Publish and use your data

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

1st
Summer
School
on

Smart
Ci2es
and
Linked
Open
Data
(LD4SC-‐15)

Hands-‐on
4
Publish
and
use
your
data

Álvaro
Sicilia,
Filip
Radulovic

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Background

•  Álvaro
Sicilia
(asicilia@salleurl.edu)

•  Background:
Computer
Science

•  From:
Architecture,
RepresentaMon
&
ComputaMon
(ARC)

Engineering
and
Architecture
La
Salle
(FUNITEC)

Universitat
Ramon
Llull

Barcelona,
Spain

•  Since
2008
working
with
SemanMc
Web
technologies

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Background

-‐
IntUBE
2008-‐2011
7th
Framework
Programme

Intelligent
use
of
building’s
energy
informa2on

-‐
RÉPENER
2009-‐2012
Spanish
NaMonal
RDI
Plan

Control
and
improvement
of
energy
eﬃciency
in
buildings

through
the
use
of
repositories

-‐
SEMANCO
2011-‐2014
7th
Framework
Programme

Seman2c
Tools
for
Carbon
Reduc2on
in
Urban
Planning

Project
Coordinator:

VTT,
Finland

Project
Coordinator:
ARC
Engineering
and
Architecture
La
Salle,
Spain

Project
Coordinator:
ARC
Engineering
and
Architecture
La
Salle,
Spain

-‐
OPTIMUS
2013-‐2016
7th
Framework
Programme

Op2mising
the
energy
use
in
ci2es
with
smart
decision
support
system

Project
Coordinator:

NaMonal
Technical
University
of
Athens,
Greece

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Index

•  Requirements

•  Guidelines
for
the
PublicaMon
of
Linked
Data

•  Guidelines
for
the
ExploitaMon
of
Linked
Data

•  Hands-‐on
Session

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Linked
Data
life
cycle

Specification
Modelling
GenerationPublication
Exploitation
Linking
5

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Requirements

•  Legal
framework
of
the
dataset

The
publicaMon
of
energy
related
data
requires
that

these
data
are
equipped
with
a
proper
license

framework
in
order
to
be
later
re-‐used
and
exploited
by

the
wide
public.

Linked
Open
Data
legal
compliancy
is
closely
related
to

data
protecMon
issues,
IPR
(Intellectual
Property
Rights)

and
copyright
(legal
enMtlements
for
work
creaMons),

and
privacy.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Requirements

type
License

Comments
Suitability
for

LOD
principles

Public

Domain

CreaMve
Commons

CCZero
(CC0)

-‐
The
least
restricMve
CC
license.

-‐
Removes
all
copyright
restricMons
from
content.

-‐
Can
be
only
applied
by
authors/neighbouring
rights
over
the

content.

-‐
The
Public
Domain
Mark
can
be
applied
by
anyone
to

content
that
is
already
free
of
copyright
restricMons
.

Ideal

Open
Data

Commons
Public

Domain
DedicaMon

and
Licence
(PDDL)

-‐
Allows
data
and
database
unrestricted
sharing,
reuse,

reproducMon
and
adapMon
with
no
restricMons.

AfribuMon

AfribuMon

CreaMve
Commons

AfribuMon
4.0
(CC-‐
BY-‐4.0)

-‐
Allows
the
users
to
copy
or
remix
the
work
in
any
way.

-‐
The
users
must
afribute
the
work
to
the
original
creator.

-‐
The
creator
should
provide
a
link
to
the
CreaMve
Commons

page
explaining
the
user’s
responsibiliMes
and
provide
an

easily-‐accessed
list
of
creators.

AfribuMon

requirements

may
lead
to

afribuMon

stacking

Open
Data

Commons

AfribuMon
License

(ODC-‐BY)

-‐
Allows
users
to
copy,
distribute,
and
use
the
database.

-‐ Allows
users
to
produce
works
from
the
database,
modify,

transform
and
built
upon
the
database.

-‐ 
Users
must
afribute
any
public
use
of
the
database
or
works

produced
from
the
database
and
make
clear
to
others
the

license
of
the
database
.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Requirements

type
License

Comments
Suitability
for
LOD

principles

AfribuMon

Share-‐Alike

CreaMve
Commons

AfribuMon
Share-‐
Alike
4.0
(CC-‐BY-‐
SA-‐4.0)

-‐ 
AfribuMon
restricMons
are
applied.

-‐ 
Users
transforming
the
work
into
something
new
must

distribute
that
work
under
the
CC
BY-‐SA
license,
or
a

similarly
open
license.

AfribuMon

requirements
may

lead
to
afribuMon

stacking.

Share-‐alike

requirements
may

lead
to

interoperability

issues

Open
Data

Commons
Open

Database
License

(ODbL)

-‐ 
Users
must
keep
the
database
open
technologically
and

oﬀer
any
adapted
version
of
the
database
or
works

produced
from
it
under
the
ODbL.

-‐ 
Limited
commercial
reuse
of
the
database
or
its
contents.

-‐
A
separate
Database
Contents
License
(DbCL)
to
the

contents
of
a
database
licensed
under
ODbL,
which
waives

all
rights
in
the
individual
contents.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Requirements

+
Easy
to
use

+
Widespread
adopted

+
Flexible

+
Available
to
human
&machine
readable
forms

+
Direct
links
between
the
resource
and
its
license

+
Symbolic
representaMon
of
the
license
to
recognize
usage
terms

-‐CC
licenses
are
copyright
based
and
designed
to
protect
creaMve

works
(content)
–
databases
are
not
creaMve
works
but
facts
of
this

work

-‐
Third
party
rights
material
included
in
the
data
may
require

addiMonal
clearances
and
is
not
provided
as
informaMon
in
the
license

-‐Cannot
be
revoked
once
applied.
CC
licenses
and
ODC-‐By
as
well
as

ODC-‐ODbl
are
irrevocable

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Requirements

•  Quality
requirements
according
to
ISO/IEC
25012

-‐ 
Accuracy:

-‐ 
The
publishing
dataset
must
be
semanMcally
and

syntacMcally
accurate.

-‐
The
dataset
should
not
contain
repeatedly

redundant
values.

-‐
Accuracy
is
also
expected
for
the
reuse
of
the

published
dataset.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Requirements

•  Quality
requirements
according
to
ISO/IEC
25012

-‐ 
Completeness:

-‐ 
The
data
items
published
are
necessary
to
support

the
applicaMon
for
which
it
is
intended.

-‐ 
Consistency:

-‐ 
The
dataset
before
published
should
be
complete

and
consistent.

-‐
ConﬂicMng
statements
and
errors
should
be

detected
before
publicaMon.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Requirements

•  Quality
requirements
according
to
ISO/IEC
25012

-‐ 
Credibility:

-‐ 
Linked
Open
Data
must
be
credible
and
fully
compliant
with

the
license,
policy
and
terms
of
use
derived
from
the

provenance
source.

-‐ 
Agreements
and
afribuMons
should
be
deﬁned
where

appropriate
to
clarify
users
whether
they
can
or
cannot
trust

the
data.

-‐ 
Timeless:

-‐ 
The
publicaMon
process
should
be
designed
for
its

maintenance.

-‐ 
The
dataset
should
be
Mmelessly
handled
by
the

responsible
dataset
supporter
in
order
to
maintain,
update

and
enable
the
usage
and
exploitaMon
of
data.

-‐ 
The
processes
and
tools
should
be
able
to
support

maintaining
the
dataset
over
Mme

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Requirements

•  Requirements
according
to
AENOR
PNE
178301

standard
on
Smart
Ci2es
and
Open
Data

-‐ Open
data
must
be
published
through
persistent
URLs

and
using
standard,
structured,
open,
and
non-‐
proprietary
formats
that
allow
the
unique
idenMﬁcaMon

of
resources.

-‐ Vocabularies
used
in
open
data
must
be
published

online
through
persistent
URLs.

-‐
Open
datasets
must
be
included
in
relevant
open
data

catalogues.

-‐
The
organizaMon
must
promote
the
reuse
of
open

data
by
providing
supporMng
documents
and
materials.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Requirements

•  Requirements
according
to
AENOR
PNE
178301

standard
on
Smart
Ci2es
and
Open
Data

-‐ Open
data
must
be
available
by
downloading
the

respecMve
ﬁles
and
through
web
APIs
or
SPARQL

endpoints.

-‐ Non-‐discriminatory
access
to
open
data
must
be

ensured
by:
not
requiring
administraMve
procedures
or

user
registraMon
and
by
guaranteeing
equal
rights,
non-‐
discriminaMon
and
accessibility.
AdministraMve

procedures
or
user
registraMon
could
be
allowed
in

jusMﬁed
cases.

-‐ 
The
access
and
use
of
open
data
must
be
periodically

measured.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Requirements

•  Requirements
according
to
AENOR
PNE
178301

standard
on
Smart
Ci2es
and
Open
Data

-‐ Open
data
must
be
documented
using
metadata.

-‐ Vocabularies
used
in
open
data
must
be
documented

using
metadata.

-‐ 
Open
data
licenses
and
use
condiMons
must
be

documented
and
published
online.

-‐ 
Open
data
licenses
must
be
standard,
self-‐
documented,
based
on
exisMng
standards,
and

preferably
in
a
machine-‐processable
format.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Requirements

Requirements
summary:

•  Legal
compliance
aspects
à
rights
protecMon,

license
terms

•  Quality
of
data
and
metadata
!
accuracy,

completeness,
consistency,
credibility,
and

sustainability

•  Publica2on
requirements
!
data
and
vocabularies

accessible

•  Social
requirements
!
maintenance
and
promoMon

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Index

•  Requirements

•  Guidelines
for
the
Publica2on
of
Linked
Data

•  Guidelines
for
the
ExploitaMon
of
Linked
Data

•  Hands-‐on
Session

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Linked
Data
life
cycle

Specification
Modelling
Exploitation
Linking
18

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Ensure
Legal
compliance

Two
possible
cases:

a)  RDF
dataset
is
generated
from
a
data
source
that
permits
the

use
of
the
data,
and
when
the
publicaMon
of
the
produced

RDF
dataset
complies
to
the
license
and
legal
terms
of
the

original
data
source

à
RDF
dataset
can
be
published
without
obstacles

b)  Or,
to
ensure
legal
compliance.
Usually,
legal
aspects
can
be

addressed
by
preserving
the
privacy
of
the
data

à
data
anonymizaMon

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Ensure
Legal
compliance
!
Data
anonymiza2on

Privacy-‐preserving
data
publishing
:

a)  Explicit
idenMﬁers
are
afributes
that
explicitly
idenMfy
the
enMty

of
interest
(e.g.,
id
of
a
person,
property
number
of
a
building)

b)  Quasi
idenMﬁers
(QID)
are
sets
of
afributes
that
can
potenMally

idenMfy
the
enMty
of
interest.
(e.g.,
date
of
birth,
postal
code,

gender…)

Radulovic
F.,
García-‐Castro
R.,
Gómez-‐Pérez
A.:
Towards
the
AnonymisaMon
of
RDF
Framework.
In
Proceedings
of
the
27th
InternaMonal

Conference
on
Sotware
Engineering
and
Knowledge
Engineering
(SEKE2015),
Pifsburg,
Pennsylvania,
USA.
July
2015.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Ensure
Legal
compliance
!
Data
anonymiza2on

Techniques:

•  Suppression
is
a
technique
in
which
some
values
or
complete

records
in
a
dataset
are
replaced
with
some
other
specific
value

or
record.

Id
Building
use
Consump2on

1
School
12352

2
ResidenMal
2334

3
School
15121

4
Office
5252

Id
Building
use

1
School

2
ResidenMal

3
School

4
Office

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Ensure
Legal
compliance
!
Data

anonymiza2on

Techniques:

•  Generaliza2on
is
a
technique
that
transforms
pieces
of
data

into
more
general
data
or
sets
of
data,
and
is
suited
for

transformaMon
of
categorical
afributes
and
discrete
numerical

afributes
à
use
of
postal
codes
instead
of
addresses,
use

range
of
values
instead
of
speciﬁc
values

Id
Postal
Code
Consump2on

1
08006
12352

2
08022
2334

3
08021
15121

Id
Postal
Code
Consump2on

1
0800*
12352

2
0802*
2334

3
0802*
15121

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Ensure
Legal
compliance
!
Data

anonymiza2on

Techniques:

•  Generaliza2on
is
a
technique
that
transforms
pieces
of
data

into
more
general
data
or
sets
of
data,
and
is
suited
for

transformaMon
of
categorical
afributes
and
discrete
numerical

afributes
à
use
of
postal
codes
instead
of
addresses,
use

range
of
values
instead
of
speciﬁc
values

Id
Postal
Code
Consump2on

1
08006
12352

2
08022
2334

3
08021
15121

Id
Postal
Code
Consump2on

1
08006
10k-‐14k

2
08022
1k-‐5k

3
08021
14k-‐20k

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Ensure
Legal
compliance
!
Data
anonymiza2on

Techniques:

•  Data
aggrega2on:
For
example
aggregate
energy
consumpMon

of
buildings
by
type
of

buildings

Id
Building
use
Consump2on

1
School
12352

2
ResidenMal
2334

3
School
15121

4
Office
5252

5
Office
5623

6
ResidenMal
3452

Building
use
Total
Consump2on

School
13736

ResidenMal
2893

Office
5437

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Ensure
Legal
compliance
!
Data
anonymiza2on

Techniques:

•  Data
aggrega2on:
For
example
aggregate
energy
consumpMon

of
buildings
by
type
of

buildings

Id
Building
use
Consump2on

1
School
12352

2
ResidenMal
2334

3
School
15121

4
Office
5252

5
Office
5623

6
ResidenMal
3452

Building
use
Ave.
Consump2on

School
6836

ResidenMal
1443

Office
2677

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Ensure
Legal
compliance
!
Data
anonymiza2on

Techniques:

•  Anatomiza2on
and
permuta2on
are
techniques
that,
unlike

suppression
and
generalizaMon,
do
not
modify
the
data
but

rather
remove
the
relaMonship
between
the
quasi
idenMfiers
and

sensiMve
values.

•  Perturba2on
is
a
technique
in
which
original
data
are
replaced

with
noise
or
syntheMc
data
in
such
a
way
that
staMsMcal

analyses
based
on
the
perturbed
data
do
not
significantly
differ

from
the
staMsMcal
analysis
of
the
original
data.
à
to
replace

observed
values
with
the
average
computed
on
a
small
group
of

units

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Ensure
Legal
compliance
!
Data
anonymiza2on

Steps
to
ensure
legal
aspects
of
the
dataset

1.  To
iden2fy
explicit
idenMfiers,
quasi
idenMfiers,
and
sensiMve

afributes
in
the
dataset.

2.  To
select
the
techniques
to
use
on
the
previously
idenMfied

afributes
in
order
to
ensure
legal
compliance.

3.  To
apply
the
selected
techniques
over
the
idenMfied
afributes.

4.  To
modify
the
ontology.
In
the
case
that
data
anonymizaMon

implies
some
changes
in
the
data
model

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Ensure
Legal
compliance
!
Examples

Leeds
City
Council
example

energy
consumpMon
of
council
sites
within
the
Leeds

jurisdicMon
is
licensed
under
the
Open
Government
License,

which
permits
the
use
and
modiﬁcaMon
of
the
data

à
it
is
not
necessary
to
perform
any
addiMonal
step
in
order

to
ensure
legal
compliance

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Ensure
Legal
compliance
!
Examples

BECA
energy
consump2on
example

Needed
anonymizaMon:

QIDs
and
sensi2ve
a`ributes

Anonymiza2on
Technique

{evaluaMon
number}

{tenant
idenMfier}

{residence
idenMfier}

QIDs.
Those
afributes
will
be
generalized
(e.g.,
value
35698456

is
generalized
to
356*****).

{building
idenMfier,
residence
idenMfier,

tenant
number}

QID.
Since
residence
idenMfier
is
already
generalized,

addi2onal
generaliza2on
will
be
performed
for
tenant
number

{comment}

QID
because
in
some
cases
it
contains
informaMon
about

tenant
idenMfiers
in
natural
language.
Therefore,
this
afribute

will
be
completely
suppressed.

{evaluaMon
number,
residence
size}

The
residence
size
afribute
will
be
generalized
by
taking
into

account
the
interval
to
which
the
size
belongs
to
and
then
by

assigning
the
mean
value
of
the
interval
(e.g.,
if
the
size
of

residence
is
38
square
meters,
the
corresponding
interval
is

30-‐49
and,
therefore,
value
35
will
be
assigned).

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Publish
the
dataset
and
the
ontology

The
goal
of
this
step
is
to
make
accessible
through
the
Web
the

ontology
and
the
RDF
dataset
following
Linked
Data
principles.

1.  Use
URIs
to
name
(idenMfy)
things.

2.  Use
HTTP
URIs
so
that
these
things
can
be
looked
up

(interpreted,
"dereferenced").

3.  Provide
useful
informaMon
about
what
a
name
idenMﬁes

when
it's
looked
up,
using
open
standards
such
as
RDF,

SPARQL,
etc.

4.  Refer
to
other
things
using
their
HTTP
URI-‐based
names

when
publishing
data
on
the
Web.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Publish
the
dataset
and
the
ontology

Steps:

1.  To
store
the
RDF
data
into
a
persistent
repository
where

data
can
be
then
accessed
and
queried
à
RDF
repository

2.  To
enable
resolvable
HTTP
URIs
and
content
negoMaMon,

i.e.,
the
mechanisms
for
accessing
the
data
through
the

Web.

3.  To
enable
a
SPARQL
HTTP
endpoint.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Publish
the
dataset
and
the
ontology

Steps:

1.  To
store
the
RDF
data
into
a
persistent
repository
where

data
can
be
then
accessed
and
queried
à
RDF
repository

dataset

Rdf

dump

Triple
store

Sparql

queries

dataset
SQL

RDF

wrapper

Sparql

queries

•  Fast

•  Not
up
to
date

•  Not
fast

•  Updated

R2RML
mappings
Rela/onal

database

Virtuoso
server

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Publish
the
dataset
and
the
ontology

Steps:

2.  To
enable
resolvable
HTTP
URIs
and
content
negoMaMon,
i.e.,

the
mechanisms
for
accessing
the
data
through
the
Web

Pubby:
Image
taken
from:

hfp://wifo5-‐03.informaMk.uni-‐mannheim.de/pubby/

Humans
à
HTML
content

Computers
à
RDF
content

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Publish
the
dataset
and
the
ontology

Steps:

2.  To
enable
resolvable
HTTP
URIs
and
content
negoMaMon,
i.e.,

the
mechanisms
for
accessing
the
data
through
the
Web

PUBBY
conﬁgura2on

Go
to:

tomcat/webapps/pubby/
WEB-‐INF/conﬁg.n3

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Publish
the
dataset
and
the
ontology

Steps:

2.  To
enable
resolvable
HTTP
URIs
and
content
negoMaMon,
i.e.,

the
mechanisms
for
accessing
the
data
through
the
Web

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon
Content
nego2a2on:
HTML
"
for
humans

Content
nego2a2on:
RDF
"
for
computers

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Publish
the
dataset
and
the
ontology

Steps:

2.  To
enable
resolvable
HTTP
URIs
and
content
negoMaMon,

i.e.,
the
mechanisms
for
accessing
the
data
through
the

Web

Alterna2ves:

• Linked
Data
API

!
Elda
or
Puelia

• W3C
Linked
Data
Plaeorm
(LDP)
speciﬁca2on

!
LDP4j
or
Apache
Marmo`a

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Publish
the
dataset
and
the
ontology
!
Examples

Leeds
City
Council
&
BECA
energy
consump2on
examples

1.  RDF
dataset
à
Openlink's
Virtuoso
Open
Source
repository.

Ontology
à

hfp://smartcity.linkeddata.es/lcc/ontology/EnergyConsumpMon#,

hfp://smartcity.linkeddata.es/BECA/ontology/EnergyConsumpMon#

2.  HTTP
access
to
the
data
à
Linked
Data
API
(ELDA)

3.  SPARQL
endpoint
à
Virtuoso
at
hfp://smartcity.linkeddata.es/lcc/sparql

hfp://smartcity.linkeddata.es/BECA/sparql

RDF
dumps
à

hfp://smartcity.linkeddata.es/lcc/lcc-‐dataset.fl

hfp://smartcity.linkeddata.es/BECA/BECA-‐dataset.fl

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Publish
metadata
and
online
documenta2on

The
goal
of
this
step
is
to
create
and
publish
the
documentaMon

of
the
RDF
dataset
and
the
ontology.

This
documentaMon
is
oriented
to
both
humans
and
machines

and
its
purpose
is
to
facilitate
the
usage
of
the
dataset
that
is

being
made
available.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Publish
metadata
and
online
documenta2on

To
create
and
publish
human-‐readable
metadata
descripMons:

To
create
and
publish
a

human-‐readable

documentaMon
of
dataset

and
ontology.

Providing
documentaMon

about
the
dataset
and
the

ontology
can
ease
the
data

usage
to
consumers

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Publish
metadata
and
online
documenta2on

To
create
and
publish
machine-‐readable
metadata
descripMons:

Two
vocabularies
published
by
the
W3C
allow
describing
datasets

and
data
catalogues
in
RDF:

-‐ 
VoID
(Vocabulary
of
Interlinked
Datasets)

-‐ 
DCAT
(Data
Catalogue
Vocabulary)

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Publish
metadata
and
online
documenta2on

To
create
and
publish
machine-‐readable
metadata
descripMons:

-‐
DCAT
(Data
Catalogue
Vocabulary)

@prefix
os:

<hfp://a9.com/-‐/spec/opensearch/1.1/>
.

@prefix
dct:

<hfp://purl.org/dc/terms/>
.

@prefix
xsd:

<hfp://www.w3.org/2001/XMLSchema#>
.

@prefix
api:

<hfp://purl.org/linked-‐data/api/vocab#>
.

@prefix
rdf:

<hfp://www.w3.org/1999/02/22-‐rdf-‐syntax-‐ns#>
.

@prefix
xhv:

<hfp://www.w3.org/1999/xhtml/vocab#>
.

<h`p://smartcity.linkeddata.es/lcc>

a

dct:Dataset
;

dct:license

<h`p://purl.org/NET/rdflicense/ukogl1.0>;

dct:source

“We
acknowledge
that
this
dataset
uses
data
coming
from
the
Leeds
City
Council
by
including,
please

check
the
machine-‐readable
licenses
provided
here
and
further
informa2on
at

h`p://www.leeds.gov.uk/opendata/pages/developer-‐datasets.aspx"
;

<hfp://www.w3.org/2002/07/owl#sameAs>

<h`p://datahub.io/dataset/lcc-‐leeds-‐city-‐council-‐energy-‐consump2on-‐linked-‐data>
.

dct:publisher

“The
publisher
of
the
dataset”;

dct:language

<h`p://id.loc.gov/vocabulary/iso639-‐1/en>

;

dct:accrualPeriodicity

<h`p://purl.org/linked-‐data/sdmx/2009/code#freq-‐W>

;

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Publish
metadata
and
online
documenta2on

To
create
and
publish
machine-‐readable
metadata
descripMons:

-‐
VoID
(Vocabulary
of
Interlinked
Datasets)

@prefix
rdf:
.

@prefix
rdfs:
<hfp://www.w3.org/2000/01/rdf-‐schema#>
.

@prefix
foaf:
<hfp://xmlns.com/foaf/0.1/>
.

@prefix
dcterms:
.

@prefix
void:
<hfp://rdfs.org/ns/void#>
.

@prefix
xsd:
.

##
your
dataset

<h`p://your.dataset.com/>
rdf:type
void:Dataset
;

foaf:homepage
<h`p://your.dataset.com/homepage>
;

dcterms:Mtle
“Title
of
your
dataset"
;

dcterms:descripMon
“Descrip2on
of
your
dataset."
;

void:sparqlEndpoint
<h`p://your.dataset.com/sparql>
;

void:uriSpace
"h`p://your.dataset.com/resource/";

void:exampleResource
<h`p://your.dataset.com/resource/URI/XXXX>
.

dcterms:source
"
Descrip2on
of
the
dataset
source"
;

dcterms:created
“XXXX-‐XX-‐XX"^^xsd:date;

dcterms:license
<h`p://crea2vecommons.org/licenses/by/3.0/>

dcterms:subject
<h`p://dbpedia.org/resource/Building>;

void:triples
150297
;

void:enMMes
18890
;

void:classes
65
;

void:properMes
100
;

void:disMnctSubjects
18962
;

void:disMnctObjects
26097
;

##
datasets
you
link
to

:Anotherdataset
rdf:type
void:Dataset
;

foaf:homepage
<
h`p://another.dataset.com/homepage>
;

dcterms:Mtle
“Another
2tle"
;

dcterms:descripMon
“Another
descrip2on."
;

<
h`p://another.dataset.com/resource/URI/XXXX
>
.

:Yourdataset-‐Anotherdataset
rdf:type
void:Linkset
;

void:linkPredicate
<h`p://your.dataset.com/predicate
used
for
linking>
;

void:target
;

void:target
:Anotherdataset
.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Publish
metadata
and
online
documenta2on
!

Examples

Leeds
City
Council
example

DCAT
descripMon:
hfp://smartcity.linkeddata.es/lcc/dcat.fl

Ontology:
hfp://smartcity.linkeddata.es/lcc/ontology/EnergyConsumpMon/

BECA
energy
consump2on
example

DCAT
descripMon:
hfp://smartcity.linkeddata.es/BECA/dcat.fl

Ontology:
hfp://smartcity.linkeddata.es/BECA/ontology/EnergyConsumpMon

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Enable
dataset
discovery

to
enable
the
mechanisms
to
complement
the
eﬀorts
from
the

previous
step
and
to
allow
both
human
and
machines
to
discover

and
befer
use
the
dataset.

1.  To
create
a
sitemap.

2.  To
register
the
dataset
in
a
dataset
catalogue.

3.  To
ensure
the
fulﬁllment
of
requirements
for
addiMon
to
the

LOD
cloud.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Enable
dataset
discovery

1.  To
create
a
sitemap.

A
sitemap
is
a
mechanism
to
inform
search
engines
about
the

page
structure
of
a
certain
web
site
in
order
to
allow
for
a
more

eﬃcient
crawling.

It
is
widely
used
and
adopted
by
major
search
engines
and
it
is

therefore
recommended
for
any
type
of
web
site
including

datasets.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Enable
dataset
discovery

1.  To
create
a
sitemap
with
sitemap4rdf.

There
are
tools
like
sitemap4rdf
that
can
generate
a
sitemap

based
on
the
contents
of
a
sparql
endpoint:

hfp://lab.linkeddata.deri.ie/2010/sitemap4rdf/

sitemap4rdf
{your_sparql_endpoint}
{preﬁx_of
your_url}

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Enable
dataset
discovery

1.  To
create
a
sitemap
with
sitemap4rdf.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Enable
dataset
discovery

2.  To
register
the
dataset
in
a
dataset
catalogue.

There
are
available
several
online
data
catalogues
that
range

from
general
to
corporate
iniMaMves:

-‐Datahub:
this
data
management
pla„orm
covers
a
wide
range
of
topics.
It
offers
data

collecMons,
some
of
which
are
linked
and
open.

-‐
Reegle:
the
gateway
has
already
established
itself
as
a
popular
informaMon
portal
in
the

fields
of
renewable
energy
and
energy
efficiency.
It
offers
all
of
its
data
under
W3C

standards,
i.e.,
it
is
open
and
Linked
Data
in
a
non-‐proprietary
format
(RDF).

-‐
OpenEI:
a
collaboraMve
knowledge-‐sharing
pla„orm
with
free
and
open
access
to

energy-‐
related
data,
models,
tools,
and
informaMon.
OpenEI
features
over
55,000

content
pages,
more
than
600
downloadable
datasets,
regional
gateways
on
a
variety
of

energy-‐related
topics,
and
numerous
online
tools.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Enable
dataset
discovery

2.  To
register
the
dataset
in
a
dataset
catalogue.

There
are
available
several
online
data
catalogues
that
range

from
general
to
corporate
iniMaMves:

-‐DataCatalogs:
a
comprehensive
list
of
open
data
catalogues
in
the
world
including

representaMves
from
local,
regional
and
naMonal
governments,
internaMonal

organisaMons
and
numerous
NGOs.
NaMonal
energy
related
data
are
contained
in
the

listed
datasets.

-‐
Google
Public
Data:
a
corporate
iniMaMve
for
large
datasets
publicaMon
enabling

exploraMon
easiness,
visualizaMon
and
communicaMon.

-‐
READY4SmartCi2es:
One
of
the
direct
outcomes
of
the
project
is
a
web-‐portal
providing

an
extended
list
of
ontologies
and
datasets
for
smart
ciMes
published
both
in
human-‐
readable
(HTML
web
site)
and
machine-‐processable
(RDF
Format)
formats.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Enable
dataset
discovery

2.  To
register
the
dataset
in
a
dataset
catalogue.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Enable
dataset
discovery

3.  To
ensure
the
fulﬁllment
of
requirements
for
addiMon
to
the
LOD

cloud.

The
dataset
is
checked
with
the
record
validator

(hfp://
validator.lod-‐cloud.net)
provided
by
the
LOD
cloud
website.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Enable
dataset
discovery

3.  To
ensure
the
fulﬁllment
of
requirements
for
addiMon
to
the
LOD

cloud.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Dataset
promo2on

The
promoMon
is
important
in
order
to
ensure
that
people
are
aware
of

the
existence
of
the
dataset
and
to
ensure
its
usage.

This
way
it
can
be
used
by
third-‐parMes
by
querying,
linking
to
other

datasets
and
visualizing.

The
dataset
can
be
promoted
using
diﬀerent
channels:
Twifer,
LinkedIn,

Mailing
lists,
Workshops,
Conferences,
VoCamps….

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
publicaMon

Data
set
support

Dataset
support
is
a
conMnuous
process
in
which
the
creators
and

publishers
of
the
dataset
provide
support
in
terms
of
possible
errors

correcMon
(both
related
to
data
themselves
and
technical
errors),

data
updates
in
the
case
that
new
data
become
available,
and

technical
support
in
terms
of
solving
any
problem
that
can
aﬀect
the

accessibility
of
the
dataset.

Dataset
support
is
usually
provided
by
the
persons
that
parMcipated

in
data
generaMon
and
publicaMon.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Index

•  Requirements

•  Guidelines
for
the
PublicaMon
of
Linked
Data

•  Guidelines
for
the
Exploita2on
of
Linked
Data

•  Hands-‐on
Session

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Linked
Data
life
cycle

Specification
Modelling
Exploitation
Linking
64

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

Generic
Linked
Data
use
cases

Use
Case
1
-‐
SME
use
of
public
Linked
Energy
Data

Contributors:
Filip
Radulovic
(UPM)

Use
of
different
energy
related
data
sources
such
as
energy
consumpMon,

weather
condiMons,
building

and
HVAC
system
features,
socio-‐economic

indicators...
To
enable
SMEs
to
develop
new
business
models.

LD
benefits:
data
integraMon/interlinking,
data-‐driven
decision-‐making.

Challenges:

•
Manual
access
to
data.

•
Obtaining
heterogeneous
data
from
various
sources.

•
Different
data
formats
and
structures.

•
Dynamically
updated
data.

•
Instance
specific
data
with
different
detail
levels.

•
No
open
license
associated
with
data.

•
Data
not
available
for
reuse.

•
Privacy
protecMon.

•
ParMal
or
missing
data.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

Generic
Linked
Data
use
cases

Use
Case
1
-‐
SME
use
of
public
Linked
Energy
Data

EECITIES
example

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Use
Case
1
-‐
SME
use
of
public
Linked
Energy
Data

Data
connected
through
the

Seman&c
Energy
Informa&on

Framework

Energy
assessment
(SAP,
UEP…)
Energy
simulaMon
(URSOS,
…)

Energy
analysis
(data
mining,..)

GIS
model
(geometric
data)

DATA
TOOLS

CADASTER

GIS

ENERGY
PERFORMANCE

SOCIOECONOMIC

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Use
Case
1
-‐
SME
use
of
public
Linked
Energy
Data

Once
a
baseline
reflec2ng
the
current
state
of
the
urban
energy
model
has

been
created,
different
visualiz2on
tools
can
be
used
to
iden2fy
problem

areas.

Cluster
view
Table
view

Performance
indicators

filtering

Mul2ple
scale
visualiza2on

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Use
Case
1
-‐
SME
use
of
public
Linked
Energy
Data

informa2on
concerning
the
selected
building
which
have
not
yet
assessed

Building
geometry
obtained
from
the

3D
model

Street
address
obtained
from

Google
GeolocaMon
services

Performance
values
to
be

calculated
with
energy

assessment
tool

Year
of
construcMon
obtained
from

the
cadastre

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Use
Case
1
-‐
SME
use
of
public
Linked
Energy
Data

Interface
of
the
URSOS
tool.
The
input
data
is
automa2cally
ﬁlled
thanks
to
the

seman2c
integra2on
of
diﬀerent
data
sources.
Users
can
modify
the
input
data
in
case

there
are
errors.

Year
of
construcMon

from
the
Cadastre

Geometry
obtained
from
the
3D
model

Street
address
name
and

Street
view
from
Google

GeolocaMon
services

Wall,
ground
and
roof

properMes
from
the
building

typologies
database

VenMlaMon
from
the
building

typologies
database

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Use
Case
1
-‐
SME
use
of
public
Linked
Energy
Data

URSOS
Energy

calcula2on
engine

GIS
data

Census
Cadastre
Climate

Typology
Socio-‐Economic

Energy-‐related
data
Seman2c
Energy

Informa2on
Framework

Integrated
Plaeorm

ELITE

Federa&on
engine

Ontology

OWL-‐DL
liteA

URSOS
Input
form

3D
Maps

1
2
3 5
4

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Use
Case
1
-‐
SME
use
of
public
Linked
Energy
Data

URSOS
Energy

calcula2on
engine

GIS
data

Census
Cadastre
Climate

Typology
Socio-‐Economic

Energy-‐related
data
Seman2c
Energy

Informa2on
Framework

Integrated
Plaeorm

ELITE

Federa&on
engine

Ontology

OWL-‐DL
liteA

URSOS
Input
form

3D
Maps

1
2
3 5
41.  The
user
selects
a
building

2.  The
ID
of
the
selected

building
is
used
to
retrieve

the
building
parameters
form

the
data
sources
using

SPARQL:

Cadastre

Census

Building
typologies

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Use
Case
1
-‐
SME
use
of
public
Linked
Energy
Data

URSOS
Energy

calcula2on
engine

GIS
data

Census
Cadastre
Climate

Typology
Socio-‐Economic

Energy-‐related
data
Seman2c
Energy

Informa2on
Framework

Integrated
Plaeorm

ELITE

Federa&on
engine

Ontology

OWL-‐DL
liteA

URSOS
Input
form

3D
Maps

1
2
3 5
41.  The
user
selects
a
building

2.  The
ID
of
the
selected

building
is
used
to
retrieve

the
building
parameters
form

the
data
sources
using

SPARQL:

Cadastre

Census

Building
typologies

prefix sumo: <http://www.ontologyportal.org/SUMO.owl#>
prefix semanco: http://www.semanco-project.eu/2012/5/SEMANCO.owl#
SELECT DISTINCT ?year
WHERE {
?b a sumo:Building;
semanco:hasAge [semanco:year_Of_ContructionValue ?year];
semanco:hasBuilding_Cadastral_Data [semanco:hasCadastral_Reference ?ref].
?ref semanco:cadref1Value "2402012".
}

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Use
Case
1
-‐
SME
use
of
public
Linked
Energy
Data

URSOS
Energy

calcula2on
engine

GIS
data

Census
Cadastre
Climate

Typology
Socio-‐Economic

Energy-‐related
data
Seman2c
Energy

Informa2on
Framework

Integrated
Plaeorm

ELITE

Federa&on
engine

Ontology

OWL-‐DL
liteA

URSOS
Input
form

3D
Maps

1
2
3 5
41.  The
user
selects
a
building

2.  The
ID
of
the
selected

building
is
used
to
retrieve

the
building
parameters
form

the
data
sources
using

SPARQL:

Cadastre

Census

Building
typologies

prefix semanco: <http://www.semanco-project.eu/2012/5/SEMANCO.owl#>
SELECT DISTINCT ?age ?to ?from
WHERE {
?age a semanco:Age_Class .
?age semanco:hasTo_Year ?age_to_instance .
?age_to_instance semanco:toYearValue ?to .
filter(?to >= '1885') .
?age semanco:hasFrom_Year ?age_from_instance2 .
?age_from_instance2 semanco:fromYearValue ?from .
filter(?from <= '1885') .
}
WHERE {
?b a sumo:Building;
}

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Use
Case
1
-‐
SME
use
of
public
Linked
Energy
Data

URSOS
Energy

calcula2on
engine

GIS
data

Census
Cadastre
Climate

Typology
Socio-‐Economic

Energy-‐related
data
Seman2c
Energy

Informa2on
Framework

Integrated
Plaeorm

ELITE

Federa&on
engine

Ontology

OWL-‐DL
liteA

URSOS
Input
form

3D
Maps

1
2
3 5
41.  The
user
selects
a
building

2.  The
ID
of
the
selected

building
is
used
to
retrieve

the
building
parameters
form

the
data
sources
using

SPARQL:

Cadastre

Census

Building
typologies

SELECT DISTINCT ?age ?to ?from
WHERE {
?age a semanco:Age_Class .
?age semanco:hasTo_Year ?age_to_instance .
?age_to_instance semanco:toYearValue ?to .
filter(?to >= '1885') .
?age semanco:hasFrom_Year ?age_from_instance2 .
?age_from_instance2 semanco:fromYearValue ?from .
filter(?from <= '1885') .
}
WHERE {
?b a sumo:Building;
}
SELECT DISTINCT ?uvalue
where {
?b semanco:hasSpace [ semanco:hasCS_Envelope [semanco:hasBottom_Floor ?bf]];
semanco:hasAge <http://www.semanco-project.eu/manresa/age_class/1>.
?bf semanco:hasBottom_Floor_U-value [semanco:bottom_Floor_U-valueValue ?uvalue].
?bf semanco:hasBottom_Floor_Type [semanco:bottom_Floor_TypeValue "Bottom"].
}

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Use
Case
1
-‐
SME
use
of
public
Linked
Energy
Data

Applying
improvements.
For
example,
renova2ng
the
exis2ng
windows

or
replacing
them
with
new
ones

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Use
Case
1
-‐
SME
use
of
public
Linked
Energy
Data

Results
aqer
applying
the
improvement
measures

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Use
Case
1
-‐
SME
use
of
public
Linked
Energy
Data

Projects
can
be
compared
with
a
mul2-‐criteria
decision
tool
included
in
the

plaeorm.
Users
can
select
the
weight
(importance)
of
the
performance
indicators.

Besides,
other
indicators
deﬁned
by
users
can
be
included
in
the
analysis,
for

example:
foreseen
funding.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Use
Case
1
-‐
SME
use
of
public
Linked
Energy
Data

Services:
•  Assessing the current energy performance of buildings in towns and cities.
•  Identifying priority areas and buildings for energy efficiency interventions.
•  Evaluating the impact of proposed new buildings at the urban level.
•  Evaluating the impact of refurbishing buildings at the urban level.
•  Evaluating the impact of potential of local policies and interventions on
Sustainable Energy Action Plans (SEAP).
•  Generating missing data to enable the classification of buildings according to
their energy performance.
•  Integrating new data to be visualized and analysed.
SERVICE PLATFORM TO SUPPORT PLANNING
OF ENERGY EFFICIENT CITIES
www.eeciMes.com

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

Generic
Linked
Data
use
cases

Use
Case
2
-‐
The
energy
data
portal

Contributors:
Filip
Radulovic
(UPM)

The
energy
portal
is
a
portal
that
integrates
energy
data
and
provides
access
to

various
energy
indicators
from
different
data
sources
(e.g.,
heaMng
consumpMon,

water
consumpMon,
electricity
consumpMon
for
different
geographical
regions

etc.).

LD
benefits:
data
integraMon,
data
search,
shareable
data,
reusable
data,

extensible
data,
mulMlingual
support,
data
discovery,
transparency,
and
high

degree
of
automaMon.

Challenges:

•
Quality
of
data
and
metadata.

•
Inconsistency
between
different
sources.

•
Wide
variety
of
data
formats.

•
Data
provenance.

•
No
open
license
associated
with
data.

•
Licenses
complexity
and
diversity.

•
Tracking
changes
in
data.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

Generic
Linked
Data
use
cases

Use
Case
2
-‐
The
energy
data
portal

SEÍS
example

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Use
Case
2
-‐
The
energy
data

portal

Energy
Model

Energy
Performance
Benchmarking

Examples
of
Energy
Efficient
Building
Energy
Efficient
Design
Paferns

Enter
a
Building
SimulaMon

SEÍS
system
Data
portal

Ontology
Repository

Climate
Geographic
Monitoring
CerMficaMon

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Use
Case
2
-‐
The
energy
data

portal

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Use
Case
2
-‐
The
energy
data

portal

Eﬃcient
buildings
and
their
performance
indicators
divided
in
two
groups:
Energy

(hea2ng
and
cooling
demand,
total
primary
energy,
CO2
emissions)
and
Indoor

Space
(2me
above
and
below
comfort).

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Use
Case
2
-‐
The
energy
data

portal

The
informa2on
to
be
uploaded
is
divided
in
ﬁve
categories:
Project
Data,
Building

Proper2es,
Outdoor
Environment,
Opera2on
and
Performance.

The
data
uploaded
through
this
service
will
be
assigned
to
the
terms
of
the
ontology
thus

ensuring
the
compa2bility
of
the
new
data
with
the
exis2ng
data.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Use
Case
2
-‐
The
energy
data

portal

This
service
calculates
the
value
for
the
indicators
for
energy
eﬃcient
and
other
buildings.

The
graphics
display
the
minimun,
maximum,
and
median
values
for
each
indicator
and

type
of
building.
The
values
of
the
indicators
of
the
selected
buildings
are
shown
in
the

orange
circles.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

Generic
Linked
Data
use
cases

Use
Case
3
-‐
Energy
data
infographic

Contributors:
Filip
Radulovic
(UPM)

Energy
data
infographic
allows
the
visualizaMon
of
energy
data,
using
a
variety
of

visual
analyMcs
techniques,
related
to
different
aspects
of
these
data,
for
example

geographic
regions,
energy
indicators

LD
benefits:
data
integraMon,
mulMlingual
support,
data
discovery,
and

transparency.

Challenges:

•
Data
provenance.

•
No
open
license
associated
with
data.

•
ParMal
or
missing
data.

•
Different
data
formats
and
structures.

•
Quality
of
data
and
metadata.

•
Inconsistency
between
different
sources.

•
Deprecated
data.

•
Data
persistence.

•
Data
integraMon
from
several
resources
with
diverse
licenses
and
formats.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

Generic
Linked
Data
use
cases

Use
Case
3
-‐
Energy
data
infographic

A
script
to
create
charts
based
on
the
results
of
a
SPARQL

query
using
Google
Visualiza2on
API:
Example
1

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

Generic
Linked
Data
use
cases

Use
Case
3
-‐
Energy
data
infographic

A
script
to
create
charts
based
on
the
results
of
a
SPARQL

query
using
Google
Visualiza2on
API:
Example
2

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

A
script
to
create
charts
based
on
the
results
of
a
SPARQL

query
using
Google
Visualiza2on
API:
Example
3

Generic
Linked
Data
use
cases

Use
Case
3
-‐
Energy
data
infographic

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

Generic
Linked
Data
use
cases

Use
Case
4
-‐
Energy
consumpMon
map

Contributors:
Filip
Radulovic
(UPM)

Energy
consumpMon
data
from
various
sources
and
regions
can
be

interacMvely
shown
on
a
geographic
map

LD
benefits:
data
integraMon,
data
discovery,
and
transparency.

Challenges:

•
Data
provenance.

•
No
open
license
associated
with
data.

•
Quality
of
data
and
metadata.

•
Inconsistency
between
different
sources.

•
Deprecated
data.

•
Different
data
formats
and
structures..

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

Generic
Linked
Data
use
cases

Use
Case
4
-‐
Energy
consumpMon
map

Energy
indicators
shown
in
a
geographical
map.
Leq:
SEMANCO
plaeorm
with
neighborhood

boundaries.
Right:
SEIS
system
with
a
heat
map
of
energy
eﬃciency
buildings.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

Generic
Linked
Data
use
cases

Use
Case
5
-‐
Linked
Energy
Data
quality
improvement

Contributors:
Filip
Radulovic
(UPM)

A
large
number
of
Linked
Data
datasets
is
being
published
on
the

web,
and
it
can
be
expected
that
the
published
data
are
prone
to

errors,
which
can
originate
either
in
the
Linked
Data
generaMon

process
or
in
the
original
data
source

LD
beneﬁts:
reusable
data,
extensible
data,
and
transparency.

Challenges:

•
Enabling
user
feedback
and
updates.

•
Machine-‐readable
descripMon
of
data
quality
improvements.

•
ParMal
or
missing
data.

•
Tracking
changes
in
data.

•
ReincorporaMng
such
improvements.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

Generic
Linked
Data
use
cases

Use
Case
6
-‐
Energy
situaMon
awareness

Contributors:
Filip
Radulovic
(UPM)

The
collecMon
and
analysis
of
Linked
Energy
Data
may
provide
insight

into
situaMons
that
might
lead
to
technical
or
environmental
hazards

and
that
would
require
human
acMon

LD
beneﬁts:
sharable
data,
data
discovery,
and
transparency.

Challenges:

•
Quality
of
data
and
metadata.

•
Inconsistency
between
diﬀerent
sources.

•
Wide
variety
of
data
formats.

•
Data
provenance.

•
Deprecated
data.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

Generic
Linked
Data
use
cases

Use
Case
6
-‐
Energy
situaMon
awareness

Newcastle
case
study:
Fuel
poverty
issue
visualized

and
quan2ﬁed
through
the
SEMANCO
plaeorm.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

Generic
Linked
Data
use
cases

Use
Case
6
-‐
Energy
situaMon
awareness

Energy
data
analysis

RDF
dataset

Sparql

queries

Machine

learning

methods

New

insights

Decision

making

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

Generic
Linked
Data
use
cases

Use
Case
6
-‐
Energy
situaMon
awareness

Rapidminer
a
suit
for
implemen2ng
Machine
Learning
methods
using
a
graphic
interface.

Includes
Weka
repository
(clustering,
regression,
classiﬁca2on…)

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

Generic
Linked
Data
use
cases

Use
Case
6
-‐
Energy
situaMon
awareness

Operators
for
retrieving
RDF
data
from
an
endpoint
with
SPARQL

queries

SELECT
disMnct
?uprn
?label
?suburb
?gas1213

WHERE
{

?feature
<hfp://schema.org/containedIn>
[rdf:label
?suburb].

?feature
rdf:label
?label.

?feature
lcc:uprn
?uprn.

?observaMon
ssnx:featureOfInterest
?feature.

?observaMon
ssnx:observedProperty
[rdf:label
"Gas"].

?observaMon
ssnx:observaMonResult

[ssnx:hasValue
[lcc:hasQuanMtyValue
?gas1213]].

?observaMon
ssnx:observaMonSamplingTime
[rdf:label
?Mme].

FILTER
regex(?Mme,
"2012/2013").

}

Gas
consump2on
12/13

Gas
consump2on
11/12

Gas
consump2on
10/11

Electricity
consump2on
12/13

Electricity

consump2on
11/12

Electricity

consump2on
10/11

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

Generic
Linked
Data
use
cases

Use
Case
6
-‐
Energy
situaMon
awareness

Operators
for
joining
the
results
of
the
queries

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

Generic
Linked
Data
use
cases

Use
Case
6
-‐
Energy
situaMon
awareness

Operators
for
cleaning
the
data
items

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

Generic
Linked
Data
use
cases

Use
Case
6
-‐
Energy
situaMon
awareness

Operator
for
clustering
examples
based
on
their
proper2es

Minimum
number
of
clusters

Maximum
number
of
clusters

Methods
for
calcula2ng
the
distance

between
items
(similitude)

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

Generic
Linked
Data
use
cases

Use
Case
6
-‐
Energy
situaMon
awareness

Operator
for
preparing
the
ﬁnal
results

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Guidelines
for
the
ExploitaMon

Generic
Linked
Data
use
cases

Use
Case
6
-‐
Energy
situaMon
awareness

Cluster
0

Cluster
1

Cluster
2

The
buildings
of
each
cluster
have
similar
performance
over
the
period
2010-‐2013.

"
The
City
Council
can
propose
a
public
funding
for
refurbishing
the
bad
performing

buildings
based
on
the
results
of
the
clustering

Results
of
the
process:
4
clusters

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

What
are
we
going
to
do?

Specification
Modelling
Exploitation
Linking
106

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

PublicaMon
Index

1.  Ensure
legal
compliance

2.  Publish
the
dataset
and
the
ontology

3.  Publish
metadata
and
online
documentaMon

4.  Enable
dataset
discovery

5.  Dataset
promoMon

6.  Dataset
support

107

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Ensure
Legal
compliance

•  If
the
source
of
your
dataset
permits
the
use
of
data

then
the
RDF
dataset
has
to
comply
the
license
and

legal
terms
of
the
original
data
source.

•  The
main
issue
to
take
into
account
is
the
data

privacy.
That
is:
private
enMMes
described
in
the

dataset
cannot
be
idenMﬁed.
(e.g.
people)

108

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Ensure
Legal
compliance

•  TASK
1:
Check
if
your
dataset
preserves
privacy

No
explicit
iden&ﬁers
are
used
as
literals
and
in
URIs
(e.g.
Na&onal
ID

numbers,
credit
card
numbers….)

109

In
the
case
your
dataset
does
not
preserves

privacy
go
back
to
RDF
genera2on
session
and

apply
the
following
anonymiza2on
techniques:

-‐  Suppression

-‐  Generaliza2on

-‐  Anatomiza2on

-‐  Perturba2on

-‐  Aggrega2on

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Publish
the
dataset
and
the
ontology

•  Make
accessible
through
the
Web
the
ontology
and

the
RDF
dataset
(also
the
links
to
other
datasets)

following
Linked
Data
principles.

–  To
store
the
RDF
data
into
a
persistent
repository

–  To
enable
resolvable
HTTP
URIs
and
content
negoMaMon

–  To
enable
a
SPARQL
HTTP
endpoint

110

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Publish
the
dataset
and
the
ontology

•  TASK
2:
To
store
the
RDF
data
into
a
persistent

repository

Upload
the
RDF
dataset
and
the
ontology
to
the
OpenLink
Virtuoso
server

111

Deliverable:
a
report
with
the
result
of
some
SPARQL

queries

using
the
Virtuoso
server
endpoint

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Publish
the
dataset
and
the
ontology

•  TASK
2:
To
store
the
RDF
data
into
a
persistent

repository

Upload
the
RDF
dataset
and
the
ontology
to
the
OpenLink
Virtuoso
server

112

Op2on
a)
Using
conductor
(Web
interface)
for
small
datasets
(
<
10
MB)

RDF
ﬁle
in
RDF/XML
format

Name
of
the
graph

(e.g
name
of
the
dataset)

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Publish
the
dataset
and
the
ontology

•  TASK
2:
To
store
the
RDF
data
into
a
persistent

repository

Upload
the
RDF
dataset
and
the
ontology
to
the
OpenLink
Virtuoso
server

113

Op2on
b)
Using
Virtuoso
console
for
big
datasets
(
>
20
MB)

1.
Store
your
RDF
dump
ﬁle
in
RDF/XML
format
in
a
folder
of
the
server
where
Virtuoso
is
installed

2.
Go
to
ISQL
console

3.
Invoke
this
method:

DB.DBA.RDF_LOAD_RDFXML_MT
(ﬁle_to_string_output
(‘path_to/rdf_dump.rdf'),'',
'{your_graph_name}');

4.
In
case
you
need,
clear
the
graph
with
this
method:

SPARQL
CLEAR
GRAPH
<{your_graph_name}>;

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Publish
the
dataset
and
the
ontology

•  TASK
3:
To
enable
resolvable
HTTP
URIs
and
content

negoMaMon

Install
Pubby
to
enable
resolvable
HTTP
URIs

114

Deliverable:
dataset
with
resolvable
URIs

op2onal

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Publish
the
dataset
and
the
ontology

•  TASK
3:
To
enable
resolvable
HTTP
URIs
and
content

negoMaMon

Install
Pubby
to
enable
resolvable
HTTP
URIs

115

PUBBY
conﬁgura2on

Go
to:

tomcat/webapps/pubby/
WEB-‐INF/conﬁg.n3

op2onal

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Publish
metadata
and
online
documentaMon

116

•  Create
and
publish
the
documentaMon
of
the
RDF

dataset
and
the
ontology.
This
documentaMon
is

oriented
to
both
human
and
machine
users
and
its

purpose
is
to
facilitate
the
usage
of
the
dataset
that
is

being
made
available.

–  DescripMon
of
the
datasets
in
DCAT
and
VoID
vocabularies

–  Human-‐readable
documentaMon
of
dataset
and
ontology

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Publish
metadata
and
online
documentaMon

•  TASK
4:
To
describe
the
dataset
in
DCAT
/VoID

vocabularies

117

Deliverable:
a
DCAT
or
VoID
ﬁle
describing
your

dataset

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Publish
metadata
and
online
documentaMon

•  TASK
4:
To
describe
the
dataset
in
DCAT
/VoID

vocabularies

Following
the
DCAT
example:

118

@prefix
os:

<hfp://a9.com/-‐/spec/opensearch/1.1/>
.

@prefix
dct:

.

@prefix
xsd:

.

@prefix
api:

<hfp://purl.org/linked-‐data/api/vocab#>
.

@prefix
rdf:

.

@prefix
xhv:

<hfp://www.w3.org/1999/xhtml/vocab#>
.


a

dct:Dataset
;

dct:license

<h`p://purl.org/NET/rdflicense/ukogl1.0>
;

dct:source

“Descrip2on
of
the
dataset
source"
;

<hfp://www.w3.org/2002/07/owl#sameAs>

<h`p://datahub.io/dataset/XXX>
.

dct:publisher

“The
publisher
of
the
dataset”;

dct:language

<h`p://id.loc.gov/vocabulary/iso639-‐1/en>

;

dct:accrualPeriodicity

<h`p://purl.org/linked-‐data/sdmx/2009/code#freq-‐W>

;

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Publish
metadata
and
online
documentaMon

•  TASK
4:
To
describe
the
dataset
in
DCAT
/VoID

vocabularies

Following
the
VoID
example:

119

@prefix
rdf:
.

@prefix
rdfs:
<hfp://www.w3.org/2000/01/rdf-‐schema#>
.

@prefix
foaf:
<hfp://xmlns.com/foaf/0.1/>
.

@prefix
dcterms:
.

@prefix
void:
<hfp://rdfs.org/ns/void#>
.

@prefix
xsd:
.

##
your
dataset

rdf:type
void:Dataset
;

foaf:homepage
<h`p://your.dataset.com/homepage>
;

dcterms:Mtle
“Title
of
your
dataset"
;

dcterms:descripMon
“Descrip2on
of
your
dataset."
;

void:sparqlEndpoint
<h`p://your.dataset.com/sparql>
;

void:uriSpace
"h`p://your.dataset.com/resource/";

<h`p://your.dataset.com/resource/URI/XXXX>
.

dcterms:source
"
Descrip2on
of
the
dataset
source"
;

dcterms:created
“XXXX-‐XX-‐XX"^^xsd:date;

dcterms:license
<h`p://crea2vecommons.org/licenses/by/3.0/>

dcterms:subject
<h`p://dbpedia.org/resource/Building>;

void:triples
150297
;

void:enMMes
18890
;

void:classes
65
;

void:properMes
100
;

void:disMnctSubjects
18962
;

void:disMnctObjects
26097
;

##
datasets
you
link
to

:Anotherdataset
rdf:type
void:Dataset
;

foaf:homepage
<
h`p://another.dataset.com/homepage>
;

dcterms:Mtle
“Another
2tle"
;

dcterms:descripMon
“Another
descrip2on."
;

<
h`p://another.dataset.com/resource/URI/XXXX
>
.

:Yourdataset-‐Anotherdataset
rdf:type
void:Linkset
;

void:linkPredicate
<h`p://your.dataset.com/predicate
used
for
linking>
;

void:target
;

void:target
:Anotherdataset
.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Publish
metadata
and
online
documentaMon

•  TASK
4:
To
describe
the
dataset
in
DCAT
/VoID

vocabularies

120

Resources:

-‐  hSp://www.w3.org/TR/vocab-‐dcat/

-‐  hSp://www.w3.org/TR/void/

-‐  hSps://code.google.com/p/void-‐impl/wiki/SPARQLQueriesForSta&s&cs

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Publish
metadata
and
online
documentaMon

•  TASK
5:
To
create
human-‐oriented
documentaMon

With
Widoco

121

Deliverable:
a
HTML
document
describing

your
ontology

op2onal

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Publish
metadata
and
online
documentaMon

•  TASK
5:
To
create
human-‐oriented
documentaMon

With
Widoco

122

1.
Setup
the
config
file:

config/config.proper&es

2.
Invoke
this
method:

java
-‐jar
widoco-‐0.0.1-‐jar-‐with-‐dependencies.jar
-‐ontFile
{you_ontology_file.owl}

op2onal

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Enable
dataset
discovery

123

•  To
enable
the
mechanisms
to
allow
both
human
and

machines
to
discover
and
befer
use
the
dataset.

–  To
create
a
sitemap
to
inform
search
engines
about
the

page
structure.

–  To
register
the
dataset
in
dataset
catalogues

(READY4SmartCiMes,
Datahub,

Reegle,
OpenEI…)

–  To
ensure
the
fulﬁlment
of
requirements
for
addiMon
to
the

LOD
cloud.

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Enable
dataset
discovery

•  TASK
6:
To
create
a
sitemap

With
sitemap4rdf

124

Deliverable:
a
XML
document
with
the
site

map
of
your
dataset

op2onal

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Enable
dataset
discovery

•  TASK
6:
To
create
a
sitemap

With
sitemap4rdf

125

1.
Invoke
this
method:

sitemap4rdf
{your_sparql_endpoint}
{preﬁx_of
your_url}

op2onal

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Enable
dataset
discovery

•  TASK
7:
To
register
the
dataset
in
dataset
catalogues

In
READY4SmartCi&es,
Datahub,
Reegle,
OpenEI

126

Deliverable:
a
new
record
in
a
dataset

catalogue
for
your
dataset

op2onal

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Enable
dataset
discovery

•  TASK
7:
To
register
the
dataset
in
dataset
catalogues

In
READY4SmartCi&es,
Datahub,
Reegle,
OpenEI

127

1.
Go
to
:
hfp://smartcity.linkeddata.es/datasets/

2.
Click
on
through
a
detailed
form
and
ﬁll
the
form

op2onal

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Enable
dataset
discovery

•  TASK
8:
To
ensure
the
fulﬁlment
of
requirements
for

addiMon
to
the
LOD
cloud

Using

Data
Hub
LOD
Datasets

Deliverable:
a
report
describing
the
level
of

fulﬁlment
of
the
LOD
requirements
of
your

dataset

op2onal

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

Enable
dataset
discovery

•  TASK
8:
To
ensure
the
fulﬁlment
of
requirements
for

addiMon
to
the
LOD
cloud

Using

Data
Hub
LOD
Datasets

129

1.
Go
to
:
hfp://validator.lod-‐cloud.net/

2.
Validate
your
dataset
(previously
uploaded
in
Data
Hub
repository)
using
the
name
of
the

dataset

op2onal

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

What
are
we
going
to
do?

Specification
Modelling
Exploitation
Linking
130

LD4SC
Summer
School

7th
-‐
12th
June,
Cercedilla,
Spain

ExploitaMon
Index

1.  Deﬁne
a
use
case

2.  Use
your
data

131

Publish and use your data

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