The document outlines a proposal for an experiential platform aimed at participatory evaluation of sustainable innovations in livelihood conditions. It emphasizes the importance of evidence-based decision making, integrating both objective and subjective indicators to engage citizens continuously in the evaluation and planning process. The platform aims to harness collective intelligence and provide ongoing support for informed public policy decisions regarding sustainable development.

1. 
Joint
FAO-­‐ENOLL
meeting
Rome,
26-­‐01-­‐2011
PaESI Concept Note and Technical Architecture
An Experiential Platform for the
Participatory Evaluation of
Sustainable Innovation in
Livelihood Conditions
Francesco Molinari

2. 2
TOC
 Ra-onale
 Sustainable
Development
as
Systemic
Change
 An
alterna-ve
point
of
view
 Concept
 Evidence
based
decision
making
 Immersive
/
experien-al
plaHorm
 Digital
ecosystem
 Func-onal
descrip-on
 Conclusions

3. 3
Rationale
 Sustainable
development
is
a
maJer
of
systemic
change
that
(posi1vely)
impacts
on
the
economic
drivers
of
a
community,
while
preserving
the
fundamental
characters
of
the
social
and
environmental
landscape.
 However,
evalua-ng
the
progress
“towards
a
beJer
future”
of
a
given
community
is
mostly
a
foresigh1ng
exercise,
possibly
grounded
on
con-ngent
pieces
of
evidence,
which
can
only
en-tle
to
work
out
“reasonable”
specula-ons
–
quite
oQen
becoming
“seIf-­‐fulfilling”
expecta-ons.
 An
alterna-ve
point
of
view
takes
as
a
baseline
for
defining
sustainable
innova-on
(of
a
policy
stance,
or
a
concrete
instance
thereof)
the
actual
livelihood
condi1ons
of
the
people
affected
by
its
envisaged
implica-ons,
in
terms
of
e.g.
available
housing,
nutri-on,
health
records,
levels
of
educa-on
etc.

4. 4

5. 5
Rationale
(2)
 In
principle,
the
various
elements
forming
this
baseline
can
be
analysed,
interpreted
and
even
visualised,
to
help
governments
make
more
informed
decisions
on
systemic
change,
and
especially
to
“fine
tune”
their
ongoing
policy
ac-ons:
 either
objec1vely,
i.e.
by
measuring
and
benchmarking
some
quan1ta1ve
indicators
of
performance,
in
terms
of
an
“assessed
impact”
projec-on
over
-me;
 or
subjec1vely,
i.e.
by
integra1ng
people’s
“wishes
and
wills”
into
the
decision-­‐
making
process,
to
arrive
at
a
“perceived
impact”
evalua-on
with
the
help
of
the
ci-zens
directly
or
poten-ally
affected
by
the
ac-on’s
results.
 What
is
missing
in
this
scenario
is
the
introduc-on
of
a
permanent,
“evidence
based”,
decision
support
plaGorm,
assisted
by
(though
not
limi-ng
itself
to)
the
use
of
ICT
tools,
and
open
to
the
par-cipa-on
of
a
huge
number
of
people,
not
only
stakeholder
representa-ves,
but
mostly
coming
from
the
general
public
of
a
given
jurisdic-on.

6. 6
Concept
 The
plaHorm
should
offer
to
people
the
possibility
of
ge]ng
immersive
experiences
–
from
which,
the
“experien1al”
aJribute
used
to
name
it
–
during
the
configura-on
and
valida-on
of
future
scenarios
concerning
a
community’s
growth
and
development.
 The
ongoing
evalua-on
of
public
policies
done
through
the
plaHorm
should
reflect
a
pragma1c
combina1on
of
objec1ve
and
subjec1ve
indicators,
thus
responding
seamlessly
and
dynamically
to
the
evolving
needs
and
requirements
of
the
par-cipants,
rather
than
depending
on
the
usual
-me
lags
in
the
collec-on
and
elabora-on
of
performance
related
evidence.
 Finally,
people’s
engagement
in
the
plaHorm
ac-vi-es
should
be
con1nuous
and
uninterrupted,
thus
going
far
beyond
the
occasional,
“one-­‐shot”
experiments
where
ci1zens
are
used
as
“guinea
pigs”
in
a
guided
par-cipatory
environment
and
pathway.

7. 7
Concept
(2)
 The
PaESI
solu-on
comes
from
original
in-­‐house
research
efforts
done
at
our
Company
in
the
framework
of:
1. an
assessment
study
of
the
Living
Labs
“phenomenon”,
promoted
by
the
European
Commission
in
2008,
where
an
updated
version
of
the
MASAI
Approach*
was
developed
and
implemented,
focusing
on
the
transi-on
phase
of
European
Living
Labs
from
R&D
towards
industrially
and
commercially
viable
solu-ons;
2. an
innova1ve
start-­‐up
project
(www.supermoney.eu),
funded
by
the
Italian
Ministry
of
Youth
Innova1on,
which
has
deployed
a
web
service
to
households
and
businesses,
allowing
the
comparison
of
prices
and
other
commercial
condi-ons
of
several
mass
consump-on
goods
and
services
–
from
fixed
and
mobile
telephony
to
the
most
popular
banking
and
insurance
contracts.
 It
also
takes
into
account
the
ongoing
experience
at
FAO
in
the
collec-on
and
delivery
of
livelihood
datasets
(e.g.
hJp://kids.fao.org/glipha/index.html)
* The MASAI basic approach has first been developed by MTA in 2004 and used for a Study of the Impact of the IST Programme, and of its
predecessor Programmes Esprit IV, ACTS, TAP (Contract N° C28262 with DG INFSO).

8. 8
Concept
(3)
 The
PaESI
plaHorm
is
also
based
on
the
no-on
of
“digital
ecosystem”,
a
Living
Lab-­‐like
community
resul-ng
from
a
con-nuous
interac-on
among
the
three
cons-tu-ng
elements
of
any
“real-­‐life”
socio-­‐economic
space:
 -­‐
the
people,
in
their
various
roles
(e.g.
ci-zens,
customers
etc.),
 -­‐
the
(private
and
public)
ins1tu1ons
popula-ng,
delimi-ng
and
regula-ng
the
people’s
living
spaces,
and
 -­‐
the
(natural
and
built)
environment
they
all
live
in.
 Like
any
biological
system,
a
digital
ecosystem
aims
first
to
its
own
growth
and
development,
thanks
to
the
con-nuous
inclusion
and
selec-on
of
new
users
and
interac-on
among
its
cons-tu-ng
elements.
The
system
can
also
let
some
new
and
addi-onal
self-­‐organising
structures
emerge,
which
enhance
its
compe--veness
with
respect
to
other,
less
powerful
or
efficient,
structures.
However,
its
final
target
is
always
to
reach
a
cri-cal
mass,
allowing
the
so-­‐
called
“autopoiesis”,
or
“network
effects”,
typical
of
complex
systems,
a
phenomenon
that
can
be
managed
and
governed
by
the
use
of
appropriate
methods
and
tools.

9. 9
Functional
description
Decision Scenario Scenario Scenario • Ranking of priorities
Makers A B N • Informed decisions
1 • Provision of indicators
• Definition of scenarios
• Feedback
PaESI 3 collection
• Immersive scenarios
Platform for evidence • Shared future visions
based
decision • Transparent alternatives
making
• Self-Profiling
2
• Analysis of indicators
• Selection of scenarios
• Active engagement
Users User User User • Improvement of own
#1 #2 #X
livelihood conditions

10. 10
Functional
description
(2)
 In
its
current
implementa-on,
our
proposed
system
architecture
leverages
on
four
different
components
and
data
sources:
1. an
informa1on
base,
which
is
created
and
configured
since
the
1
project’s
ini1alisa1on,
and
is
then
con-nuously
monitored
and
updated
at
the
level
of
M2M
interac-on,
i.e.
via
a
permanent
dialogue
with
the
customer
organisa-ons’
[ins-tu-ons’]
IT
systems
2. a
computa1onal
model,
framing
the
collec1on,
integra1on
and
localisa1on
of
user
data
(profiles,
indicators,
explicit
and
implicit
preferences,
needs,
requirements
etc.)
and
possibly
environmental
data
2 (deriving
from
available
pieces
of
evidence)
3. user
generated
datasets,
collec-ng
the
inputs
provided
by
the
par-cipants
while
being
put
in
rela-on
with
the
contents
of
the
3
informa-on
base
4
4. system
generated
datasets
(outputs),
offering
on-­‐the-­‐fly
support
to
informed
decision-­‐making.

11. 11
Conclusions
 The
plaHorm
is
being
developed
thanks
to
the
support
of
EU
funding
in
the
context
of
the
CIP
(ICT-­‐PSP)
project
HABITATS.
Its
broad
aim
is
to
leverage
the
intelligence
of
all
relevant
actors,
knowledge
and
datasets,
in
co-­‐designing
sustainable
livelihood
projects
and
programmes.
 We
believe
this
concept
and
plaHorm
can
be
successfully
adapted
to
the
purpose
of
performing
a
par-cipatory
evalua-on
of
the
sustainability
of
innova-on,
as
well
as
providing
a
valid
and
updated
informa-onal
support
to
public
decision
makers
in
a
number
of
related
domains.