massimo caccia infn & universita’ dell’insubria
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The TTN Questionnaire: a first glance at the data. Massimo Caccia INFN & Universita’ dell’Insubria. TTN mid-term workshop, CERN – June 23-24, 2009. The data sample (1/2). benchmark institutions:. - PowerPoint PPT PresentationTRANSCRIPT
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Massimo Caccia
INFN & Universita’ dell’Insubria
TTN mid-term workshop, CERN – June 23-24, 2009
The TTN Questionnaire:a first glance at the data
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The data sample (1/2)
benchmark institutions:
LBL No reply
TRIUMF I fear they did not get the point
FNAL Rather incomplete feedback
BNL Rather complete feedback!*
KEK No reply
* Possible misunderstanding: data for the full lab, not only for the HEP division (221/982 FTE’s)
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The data sample (2/2): our statistical population ( xxx % addressed institutions)
Universities
EPFL Good quality feedback small HEP community (50/3280 FTE’s) Use it as a second benchmark!
Bern Incomplete (e.g. no FTE’s etc.)
Zurich As above
ETH As above
NCSR As above
labs
CERN ok
DESY ok
GSI ok
PSI ok
Natl. Institutes
FTEFTE in HEP
NIKHEF 200 200
IN2P3 3000 3000
CEA 3500 500
By the end of the day: • 7 institutions split into 2 categories• 1 extra benchmark
NOT WORTH ANYTHING TERRIBLY SOPHISTICATED!
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Labs by size [FTE]FT
EFT
E in H
EP
CERN
DESYGSI
PSI
an averaging procedure weighted by FTE in HEP will be dominated by CERN DESY and PSI do represent a good example of labs where HEP and no-HEP live together
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(poor) analysis method
constrained by the limited statistical population and the large spread (standard deviation) of the data
assume as basic figures the Executive Summary indicators of the 2006 ASTP survey for fiscal year 2006 [excluding financial data on the income & start-up’s], namely:
Invention disclosures Patent applications Patent grants License agreements Research agreements
Normalized to 1 year and per 1000 FTE’s
assume as a reference the ASTP mean data + BNL and EPFL
compare to the mean and weighted mean values for labs & institutions (weights defined by FTE in HEP)
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A closer to look to the indicators for the labs (normalized to 1000 FTE’s, per annum) (1/3)
dis
closu
res
license
dap
plic
ati
ons
gra
nte
d
CERN
DESY
GSI
PSI
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A closer to look to the indicators for the labs (normalized to 1000 FTE’s, integrated) (2/3)
CERNDESY GSI PSI
fam
ilies
license
dR
ATIO
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A closer to look to the indicators for the labs (normalized to 1000 FTE’s) (3/3)
IP t
ransf
er/
an
num
Agre
em
ent/
an
num
CERN
DESY
GSIPSI
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The performance indicator summary table(per 1000 FTE’s)
labs Natl. Inst. BNL EPFLAST
P UNI.
ASTP
PRO
ASTP mean
<x>W <x> x
<x>W
<x> x
disclosures 7 9 9.8 2.3 1.3 1.3 33 24 15.6 20.4 16.6
Patent applications
4.4 4.1 5.5 1.7 0.9 1.0 13 12 5.5 9.2 6.3
Patent grants 1.0 1.3 1.3 0.1 0.3 0.5 9 6 2.6 7.8 3.2
License agreements
0.3 1.1 1.4 0.4 0.3 0.4 3 8 4.8 11.6 6.3
IP agreements 1.0 3.2 5.1 0.6 1.0 1.4 3 9 NA NA NA
Research Agreements
48.5 122 185 16.2 6.7 1.5 92 119 111 95.8 108.8
Patent families 27.5 32.0 25.1 12.2 8.6 4.5 120 78 NA NA NA
Overall Licensed patents
10.1 10.9 12.3 0.1 0.3 0.5 88 38 NA NA NA
ASTP mean weighted by the data size in the 2 samples
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Conclusions (1/3)
a picture is worth a thousand words:
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labs do it better
German labs do it a lot better!
the spread among the different institutions is terrifying (a lot higher than among benchmarks, irrespective of their intrinsic differences…)
there’s a solid rock motivation for the TTN
KE towards other disciplines and Research agreements with other scientific community has definitely to be pursued (DESY is, to me, a fairly good example!)
Conclusions (2/3)
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Conclusions (3/3)