This document summarizes lessons learned from open government data projects in Spain and internationally. It discusses the varied approaches taken in different Spanish regions, common concerns raised about open data, and lessons regarding organization, finances, and technology. Key lessons include starting small, identifying champions, performing cost analyses, adapting to existing systems, and addressing concerns about privacy, legal issues and complexity through improved standardization and capacity building. Overall open data projects are increasing and providing success stories, but the full ecosystem of social, economic and political factors must be considered.

1. Open
Government
Data
(approaches,
concerns
and
barriers,
lessons
learned)
Share-­‐PSI
workshop,
10-­‐11
May
2011,
Brussels
José
Manuel
Alonso
CC-­‐BY
2011
CTIC
Centro
Tecnológico

2. Overview
• Context
and
projects
in
Spain
– Variety
of
approaches
• Concerns
heard
– Importance
of
OGD
Ecosystem
• Lessons
learned
(and
food
for
discussion)
– OrganizaTonal
– Financial
– Technical

3. Context: Projects
• Spain
(11
projects
+
3
more
in
the
works)
– 2
Local
– 8
Regional
– 1
NaTonal:
NaTonal
Data
Catalogue
• InternaTonal
(2
projects
+
2
more
in
the
works)
– Feasibility
(in
partnership
with
Web
FoundaTon)
• Chile,
Ghana
– StandardizaTon:
W3C
eGovernment

4. Spain: varied technical approaches
Datasets
Technology
Asturias
Few
5-­‐star
Linked
Data
Basque
Country
Hundreds,
much
low-­‐ All
formats,
RDF
metadata
hanging
fruit
Cataluña
Dozens
All
formats,
some
RDF/XML,
several
APIs,
some
high
quality
Zaragoza
Dozens
All
formats,
some
5-­‐star
Linked
Data,
some
APIs
Gijón
Dozens
All
formats,
some
RDF/XML,
several
APIs,
some
high
quality
Na9onal
Hundreds
from
XLS
to
HTML
pages
to
PDF
reports

5. Spain: varied types of information
Example
Asturias
Hundreds
of
occupaTonal
training
courses
in
Linked
Data
Basque
Country
Database
of
Spanish-­‐Basque
word
and
expression
translaTons
(700Mb)
Cataluña
25.000
geo-­‐located
public
equipments
in
RDF/XML
Zaragoza
Water
cut
offs
in
real
Tme
(GeoRSS)
Gijón
Public
transport
in
real
Tme
(Linked
Data)
Na9onal
A
liele
bit
of
everything

6. Concerns Heard
• Loss
of
licensing
revenue
• Loss
of
control
• Legal
challenges
• Unwelcomed
exposure
• Procedural
changes
• Privacy
• NaTonal
security
• Complexity
• Investment
• Capacity
building
required
• AuthenTcity,
quality
• CorrupTon,
falsificaTon
of
data
• Customer
service
(PosiTves
are
outweighing
the
concerns)

7. OGD Ecosystem: Context is very important
Economical and Business
Macroeconomic Stability
Financial Markets
Markets for Goods and Services Social
Business Environment
Demographics
Labor Market
Quality of Life
Education and Literacy
Infraestructures y Sci-Tech
Innovation
ICT Usage
Infraestructures
Institutional and Political
Governance and Democracy
Transparency and Corruption
Open Access Cooperation
Legal Basis
Awareness and Support
Data and Interoperability
Agents

8. Lessons learned: organizational
• Raise
awareness
• Resistance
to
change
is
a
delicate
issue
– Government
people
tend
to
avoid
risks
(so
keep
them
low)
• (Almost)
no
performance
data
available
• “What
I’m
doing
already
works
well
enough”
• Start
small
and
grow
steadily
• Technology
represents
a
small
percentage
– Much
Tme
spent
on
analyzing
state
of
the
(internal)
art
– Much
internal
outreach
is
needed
• IdenTfy
champions
• Examples
help
– If
they
tell
how
to
improve
lives,
even
beeer
– Beware
of
the
“blinded
by
visualizaTons”,
aka
trivilizaTon
for
the
masses
effect

9. Lessons learned: financial
• Perform
an
informed
cost
analysis
• e.g.
the
18K
EUR
TB
• susteinability
beyond
the
hype
phase
• Beware
of
the
economic
growth
argument
– Re-­‐use
is
not
that
high
– Monitoring
pracTce
so
far
is
not
good
enough
• Downloads?
(and
what
about
entrepreneurships?)
• Improved
Efficiency
– Consolidated
informaTon
• Improved
interoperability
(by
chance?)
• Licensing:
give
the
informaTon
away
for
free
but
be
ready
to
fight
for
doing
so
– Promote
CC-­‐BY
or
CC0
like
licenses
– OGL
great
step
forward

10. Lessons learned: technical
• Raw
data
now…
and
beeer
data
aoerwards
– i.e.
start
with
the
low
hanging
fruit
– improve
over
Tme
(steps)
• Do
not
try
to
enforce
an
specific
architecture
• Chances
are
you
could
not
deploy
it
• Try
to
adapt
to
exisTng
systems
and
build
on
top
of
them
as
a
start
• More
standardizaTon
is
needed
– e.g.
on
vocabularies
– What’s
a
dataset?
What’s
a
catalogue?
• CounTng
datasets
is
bad
• Linked
Data
is
not
easy
but
a
good
tacTc,
needs
improvement
• It
just
doesn’t
work
(semanTc
browsers
examples)
• Beeer
tooling
is
needed
• Capacity
building

11. Conclusions
• The
whole
ecosystem
is
very
important,
don’t
underesTmate
• Concerns
are
sTll
many
but
there
are
some
arguments
to
be
used
• They
need
to
be
addressed
ASAP
anyway
• The
number
of
projects
is
constantly
increasing
and
improving
– Let’s
build
on
success
stories

12. Thank you
• hep://datos.fundacioncTc.org
• hep://www.w3.org/eGov
• hep://www.webfoundaTon.org
• josema.alonso@fundacioncTc.org
• josema@w3.org
• josema@webfoundaTon.org
• @josemalonso