are to FIPS documents such as the Secure

Hash Standard (FIPS 180) and the Advanced Encryption Standard (FIPS 197). Another

highly cited category of NIST grey literature is Category 7 (Official NIST Publications).

Many of these citations are to NIST documents such as NISTIRs and NIST special

publications, which often describe the contents of the FIPS documents from Category 5.

Figures 8 and 9 show the distribution of citations to NIST by citing assignee. Figure 8 –

which is divided into the four main NIST document types – reveals that IBM and Microsoft

cite NIST most extensively, followed by Calcitec (a medical devices firm), 3M and Micron

Technology. This figure also reveals that the different assignees cite different types of

NIST outputs. Both IBM and Microsoft build extensively on NIST grey literature, as do

Intertrust, Intel, Cisco and Hewlett-Packard. Meanwhile, Calcitec builds primarily on NIST

peer reviewed papers, as do the University of California and Michigan State University,

plus the US Department of Commerce (which includes citations from NIST’s own patents

to NIST papers). NIST’s patents are cited most heavily by 3M, Western Digital and Cree.

Figure 9 is the same as Figure 8, but with citations to NIST grey literature divided into the

eight subcategories. This figure highlights the extensive influence of the Software/Standard

Reference Databases/Algorithms subcategory (Category 5) on the patents of IBM and

Microsoft, plus the patents of First Data, Cisco and Oracle. It also highlights the influence

of NIST Educational Networking (Category 4), such as workshops and conferences, on the

patents of Microsoft, Intertrust and Assa Abloy.

Figures 10 and 11 show the distribution of citations to NIST according to the industry of

the citing assignees. Note that these industries are not the same as the technologies

examined earlier in Figures 6 and 7. For example, Microsoft is categorized as being in the

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Software industry, based on its primary industry classification. Hence, Microsoft’s patents

are all considered as part of the Software industry in Figures 10 and 11. However, while

Microsoft is a software company, it has patents across a wide range of technologies (as

defined by patent classifications), which were used in the generation of Figures 6 and 7.

Figure 10 shows that Universities cite NIST technical outputs most extensively, followed

by Semiconductor companies, Software companies, and Communications companies.

Other industries that cite NIST outputs extensively are Medical Equipment/Instruments,

Computer Systems and Electronics. Figure 10 also reveals that Universities cite primarily

NIST peer reviewed papers, as do Medical Equipment/Instruments companies. Meanwhile,

Semiconductor, Software and Communications companies build more extensively on

NIST grey literature. Semiconductor companies also cite NIST patents extensively, as do

Electronics and Computer Peripherals/Storage companies.

Figure 11 breaks out citations to NIST grey literature according to the various

subcategories of this literature. This figure shows that Semiconductor, Software,

Communications and Computer Systems companies have large numbers of citations to

NIST Educational Networking (i.e. workshops and conferences). Companies in these

industries also cite Official NIST Publications, and Other NIST Publications, extensively.

Overall, the organization-level results discussed above highlight the significant increase in

citations from US patents to NIST technical outputs. These citations are from patents

owned by organizations across a broad range of industries, describing a wide variety of

technologies. The results above also demonstrate how the increase in citations to NIST

outstrips citations to comparable document sets. This suggests that NIST’s technical

outputs have had a strong, and growing, impact on technological developments.

Document-Level Results

The previous section of the report focuses on results at the level of the entire portfolio of

NIST technical outputs. In this section, we report results at the level of individual NIST

outputs. The objective of this section is to highlight individual NIST documents that have

had a particularly strong impact on subsequent technological developments. These results

are divided according to the eleven detailed categories of NIST outputs described in the

methodology section of the report (i.e. NIST assigned patents; NIST government interest

patents; NIST peer reviewed papers; plus eight categories of NIST grey literature).

Table 1 lists the NIST assigned patents with the highest Citation Index values. As outlined

earlier in the report, the Citation Index is a normalized impact indicator. It measures how

many times patents have been cited as prior art by subsequent patents, compared to peer

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patents from the same year and technology. For example, the patent at the head of Table 1

(US #5,356,756) has been cited by 110 subsequent patents. The mean number of citations

for all 1994 patents in the same patent classification is 14.6. Hence, the ’756 patent has a

Citation Index of 7.53 (110/14.6), showing it has been cited 7.53 times as frequently as

expected. This patent describes materials processing for thin films, designed for use in

sensors, electronic devices and sample analysis.

The second and third patents in Table 1 (US #5,795,782 and US #6,015,714) are part of

the same patent family (i.e. they are related to the same underlying invention). They

describe a method for rapid DNA analysis, and have both been cited by more than 100

subsequent patents, five times as many citations as expected given their age and

technology. Looking further down the list of patents in Table 1, the one with the highest

absolute number of subsequent citations is US #6,088,679. This patent describes a business

process system for workflow management. It has been cited by 233 subsequent patents, but

this is only twice as many expected, since it is in a rapidly expanding area of patenting (i.e.

business methods), in which citation rates are very high.

Table 2 shows the NIST government interest patents that have the highest Citation Index

values. There are a number of patents in this table with very high Citation Indexes, notably

the patent at the head of the table (US #7,330,404). This patent has been cited by 127

subsequent patents since it was issued in 2008, which is more than 40 times as many

citations as expected given its age and technology. It describes a transducer for use in

optical storage (for example in disk drives), and is assigned to Seagate Technology – one

of a number of highly cited Seagate patents in Table 2. Other companies with a series of

highly cited NIST government interest patents include ConforMIS (whose patents describe

treatment of cartilage in joints); Bind Biosciences (controlled drug delivery); and General

Electric (phosphor blends for LED devices).

NIST-sponsored peer reviewed papers that have been cited frequently in US patents are

shown in Table 3. The paper at the head of this table has been cited by 277 subsequent

patents (and over 5,000 papers, according to Google Scholar). It was published in Science

in 1995, and describes sequencing of the H.influenzae genome (the first example of a free-

living organism having its entire genome sequenced).

The second paper listed in Table 3 does not report original research, but is instead a

literature survey of face recognition technology. It has been cited by 161 patents. There are

three further papers in Table 3 that have been cited by more than 100 patents. They are a

1996 paper describing a membrane filter for use in DNA analysis (137 patent citations),

and two papers from the same NIST research group describing methods for measuring

nanoscale distances (120 and 116 patent citations). The most highly cited recent NIST peer

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reviewed paper is the ‘NIST Definition of Cloud Computing’. This was published in the

Communications of the ACM in 2010, and has already been cited by 68 subsequent US

patents.

Tables 4-11 list the individual items of NIST grey literature that have been cited most

frequently by US patents, with each table focusing on a different category of this literature.

Table 4 contains the most highly cited NIST Educational Networking publications (i.e.

workshops, presentations, conference papers etc). The most highly cited of these

publications is a 1996 presentation describing a proposed federal public key infrastructure

(PKI) for secure communications. It has been cited as prior art by 28 subsequent patents.

It is one of a number of papers in Table 4 concerned with PKI technology. The table also

contains highly cited papers describing frameworks for information infrastructures,

equipment operator training, and detecting intrusive behavior in networks.

Table 5 lists the NIST Software/Databases/Algorithms publications cited most frequently

by subsequent US patents. The most highly cited are the Federal Information Processing

Standards (FIPS) publications outlining the Advanced Encryption Standard (FIPS 197);

the Secure Hash Standard (FIPS 180); and the Digital Signature Standard (FIPS 186).

These standards documents have been cited by hundreds of subsequent patents, and are the

most highly cited individual items of NIST grey literature.

The NIST Standard Reference/Resource Materials cited most frequently in patents are

shown in Table 6. The most highly cited is the NIST ‘Dictionary of Algorithms and Data

Structures’, which has been cited by 67 subsequent patents. Also highly cited are the red-

black tree (48 patent citations), and the Bloom filter (17 patent citations), which are

respectively a specific data structure and an algorithm listed in this NIST dictionary.

Table 7 lists the Official NIST Publications (NISTIRs, Special Publications etc) that have

been cited most frequently by US patents. The publication at the top of this list is a 1980

NBS technical note describing a Schottky diode bridge sampling gate, designed for

measuring low level signals in circuits. This publication has been cited by 101 subsequent

US patents. The second publication in Table 7 is ‘The NIST Definition of Cloud

Computing’ with 67 citations from US patents. This is NIST’s own publication of this

definition, which also appeared in the Communications of the ACM (see Table 3). Other

highly cited NIST Special Publications are concerned with block ciphers and public key

infrastructure, both of which are related to cryptography.

The publications in Table 8 are NIST Joint Partnership Publications, meaning they were

developed in collaboration with other organizations and agencies. The publication at the

head of this table is entitled ‘Federal Criteria for Information Technology Security’, and

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dates back to 1992. It has been cited by 31 US patents since its publication. More recent is

the second publication in Table 8, which is a review of ultra-wideband technology

published by NIST in partnership with DARPA in 2003. This publication has been cited

by 24 subsequent US patents. In general, the publications in Table 8 are relatively old,

some dating as far back as 1960.

The publications in Table 9 (Other NIST Publications) are generally more recent, with most

being published post-2000. The most highly cited of these publications is from 2003, and

has been cited by 66 US patents. It is entitled ‘Intrinsic velocity and its relation to intrinsic

conductivity’. Other highly cited publications include papers on biometrics (38 patent

citations), thin films (34 patent citations), and internet security (30 patent citations).

Table 10 contains items of correspondence with NIST that have been cited by numerous

subsequent US patents. The citation counts in this table are mostly quite low, with only

four items being cited by more than 10 patents. Two of these four items are comments to

NIST regarding modes of operation of the Advanced Encryption Standard (AES). They

have been cited by 17 and 11 patents respectively. The other two items are a submission to

NIST regarding the Galois/Counter Mode (GCM), used in cryptography; and a private

communication to NIST dating back to 1978.

The citation counts in Table 11 (Publications mentioning NIST) are also relatively low,

with the most highly cited single publication having been cited by 18 subsequent US

patents. This is a paper published in 1999 that refers to the NBS phosphor standard samples.

Table 11 also contains a discussion of the NIST Digital Signature Standard (15 patent

citations); a proposed NIST standard for role-based access control (15 patent citations);

and an analysis of the NBS data encryption standard (14 patent citations).

V. Conclusions

This report outlines the results of an analysis designed to evaluate the technological impact

of technical outputs associated with NIST. The analysis is based on tracing forward from

these NIST outputs to determine how frequently they have been cited by subsequent

patents. This makes it possible to evaluate the extent to which NIST funded activities have

helped form the foundation for a wide range of technologies.

The analysis presented in this report reveals that there has been a significant increase over

time in citations from US patents to NIST technical outputs. These citations are from

patents owned by organizations across a broad range of industries, describing a wide

variety of technologies. Our analysis also demonstrates how the increase in citations to

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NIST outstrips citations to comparable document sets. This suggests that NIST’s technical

outputs have had a strong, and growing, impact on technological developments.

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VI. Appendix: Figures and Tables

188 (

0.5

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100 (

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11. O

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Lets delete this heading. But please move all of the figure below ahead of the tables in appendix 1.

25

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4.-

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#

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Age W

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"F

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Com

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Build

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Technic

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Core

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T 

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NIS

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NIS

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Abberley e

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he T

HIS

L S

poken D

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NIS

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Ruiz

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IND

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Conceptu

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terlin

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RE

C-8

Evalu

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IST

Specia

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ublic

ation 5

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46, 1999, 597-6

06.

Ta

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NIS

T P

ub

lic

ati

on

s (

NIS

TIR

, S

pe

cia

l P

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lic

ati

on

s e

tc.)

H

igh

ly C

ite

d i

n P

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13

Goya

l, "

An X

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chem

a N

am

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ter

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Ele

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National In

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f S

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s a

nd T

echnolo

gy 

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ocum

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t

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Rukhin

A A

Sta

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or

Random

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Num

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Genera

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Cry

pto

gra

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Applic

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NIS

T S

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burg

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MD

, U

S. N

o. 800-2

2. M

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15, 2001. X

P002276676 IS

SN

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76X

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"The N

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iam

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r C

ylin

drical C

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Resonato

r: P

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orm

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valu

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or

Perm

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Measure

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13

Morr

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work

in, "R

ecom

mendation f

or

Blo

ck C

ipher

Modes o

f O

pera

tion: T

he C

CM

Mode f

or

Auth

entication a

nd C

onfidentialit

y,"

NIS

T S

pecia

l P

ublic

ation 8

00 3

8C

,

May 2

004, 26 p

ages, N

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f S

tandard

s a

nd T

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gy G

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D, U

SA

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Nat'l

Bur.

Sta

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pecia

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ublic

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14, N

ov., 1

969, pp. 367 3

70, 430.

12

Kra

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T.; P

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The N

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274/N

GC

Inte

rpre

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", O

ct. 2

6, 1995, N

IST

, pp. 1-5

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11

C. T

. Liu

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. C

. K

och, D

evelo

pm

ent of

Ductile

Poly

cry

sta

lline N

i 3 A

l F

or

Hig

h T

em

pera

ture

Applic

ations , T

echnic

al A

spects

of

Critical M

ate

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Use b

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Industr

y, N

BS

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3 2

679 2

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Cente

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.S. D

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Sto

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G. et al., “R

isk M

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uid

e f

or

Info

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gy S

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ms”,

National In

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te o

f S

tandard

s a

nd T

echnolo

gy, T

echnolo

gy A

dm

inis

tration

,

U.S

. D

ept. o

f C

om

merc

e, S

pecia

l P

ublic

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00 3

0; R

ecom

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f th

e N

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f

10

Shaw

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dw

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A. F

ox, "C

om

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ultip

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earc

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In P

roceedin

gs o

f th

e 3

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ext R

etr

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TR

EC

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Mary

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IST

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Public

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50, 1995, 4 p

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10

National In

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te o

f S

tandard

s a

nd T

echnolo

gy (

NIS

T),

“R

ecom

mendation f

or

Pair W

ise K

ey

Esta

blis

hm

ent S

chem

es U

sin

g D

iscre

te L

ogarith

m C

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phy

(Revis

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” N

IST

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00 5

6A

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10

Bark

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ecom

mendation f

or

Key M

anagem

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Part

I: G

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l. N

IST

Specia

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ublic

ation 8

00 5

7 M

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2007

. pp. 1 1

42.

10

Voorh

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t al., "T

he C

olle

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usio

n P

roble

m",

Pro

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f T

RE

C-3

, N

IST

Specia

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25, A

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04.

10

Scarf

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t al., “G

uid

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n D

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nd P

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yste

ms (

IDP

S),

” N

IST

(N

ational In

stitu

te o

f S

tandard

s a

nd T

echnolo

gy),

Specia

l P

ublic

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00

94, F

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irele

ss N

etw

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Security

802.1

1 B

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Devic

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NIS

T S

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8, T

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f

Com

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10

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ecom

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or

Blo

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Modes o

f O

pera

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eth

ods a

nd T

echniq

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National In

stitu

te o

f S

tandard

s a

nd T

echnolo

gy, N

IST

Specia

l

Public

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8B

, (2

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22 p

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Roy

G. S

altm

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ccura

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om

pute

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om

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cie

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BS

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58, A

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This

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free o

f charg

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m: h

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x.d

oi.o

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0.6

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T.G

CR

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09

45

This

pu

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free o

f charg

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m: h

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x.d

oi.o

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/ NIS

T.G

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# P

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nt

Cita

tio

ns

Art

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31

Fe

de

ral C

rite

ria

fo

r In

form

atio

n T

ech

no

logy S

ecu

rity

, vo

l. I

I, V

ers

ion 1

.0, N

IST

and

Natio

na

l S

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Ag

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De

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19

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, 2

70

pa

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s.

24

Mill

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Leo

na

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Wh

y U

WB

? A

Re

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w o

f U

ltra

wid

eb

an

d T

ech

no

logy”

NIS

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AR

PA

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aith

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Man

de

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rn,

L. e

t a

l.,

"Fu

sio

n o

f P

oly

me

r N

etw

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s F

orm

ed f

rom

Lin

ea

r P

oly

eth

yle

ne

: E

ffe

ct

of

Inte

rmo

lecu

lar

Ord

er"

, co

ntr

ibutio

n f

rom

the

Ge

ne

ral

Ele

ctr

ic R

ese

arc

h L

abo

rato

ry a

nd

fro

m t

he

Po

lym

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Str

uctu

re S

ectio

n,

Na

t'l B

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Sta

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s 8

2:

46

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(1

96

0).

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Pa

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Da

vid

et

al.,

Be

nch

ma

rk T

ests

fo

r th

e D

AR

PA

Sp

oke

n L

an

gu

ag

e P

rogra

m,

NIS

T,

12

pa

ge

s,

un

da

ted

.

17



A G

uid

e t

o A

irb

orn

e,

Imp

act,

an

d S

tru

ctu

reb

orn

e N

ois

e C

on

tro

l in

Mu

ltifa

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Dw

elli

ngs 

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. S

. D

epa

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of

Ho

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g a

nd

Urb

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De

ve

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ent,

Pre

pa

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Bu

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Wa

sh

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D.

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Pa

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D.S

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Pre

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DA

RP

A A

TIS

Te

st

Re

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IST

/DA

RP

A,

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Ju

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90

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Wa

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Pu

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Ke

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fra

str

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re f

or

U.S

. G

ove

rnm

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Un

cla

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d b

ut

Se

nsitiv

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ns,"



NO

RT

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Rese

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995

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4 p

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“Da

tab

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Pro

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Em

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on N

ew

Lea

d-f

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old

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, P

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s o

f L

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”, R

ele

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4.0

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tern

et

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Mech

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" T

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PA

TIM

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ontin

uo

us S

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Corp

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NIS

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.

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Ma

gn

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ano

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“Tru

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va

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"Th

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f E

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Pa

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Sta

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s S

tatu

s",

Fra

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. O

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IST

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ED

EC

JC

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om

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n

Ele

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Th

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em

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In

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1.

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We

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Ga

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Na

t'l B

ur.

Sta

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nd

th

e N

atio

na

l S

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Fo

uda

tio

n (

197

8)*

.

3A

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Ma

teria

ls f

or

Inte

gra

ted O

ptic A

pplic

atio

ns 

; H

ayd

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ch

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Gla

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Inc.

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IST

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Bu

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Pre

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Sig

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pp. 859 8

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2

"Tru

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M. P

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NIS

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MA

CH

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Alla

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To

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Tra

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ina

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DA

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We

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Part

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Pu

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NIS

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Jansen

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., “

Auth

enticating U

sers

on H

andheld

Devic

es,”

The N

IST

, G

aithers

burg

, M

ary

land, 2003, 13 p

ages.

14

Leig

h e

t al., "T

ransfo

rmation, R

ankin

g, and C

luste

ring f

or

Face R

ecognitio

n A

lgorith

m C

om

parison,"

at http://w

ww

.itl.n

ist.gov/d

iv898/itp

erf

/renorm

.pdf.

13

Ford

, S

usan, "A

dvanced E

ncry

ption S

tandard

(A

ES

) Q

uestions a

nd A

nsw

ers

," O

ct. 2

, 2000, pp. 1-5

, obta

ined f

rom

http://w

ww

.nis

t.gov/p

ublic



--

</s

ub>

aff

airs/r

ele

ases/a

esqanda.h

tm.

13

"Filt

ration a

nd U

ltra

filtra

tion E

quip

ment and T

echniq

ues";

Mem

bra

nes.n

ist.gov; printe

d o

n A

ug. 12, 2005; pp. 1-1

4; lo

cate

d a

t:

http://w

ww

.mem

bra

nes.n

ist.gov/A

CS

chapte

r/pelle

PA

GE

.htm

l.

12

P. L. B

ender,

A P

roposal to

the N

AS

A f

or

the S

upport

of

GP

S S

ate

llite

Orb

it D

ete

rmin

ation u

sin

g the R

econstr

ucte

d C

arr

ier

Phase M

eth

od f

or

Tra

ckin

g , Q

uantu

m

Phys

ics D

ivis

ion, N

at'l

Bur.

Sta

nds, B

ould

er,

Colo

rado, pp. 1 1

2, subm

itte

d A

ug. 5, 1980.

12

Mechanic

s o

f P

neum

atic T

ires, C

lark

, N

at'l

Bur.

Sta

nds M

onogra

ph 1

12, U

.S. D

ept. o

f C

om

merc

e, pp. 241-2

43 a

nd 2

90-2

91 (

Nov. 1971).

11

Schneem

an, R

.; "

Devic

e D

river

Develo

pm

ent fo

r M

icro

soft

Win

dow

s N

T: A

ccessin

g M

otion C

ontr

ol H

ard

ware

Usin

g a

Multim

edia

Fra

mew

ork

(w

ith D

EF

S)"

, N

IST

,

Oct. 1

, 1996, D

EF

S 0

0010531-0

0010580.

10

Wayn

e J

ansen e

t al., "P

rivile

ge M

anagem

ent of

Mobile

Agents

", N

IST

Oct. 2

000.

10

Mill

er,

L.E

., e

t al. F

Y 2

005 Inte

rim

Pro

ject R

eport

, R

FID

-Assis

ted L

ocaliz

ation a

nd C

om

munic

ation f

or

First R

esponders

, O

ct. 2

5, 2005, (r

ev. M

ar.

22, 2006),

National In

stitu

te o

f S

tandard

s a

nd T

echnolo

gy, http://w

ww

.antd

.nis

t.gov/w

ctg

/RF

ID/R

FID

assis

t.htm

.

10

W.A

. Jansen, "A

Privile

ge M

anagem

ent S

chem

e f

or

Mobile

Agent S

yste

ms"

NIS

T M

ay 2

001.

9Jansen e

t al., "M

obile

Agents

in Intr

usio

n D

ete

ction a

nd R

esponse,"

NIS

T, 12 p

ages, Jun. 2000.

9Jeff

Kurt

z, et al. M

ap N

avig

ation E

xperim

ent. h

ttp://w

ww

.itl.n

ist.gov/iaui/vvrg

/nis

t-ic

v/e

xperim

ents

/mapnav/m

apnav.h

tml. L

ast accessed o

n M

ar.

1, 2006. 3 p

gs.

9H

olm

berg

, “F

acili

ty Inte

rface to the S

mart

Grid

,” N

IST

, 7 p

ages, printe

d 2

012.

8A

lbus, J.; "

A R

efe

rence M

odel A

rchitectu

re f

or

Inte

lligent S

yste

ms D

esig

n",

NIS

T, 1993, pp. 1-3

8.

8W

ayn

e J

anson e

t al., "A

pply

ing M

obile

Agents

to Intr

usio

n D

ete

ction a

nd R

esponse"

NIS

T Inte

rim

Report

, O

ct. 1

999.

8

Jansen

, W

ayn

e “

Auth

enticating M

obile

Devic

e U

sers

Thro

ugh Im

age S

ele

ction”,

Retr

ieved a

t

<http

://c

src

.nis

t.gov/(

sub)—

gro

ups/S

N(s

ub)—

S/m

obile

(sub)—

security

/docum

ents

/mobile

(sub)—

devic

es/P

P-V

isua1A

uth

entication

-rev-D

S04.p

df>

, (2

004),

10

8

“NIS

T L

ocation S

yste

m,”

[onlin

e]. W

irele

ss C

om

munic

ation T

echnolo

gie

s G

roup

, N

ational In

stitu

te o

f S

tandard

s a

nd T

echnolo

gy, M

ar.

12, 2004 [re

trie

ved in N

ov.

1, 2004]. R

etr

ieved f

rom

the Inte

rnet: <

UR

L: w

ww

.antd

.nis

t.gov>

. (2

pages).

8

Glig

or,

Virgil

D., e

t al., “F

ast E

ncry

ption a

nd A

uth

entication

: X

CB

C E

ncry

ption a

nd E

XC

B A

uth

entication M

odes”

Mar.

30, 2001 (

Apr.

20, 2001, re

vis

ion),

64 p

ages,

retr

ieved f

rom

http

://c

src

.nis

t.gov/g

roups/S

T/toolk

it/B

CM

/modes(s

ub)—

develo

pm

ent.

htm

l.

8T

. S

pie

s. F

eis

tel F

inite S

et E

ncry

ption M

ode. http://c

src

.nis

t.gov/g

roups/S

T/toolk

it/1

5 B

CM

/docum

ents

/pro

posedm

odes/f

fsem

/ffs

em

-spec.p

df.

Tab

le 9

:Oth

er

NIS

T (

No

n-P

eer

Revie

wed

) P

ub

licati

on

s H

igh

ly C

ited

in

Pate

nts

47

This

pu

blic

atio

n is

availa

ble

free o

f charg

e fro

m: h

ttp://d

x.d

oi.o

rg/1

0.6

028

/ NIS

T.G

CR

.16-0

09

# P

ate

nt

Cita

tio

ns

Art

icle

17

Lip

ma

a, H

elg

er,

et al., “C

om

me

nts

to N

IST

co

nce

rnin

g A

ES

Mod

es o

f O

pera

tio

ns:”

CT

R-M

od

e E

ncry

ptio

n 2

000, 4 p

ages.

13

McG

rew

, D

avid

A.,

et

al.,

Th

e G

alo

is/C

oun

ter

Mod

e o

f O

pera

tio

n (

GC

M)

Su

bm

issio

n t

o N

IST

, M

ay

31,

20

05

, 4

4 p

ag

es.

11

Bla

ck,

Jo

hn

, "C

om

me

nts

to N

IST

co

nce

rnin

g A

ES

Mod

es o

f O

pera

tio

ns:

A S

ugg

estio

n f

or

Ha

nd

ling A

rbitra

ry-L

en

gth

Messa

ge

s w

ith

th

e C

BC

MA

C,"

Un

ive

rsity

of

Ne

va

da

, R

en

o,

Ph

illip

Rog

aw

ay,

Un

ive

rsity

of

Ca

lifo

rnia

at

Da

vis

http

://c

src

.nis

t.go

v/C

ryp

toT

oolk

it/m

od

11

Pe

ter

L. B

end

er,

Na

t'l B

ur.

Sta

nd

s,

priva

te c

om

mu

nic

atio

n,

19

78

.

9R

og

aw

ay, P

hill

ip, “P

MA

C—

Pro

po

sa

l to

NIS

T f

or

a p

ara

lleliz

able

me

ssa

ge

au

the

ntica

tio

n c

ode

” A

pr.

1, 2001

, 27 p

ages.

8

Sch

roe

ppe

l, R

ich

ard

C., e

t al., “C

iphe

r-S

tate

(C

S)

Mod

e o

f O

pera

tio

n f

or

AE

S”

Sa

nd

ia N

atio

na

l L

ab

ora

torie

s, S

ubm

issio

n t

o N

IST

, M

ay 7

, 2004,

8 p

age

s.

7B

ella

re, M

., e

t al., “A

Co

nve

ntio

na

l A

uth

entica

ted

-En

cry

ptio

n M

od

e”

Su

bm

issio

n t

o N

IST

, A

pr.

13, 2003,

14 p

age.

7K

ohn

o, T

ada

yosh

i, e

t al., “T

he C

WC

Au

the

ntica

ted

En

cry

ptio

n (

Asso

cia

ted

Data

) M

od

e”

May 2

7, 2003, 18 p

ages, S

ubm

issio

n t

o N

IST

.

7H

ou

se

ly, R

uss, et al., “C

ou

nte

r w

ith

CB

C-M

AC

(C

CM

)—A

ES

Mod

e o

f O

pera

tio

n”

RS

A L

ab

ora

torie

s, S

ubm

issio

n t

o N

IST

, Ju

n. 3, 2002, 9 p

ages.

7D

. W

hitin

g,

R.

Hou

sle

y, N

. F

erg

uso

n,

"Su

bm

issio

n t

o N

IST

: C

oun

ter

with

CB

C-M

AC

(C

CM

)",

AE

S M

od

e o

f O

pera

tio

n,

RS

A L

ab

ort

orie

s.

5W

agn

er

et a

l.,

"Co

mm

ents

to N

IST

co

nce

rnin

g A

ES

Mod

es o

f O

pera

tio

ns:

CT

R-M

od

e E

ncry

ptio

n",

20

00

, U

niv

ers

ity

of

Ca

lifo

rnia

, p

. 1

-4.

4

Gu

rne

y e

t a

l.,

Usin

g L

ime

sto

ne

to

Red

uce

Se

t R

eta

rdatio

n in

Hig

h V

olu

me

Fly

Ash

Mix

ture

s:

Imp

rovin

g C

onstr

ucta

bili

ty f

or

Susta

inab

ility

, N

IST

(Su

bm

issio

n D

ate

: A

ug.

1,

20

11

).

3R

ive

st

et

al., T

he M

D6 h

ash

fu

nctio

n—

A P

ropo

sa

l to

NIS

T f

or

SH

A-3

. S

ubm

issio

n t

o N

IST

, F

eb. 20, 2009

.

3

Str

uik

, R

.; “

Co

mm

ents

on N

IST

Dra

ft P

ub 8

00-3

8C

: C

CM

Mod

e o

f O

pera

tio

n”,

Oct. 2

0, 2003. A

va

ilable

fro

m:

httlp

://c

src

.nis

t.go

v/C

ryp

toT

oolk

it/m

ode

s/R

eco

mm

end

atio

n/.

1

L. K

nud

se

n,

DE

AL

-A 1

28-b

it B

lock C

iphe

r, s

ubm

itte

d a

s a

n A

ES

ca

nd

idate

(se

e h

ttp

://w

ww

.nis

t.go

v/a

es),

http://w

ww

/ii/uib

/no/~

lars

r/papers

/deal.ps, A

ug. 20-2

2, 1998.

1

Te

ch

nic

al p

rop

osa

l e

ntitle

d,

So

lid S

tate

Ava

lanch

e P

hoto

dio

de

Dete

cto

r A

rra

y T

ech

no

logy f

or

Me

dic

al, E

nviro

nm

enta

l, a

nd R

ese

arc

h

Ap

plic

atio

ns,

su

bm

itte

d to

NIS

T a

s c

onfid

en

tia

l, p

roprie

tary

in

form

atio

n,

da

ted

Fe

b. 2

3,

19

93

, p

p.

5 1

3 5

16.

1F

erg

uso

n,

N.

"Au

the

ntica

tio

n W

eakn

esse

s in

GC

M,"

Co

mm

ents

to t

he

NIS

T M

od

es o

f O

pera

tio

n P

roce

ss.

20

05

.

1

Ho

t M

eta

l G

as F

orm

ing (

HM

GF

) b

y A

uto

Bo

dy C

onso

rtiu

m,

Inc.

Ma

r. 1

8, 1

99

8,

NIS

T A

dva

nce

d T

ech

no

logy,

Pro

gra

m G

ene

ral P

rogra

m

Co

mp

etitio

n 9

8-0

1.

Tab

le 1

0:C

orr

esp

on

den

ce w

ith

NIS

T H

igh

ly C

ited

in

Pate

nts

48

This

pu

blic

atio

n is

availa

ble

free o

f charg

e fro

m: h

ttp://d

x.d

oi.o

rg/1

0.6

028

/ NIS

T.G

CR

.16-0

09

# P

ate

nt

Cita

tio

ns

Art

icle

18

Oh

ku

bo

, K

. et

al (1

99

9)

"Ab

so

lute

Flu

ore

sce

nt

Qu

an

tum

Eff

icie

ncy o

f N

BS

Ph

osp

ho

r S

tand

ard

Sa

mp

les,"

Jo

urn

al o

f th

e Illu

min

atin

g

En

gin

ee

ring

In

stitu

te o

f Ja

pa

n 8

3(2

):8

7-9

3 (

pa

rtia

l tr

an

sla

tio

n).

15

"Th

e D

igita

l S

igna

ture

Sta

nd

ard

," N

atio

na

l In

stitu

te o

f S

tand

ard

s a

nd

Te

ch

no

logy (

NIS

T),

Pro

po

sa

l a

nd

Dis

cu

ssio

n,



Co

mm

. of

the

AC

M 

, 3

5 (

7),

Ju

l. 1

992

, p

p.

36

-54

.

15

Fe

rra

iolo

, e

t a

l, "

Pro

po

se

d N

IST

Sta

nd

ard

fo

r R

ole

-Base

d A

cce

ss C

ontr

ol"

, A

CM

Tra

nsa

ctio

ns o

n I

nfo

rma

tio

n a

nd

Syste

m S

ecu

rity

, vo

l.

4, N

o.

3,

Au

g.

20

01

, p

p.

22

4-2

74

.

14

Diffie

an

d H

ellm

an,

Exh

au

stive

Cry

pta

naly

sis

of

the

NB

S D

ata

En

cry

ptio

n S

tand

ard

, p

p.

74

-84

, C

om

pute

r, J

un.

19

77

.

10

Bro

wn

et

al., “S

oft

wa

re I

mp

lem

enta

tio

n o

f th

e N

IST

Elli

ptic C

urv

es O

ve

r P

rim

e F

ield

s”,

To

pic

s in

Cry

pto

logy: T

he C

ryp

tog

rap

her's T

rack

at R

SA

, Le

ctu

re N

ote

s in

Com

pute

r S

cie

nce

(L

NC

S)

20

01

, vo

l. 2

020

, p

p.

25

0-2

65

.

9T

ransla

tio

n o

f th

e O

ffic

ial L

ett

er

Da

ted

Dec.

17

, 2

00

4 F

rom

the

Nat'l

Bu

r. S

tand

s,

Min

istr

y o

f E

co

no

mic

Aff

airs o

f T

aiw

an R

e.: 9

21

28

40

7.

9

Frie

nd

, D

an

iel G

.; T

herm

oph

ysic

al P

rope

rty C

om

pute

r P

acka

ge

s f

rom

NIS

T;

pp

. 1

3-1

8;

19

92

; A

SM

E H

TD

vo

l. 2

25,

Co

mp

ute

rize

d

Th

erm

oph

ysic

al P

rope

rty P

acka

ge

s.

9A

nde

rso

n, Jo

hn

C.; “

Re

sp

on

se

to

NIS

T's

Pro

po

sa

l”; C

om

mu

nic

atio

ns o

f th

e A

CM

; vo

l. 3

5, N

o. 7; Ju

l. 1

992; pp. 41

-54.

5

IRE

; N

ew

s R

ele

ase

; IR

E T

ake

s L

ea

d in

Bu

ildin

g S

ecu

re F

oun

da

tio

n f

or

Ele

ctr

onic

Co

mm

erc

e o

n th

e I

nte

rne

t; P

art

ne

rs w

ith

NIS

T t

o

De

ve

lop P

ublic

Ke

y S

tand

ard

s;

Ba

ltim

ore

, M

ary

land

; Ju

l. 2

4, 1

99

6;

Info

rma

tio

n R

eso

urc

e E

ngin

ee

ring

; (V

ER

I-1

60

58

85

-VE

RI-

160

58

86

).

5

He

ller,

E.

"NIS

T A

wa

rds $

2 M

illio

n C

ontr

act

to E

HC

/Lig

hts

tre

am

fo

r D

eve

lopm

ent

of

Ne

w P

oto

ca

taly

st

Te

ch

no

logy,"

pre

ss r

ele

ase

Au

g.

16, 1995, pp. 1-3

.

4

Na

tio

na

l In

stitu

te o

f S

tand

ard

s a

nd

Te

ch

no

logy (

NIS

T),

"O

ptica

l M

icro

sco

pe

s E

nte

r th

e N

an

o A

ge,"

Be

tte

rhu

ma

ns N

ew

sle

tte

r

.CO

PY

RG

T.

20

02

-20

05,

2 p

ag

es.

3

Bro

wn

, D

an

iel R

.L.; “

Co

nje

ctu

re S

ecu

rity

of

the

AN

SI-

NIS

T E

llip

tic C

urv

e R

NG

”; C

ryp

tolo

gy e

Prin

t A

rch

ive

; R

ep

ort

2006/1

17; M

ar.

29,

2006; 14 p

ages. R

etr

ieved f

rom

the inte

rnet <

http://e

print.ia

cr.

org

>.

Tab

le 1

1:P

ub

licati

on

s M

en

tio

nin

g N

IST

th

at

are

Hig

hly

Cit

ed

(in

Pate

nts

)