Friday, December 9, 2011

Kites online patstat based reports update

@ url db.kites.unibocconi.it you may find updated version of KITeS patent reports, based on Patstat september 2011.


This is the full ist of resources available:

Patent count by inventor country / year
Patent count by applicant country / year
Patent count by inventor region / year
Patent count by applicant region / year
Patent count by inventor nuts3 / year
Patent count by applicant nuts3 / year
Patent count by applicant name / year
Patent count by main IPC - first 4 digits
Patent count by main IPC class reclassified on OST30
Patent count by applicant, year, OST30
Patent count by applicant country, county, region, OST30, year
Citations count by applicant name, year
Citations count by applicant country, year
Citations count by inventor country, year
Copatenting by inventor country, year
Copatenting by applicant country, year
Applicants by IPC - first 4 digits
Inventors by IPC - first 4 digits

Monday, November 28, 2011

Patstat person id new concordance file

I just released the new file of concordance ID among different edictions in patstat

'201009' to '200909' and
'201109' to '201009'
(so recursively it's possible also concordate 200909 to 201109)
@ this link you may find it in tab separated value

If you need some more details about how the file had been produced, you can check @ this previous post
http://rawpatentdata.blogspot.com/2011/10/person-ids-concordance-table.html
(anyway thanks to EPO for guesting the file on their servers and to Geert Boedt for making it possible)

Tuesday, November 22, 2011

Patent Statistics for Decision Makers 2011 - presentations

Back from washington Patent Statistics for Decision Makers 201, I put below a list of speakers who partecipated to the event; zipped full version in PDF along with 2010 statistics from 4 patent offices (US EP JP WO) can be downloaded here

Dr. Margaret Clements, Indiana University, US
The Geography of Academic Patents: A Strategic International Collaboration Network
Dr. Christian HELMERS, Universidad Carlos III de Madrid, ES
Is the Dragon Learning to Fly? An Analysis of Chinese Firms’ Patenting Activity in the US
Mr. Jean-Yves LEGENDRE, The L’Oreal Group, FR
The Use of Patent Data in Business Development at L’Oreal

Dr. James D. ADAMS, Rensselaer Polytechnic Institute, US
Discovery and Invention in Science-Based Firms
Dr. Hans LÖÖF, Royal Institute of Technology, Stockholm, SE
Patent, R&D Strategies and Entrepreneurial Spawning
Ms. Cynthia BARCELON-YANG, Bristol-Myers Squibb, US
The Role of Patent Analysis in Corporate R&D at BMS

Dr. Jan YOUTIE, Georgia Institute of Technology, US
Nanotechnology Firms from Discovery to Commercialization
Mr. Nils NEWMAN, MERIT and Intelligent Information Services Corporation, NL
Patent Overlay Mapping: Visualizing Technological Distance
Dr. Alan L. PORTER, Georgia Institute of Technology and Search Technologies, Inc., US
Tracking Emergence of a Nano Technology – Dye-Sensitized Solar Cells (DSSCs)

Mr. Kyriakos DRIVAS, University of California, Berkeley, US
The Role of Exclusive Licensing in Follow-on Research of Academic Patented Inventions
Dr. Lynne ZUCKER, UCLA, US
Patent Inventing and Scientific Discovery Synergy: Economic Effects of the Co-Evolution of
Universities and Firms

Mr. Ulrich STOLZENBURG, University of Kiel, DE
Scope and Diffusion of Knowledge from German PROs

Dr. Andrew CHRISTIE, Melbourne Law School, University of Melbourne, AU
What Difference Does Patent Examination Make?: An Analysis of the Effect of Examination in the
USPTO, the EPO and APO

Dr. Benjamin MITRA-KAHN, Intellectual Property Office, UK
A Framework for International Comparisons of Patent Backlogs
Dr. Julia LANE, National Science Foundation, US
StarMetrics: Using Patent Data to Measure Scientists’ Impacts

Mr. James BESSEN, Boston University, US
The Private Costs of “Patent Troll” Litigation
Dr. Catherine TUCKER, Massachusetts Institute of Technology, US
Patent Trolls and Innovation
Mr. Yoichiro NISHIMURA, Kanagawa University, JP
An Empirical Assessment of the Effects of Patent Thickets

Mr. Edward J. EGAN, University of California, Berkeley, US
Economic Implications of Patent Citations: Start-up Value & Organizational Form Choice
Mr. Michael J. LASINSKI, 284 Partners, LLC, US
Patents in Markets for Technology
Mr. Peter NEUHÄUSLER, Fraunhofer Institute for Systems and Innovation Research ISI, DE
Patent Information and Corporate Credit Ratings: An Empirical Study of Patent Valuation by
Credit Rating Agencies



Thursday, November 10, 2011

About Patstat 201109 address quality

Following older posts on address quality in patstat (see FI this link) as well the promise of EPO to increase the quality of addresses, I publish a raw data analisys on the coverage of data in TLS206 ASCII, by publication authority of the persons involved (applicants and inventors).

Data are filtered for aithorities with more than 100K persons. The full table can be downloaded here.


PUBLN AUTH
CTRY_CODE
CITY
ZIP_CODE
ADDRESS
STATE
npersons
AT
618701
70%
149939
17%
76
0%
158550
18%
974
0%
884886
AU
225646
18%
17937
1%
144
0%
18149
1%
1580
0%
1220880
BE
43756
44%
3056
3%
10
0%
5841
6%
157
0%
100260
BR
163996
29%
13131
2%
85
0%
11294
2%
1074
0%
571443
CA
954437
57%
224590
13%
319
0%
213805
13%
3553
0%
1685768
CH
330051
75%
40910
9%
492
0%
11601
3%
4629
1%
441558
CN
1726041
78%
154119
7%
386
0%
129331
6%
5907
0%
2220156
CS
91304
65%
15204
11%
217
0%
3932
3%
2471
2%
139842
CZ
93254
87%
19383
18%
34
0%
17414
16%
373
0%
107279
DD
134313
74%
28071
15%
392
0%
6182
3%
4323
2%
182429
DE
2394256
64%
479887
13%
1421
0%
359960
10%
16277
0%
3717514
DK
246656
63%
50065
13%
45
0%
57168
14%
463
0%
394525
EP
3944064
89%
3209446
73%
690
0%
3136945
71%
10567
0%
4407679
ES
436578
80%
107236
20%
97
0%
110159
20%
795
0%
542866
FI
226432
81%
43505
16%
265
0%
102712
37%
2827
1%
280451
FR
318738
41%
68703
9%
280
0%
53488
7%
2854
0%
786238
GB
315501
37%
14278
2%
98
0%
185697
22%
1062
0%
859983
GR
53652
53%
11872
12%
37
0%
12706
13%
454
0%
101250
HK
54506
39%
9243
7%
15
0%
10745
8%
143
0%
138188
HU
97758
63%
30532
20%
289
0%
10679
7%
3487
2%
155625
IT
150050
45%
35649
11%
110
0%
33902
10%
1138
0%
331307
JP
447686
22%
144406
7%
176
0%
128957
6%
2013
0%
2032077
KR
932706
80%
132216
11%
159
0%
121499
10%
2441
0%
1168036
MX
135570
50%
11065
4%
28
0%
11513
4%
322
0%
273738
NO
189383
64%
43122
15%
51
0%
46885
16%
736
0%
295515
NZ
62558
38%
15641
10%
38
0%
17513
11%
352
0%
163137
PL
124079
87%
23595
17%
73
0%
19343
14%
1035
1%
142492
PT
86039
70%
4003
3%
13
0%
4685
4%
131
0%
122655
RU
430544
72%
12922
2%
141
0%
6407
1%
1581
0%
598785
SE
75782
24%
6702
2%
36
0%
6522
2%
447
0%
314076
SU
669567
60%
19465
2%
290
0%
5404
0%
3383
0%
1113987
TW
231502
87%
31695
12%
18
0%
30610
11%
210
0%
266633
US
5914779
81%
5029368
69%
116078
2%
277250
4%
1162677
16%
7305084
WO
1718657
77%
352091
16%
626
0%
421852
19%
8785
0%
2218443
ZA
97482
30%
15095
5%
36
0%
16083
5%
482
0%
323448