D12.1.2 NorthPole Report on quality improvements of existing Norwegian LOD

PlanetData

Network of Excellence

FP7
–

257641



D
12
.
1
.
2
NorthPole Report on quality
improv
e
ments of existing Norwegian
LOD

Coordinator:
Dumitru Roman

With contributions from:
Jens
KildeMjelva
,
David Norheim


1
st

Quality reviewer:
Daniele Dell'Aglio

2
nd

Quality reviewer:
Pablo Mendes



Deliverable nature:

Report (R)

Dissemination level:

(Confidentiality)

Public (PU)

Contractual delivery date:

3
1.12
.2011

Actual delivery date:

31
.1
2
.2011

Version:

1
.0

Total number of pages:

27

Keywords:

Norwegian d
ata sets, open data, linked data






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Abstract

This document provides a brief overview of the Norwegian data sets as of December 2011, as far as their
relevance to the domains of the use case described in D12.1.1 is concerned, with a particular focus on the
Norwegian LOD. Furthermore, the document repo
rts on the Norwegian data sets that have been made
available as RDF to be used in the regional development and environmental friendly behaviour use cases.
Finally, we outline the next steps for provisioning of Norwegian LOD such that the necessary data for

the
use cases is provided as LOD.
This deliverable is meant to
provide the baseline for the data sets to be
used in
the two use case applications described in D12.1.1
.

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Executive summary

This deliverable is part of our endeavour of building applications th
at consume

Norwegian
linked data. In
D12.1.1 we introduced two use cases in the area of monitoring regional development in Norway and
environmentally
-
friendly behaviour, respectively. In this deliverable we provide details on the actual data
sets to be use
d in the applications implementing the two use cases. More specifically we report on the
current
status of the
data sets that have been made available
in RDF in preparation for the implementation of the
use
case
applications, and outline next steps for pro
visioning of Norwegian LOD such that the necessary data for
the use cases is provided as LOD.

This document begins with
a brief overview of the Norwegian data sets as of December 2011, as far as their
relevance to the domains of the use case de
scribed in D
12.1.1 is concerned, and then provides descriptions of
the data sets that have been made available in RDF as of December 2011. We focus on the data sets directly
related to the use cases and provide information such as data sets n
ame
, the s
ource

of the dat
a, current access
mechanism, where the data sets are hosted,
e
stimated

number
of triples
, q
uality
of the data sets
(
in terms of
compliance to the linked data principles
)
, and the use case where the data is meant to be used. In addition, we
provide brief de
scriptions of
other important Norwegian LOD sets (not directly relate to the use cases)
, and
outline some scenarios on how the data from the various data sets could be used in the context of the use
cases
.

The regional development use case is focused on mo
nitoring
innovations and development
s

in various
sectors in regions and municipalities

in Norway
, therefore several governmental
Norwegian
data sets are
required for this use case.
In this deliverable we describe how the following data sets have been provided as
linked data and
provide information on
how they are currently accessible:
Enhetsregisteret (
the
c
entral
c
oordinating
r
egister for
l
egal
e
ntities

in Norway
)
,

Grasrotandelen

(
a

registry
containing
organisations that
receive
public
funding
)
, Tjenestemannsregisteret

(
a data set containing age and gender distribution for all
governmental agencies at different locations
)
, Partifinansiering 2009

(financing of political parties in 200
9)
,
Kommunekatalogen

(the catalogue of communes in Norway)
,

NFR prosjektarktivet

(national since
foundation projects archive)
, and

SERES

(
a national metadata repository system
).

The environmentally
-
friendly behaviour use case
is meant to provide decision s
upport on
the most
environmental
-
friendly transportation options when faced with different transportation options for a short
regional trip, given constraints like time, weather, traffic and private preferences.

Therefore, public
transportation data
(in re
al
-
time)
and environmental data are required for this use case. In this deliverable we
describe how the following data sets have been provided as linked data and provide information on how they
are currently accessible:
Trafikanten

(
public transportation

data in Norway)
,
t
ransportation emissions data,
and e
lectric cars charging stations

in Oslo.

Finally, we o
utline the next steps for provisioning of Norwegian LOD such that the necessary data for the
use cases is provided as LOD.

In particular we emphasize

the need to p
rovide RDF representations of the use
cases data sets that are not yet converted to RDF
, c
reate missing links between the use cases data sets not
already linked but for which logical links exist, possibly based on vocabularies/ontologies rele
vant for the
use cases datasets.
These steps will be addressed in the upcoming deliverable D12.2.2.

With this
deliverable

we provided a
baseline for the data sets to be used in the two use case applications
, and
at the same time we improved and extended th
e Norwegian LOD.



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Document Information

IST Project

Number

FP7
-

257641

Acronym

PlanetData

Full Title

PlanetData

Project URL

http://www.planet
-
data
.eu/

Document URL


EU Project Officer

Leonhard Maqua


Deliverable

Number

D
12.1.2

Title

NorthPole Report
on quality
improvements

of
existing Norwegian
LOD

Work Package

Number

WP
12

Title

NorthPole


Date of Delivery

Contractual

M
1
5

Actual

M
1
5

Status

V
ersion

1.0

final



Nature

prototype
□

report


dissemination
□

Dissemination level

P
ublic



consortium
□


Authors (Partner)

Dumitru Roman (SINTEF), Jens KildeMjelva (Computas), David Norheim
(Computas)

Responsible Author

Name

Dumitru Roman

E
-
mail

dumitru.roman@sintef.no

Partner

SINTEF

Phone

+47
22067647


Abstract

(for dissemination)

This document provides a brief overview of the Norwegian data sets
(with a
focus on the Norwegian LOD) relevant
to the domains of the regional
development and environmental friendly behaviour use cases
(
described in
D12.1.1
)
.
T
he document reports on the No
rwegian data sets that have been
made available as RDF to be used in the

use case and discusses scenarios on
how the data sets will be used.

Keywords

Norwegian data sets, open data, linked data


Version Log

Issue Date

Rev. No.

Author

Change

2012
-
12
-
0
1

0.1

Dumitru Roman

TOC, structure, preliminary content
.

2011
-
1
2
-
0
4

0.
2

Jens KildeMjelva

Added
descriptions of some data
sets
.

2011
-
12
-
09

0.3

Dumitru Roman

Integrated content
; added
introduction, next steps
, some
descriptions of data sets
.

2011
-
1
2
-
12

0.
4

Jens KildeMjelva

Added missing data set
s

descriptions

2011
-
12
-
1
3

0.5

Dumitru Roman

Added executive summary, various
fixes

and improvements
, version for
internal review.

2011
-
12
-
18

0.6

Dumitru Roman

Addressed some of the reviewers’
comments.

2011
-
12
-
19

0.7

David Norheim

Addressed the rest of the comments
of the reviewers.

2012
-
12
-
20

1
.0

Dumitru Roman

Final fixes.



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Table of Contents

Executive summary

................................
................................
................................
................................
...........

3

Document Information

................................
................................
................................
................................
......

4

Table of

Contents

................................
................................
................................
................................
..............

5

List of figures

................................
................................
................................
................................
....................

6

List of tables

................................
................................
................................
................................
......................

7

Abbreviations and Definitions

................................
................................
................................
...........................

8

1

Introduction

................................
................................
................................
................................
................

9

2

Norwegian Open Data Sets

................................
................................
................................
......................

11

3

Data Sets in RDF

................................
................................
................................
................................
......

12

4

Use Cases Data Sets

................................
................................
................................
................................
.

16

4.1

Da
ta Sets for the Regional Development Use Case

................................
................................
..........

16

4.2

Data Sets for the Environmentally
-
friendly Behaviour Use Case

................................
.....................

20

5

Next Steps

................................
................................
................................
................................
................

26

References

................................
................................
................................
................................
.......................

27




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List of figures

Figure 1
–

I
mproving the provisioning of data for the two use cases.

................................
...............................

9

Figure 2
–

Norwegian open data sets.

................................
................................
................................
..............

11

Figure 3
–

Norwegian open data sets made available in RDF
.

................................
................................
........

12

Figure 4
–

Data sets needed for the regional monitoring use cases with potential links.

................................

16

Figure 5
–

Data sets needed in the environmentally
-
friendly behaviour use case.

................................
..........

20



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List of tables

Table 1
–

Summary of relevant Norwegian LOD data sets for the proposed case studies.

.............................

14

Table 2
–

Examples of Trafikanten queries.

................................
................................
................................
....

21

Table 3
–

Examples of queries for electric cars charging stations.

................................
................................
.

22


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Abbreviations

and Defin
itions

Data Set

–

A collection of related sets of information that is composed of separate elements but can be
manipulated as a unit by a computer.

(Oxford Dictionary)

Norwegian
Open
Data Set

–

A collection of data
(mostly in the Norwegian language)
publis
hed by
Norwegian organization

(mostly governmental but also private) and made publicly available.

Norwegian
Closed
Data Set

–

A collection of data sets published by Norwegian organization (mostly
governmental but also private) but not publicly available.

Norwegian Data Set
s
–

A collection of open or closed Norwegian data sets.

Linked Data

–

Data sets
made available
following the Linked Data principles
.
1

Linked Open Data (LOD)

–

Data sets publically available
as linked data.

Norwegian
Linked Data
–

Norwegia
n Data Sets made available as linked data.

Norwegian
LOD

–

Norwegian Data Sets made available as
LOD
.

OWL

–

Web Ontology Language

RESTful

–

Representational state transfer (REST) is a style of software architecture for distributed
hypermedia syst
ems such as the World Wide Web
introduced and defined in 2000 by Roy Fielding in his
doctoral dissertation.




1
http://www.w3.org/DesignIssues/LinkedData.html

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1

Introduction

Norway is
one of the first countries to implement the PSI
-
directive as a law in January 2009,
2

and
each new
governmental project is tod
ay required to address publication of the data it creates or processes.
Norway
is
considered as
one of a handful of countries outside of the English
-
speaking world with a clear commitment
to open data
,
3

and
offers interesting opportunities for becoming a g
reat testbed for consuming LOD data.
In
the context of PlanetData

we aim at establishing such a testbed
–

PlanetData
-
NorthPole
–

by creating
applications consuming Norwegian LOD.
In this deliverable w
e
outline
two case studies in highly sensitive
domains f
or governments and the general public such as regional development and environmental friendly
behavior, as part of our endeavor of showing the use of Norwegian LOD in practical settings
.

This deliverable is part of WP12,
“Call 1: NorthPole” which focus on
consuming and improving Norwegian
Linked Open Data for Regional Development and Environmental F
riendly Behaviour
. The
overall
objectives
of
WP12 are:

1.

To
specify and implement two case studies

for demonstrating the use and benefits of LOD in
regional
development

and
environmental friendly behaviour
, with a particular localization on
Norway;

2.

To
improve the existing Norwegian LOD and extend it

with new data sets to support the proposed
case studies;

3.

To
provide guidelines

for other countries in the use of LOD for regional development and
environmental friendly behaviour applications.

In
D12.1.1

NorthPole Case studies: definition, requirements and design

(Norheim et al, 2011) we addressed
the firs
t item and provided requirements for the two proposed use cases.
This document addresses the second
item and specifically aims to:

This deliverable is part of the process of improving and extending the Norwegian Linked Data with the aim
of providing the d
ata to the two use case applications in a form that can be easily consumed by the use case
applications. This process can be visualized in
Figure
1
.



D12.2.2

NorthPole Report on Norwegian LOD extensions




2

In Norwegian:
http://www.lovdata.no/all/hl
-
20060519
-
016.html#9

3
http://www.data.gov/opendatasites

…

…

…

Use cases

…

…

…

Use cases

(a) Before

(b) After

…

…

Norwegian Open
Data

Sets

Norwegian Closed Data

Sets

Norwegian Linked Data

…

1.

Provide a brief overview of the Norwegian data sets
as of December 2011, as far as their
relevance to the domains of the use case

describ
ed in D12.1.1

is concerned
;

2.

Provide an overview of the Norwegian LOD

as of December 2011;

3.

Describe in details the Norwegian data sets that have been made available as LOD

to be used
in the
regional development

and
environmental friendly behaviour

use cases; and

4.

Outline the next steps for provisioning of Norwegian LOD

such that the necessary data for the
use cases is provided as LOD.


Figure
1

–

Improving the provisioning of data for the two use cases.

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The
regional development

and
environmental friendly behaviour

use cases

described in D12.1.1 require data
sets from various sources. As shown in
Figure
1
(a) some of the necessary data sets are provided as open data
,
with very few provide
d as LOD
,

and some as closed data
. For the applications to consume the data sets
efficiently, the data sets need to be provisioned as linked data, situation depicted in
Figure
1
(b). This
deliverable reports on the developments of making available the data sets as linked data.

The rest of this
document is

organized as follows. Section 2
p
rovide
s

a brief overview of the Norwegian data
sets as of December 2011, as far as their relevance to the domains of
our
use case is
concerned
. Section

3p
rovide
s

an overview of the No
rwegian LOD as of December 2011. Section 4
details the Norwegian data
sets that
have been made available as LOD to be used in the regional development and environmental
friendly behaviour use cases
.
Finally,
Section
5

o
utline
s

the next steps for provisioning of Norwegian LOD
such that the necessary data for the use cases is provided a
s LOD

before the finalizations of the use case
applications
.


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2

Norwegian Open D
ata
Sets

The illustration
in
Figure
2

is a depiction of
current Norwegian open data sets
that can be considered as
relevant to the domains of the two use cases we introduced in deliverable D12.1.1
.
As it is not possible to
have a complete view over all the Norwegian open data sets
4
, we restrict ourselves to those that can be
related to the doma
ins of our use cases.



Figure
2

–

Norwegian open data sets.

The domains covered by the data sets include public sector

data

(e.g.
data about legal entities,
salaries in the
public sector, public transport data)
, environmental
data

(e.g. weather data, pollution data
, data about the
arctic region
)
, economy data

(e.g. budget and economy plan for regions in Norway, energy prices)
, and data
related to politics

(e.g. data about the political parties funding)
.

Some of these data sets
are indexed in two
open data catalogues
,
http://data.norge.no

and
http://no.ckan.net
,
where further information about the data sets are available. As our interest is in data sets that
are made
available as linked data, we will focus our attention in the next sections on data sets

for which

an RDF
representation

exists
. First, we will provide a more detailed overview of the data sets made available as RDF,
and then we will focus on the
s
pecific
data sets
we are considering for the use cases and describe what has
been achieved to date with respect to the provisioning of linked data for the
two
use cases.





4

The official catalogue for governmental open data, data.norge.no, was released in 2011, but as of December 2011, it
cont
ains only about 30 data sets.

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3

Data Sets in RDF

A subset of the
Norwegian
open data sets
that has been provided
in
R
DF
formats
is depicted in
Figure
3
,
where solid arrows are used to depict the links that have been created between the data sets, and dotted
arrows depict

some of the

potential logical links between the data sets
.


Figure
3

–

Norwegian o
pen data sets
made available in
RDF
.

In the following we briefly
introduce
each data
set directly

relevant to our use cases
and then provide details
regarding the source, access mechanism, current hosting, estimated num
ber of triples, and the relevance to
the specific case for each data set.



All legal entities are registered in the
Central Coordinating Register for Legal Entities

(
Enhetsregisteret
) at Brønnøysund Registry Centre
.
5

URIs and a RESTful service returning RDF

has been created to look up based on organizational number. The service needs to be made
searchable by including a RESTful service based lookups on NACE codes and regional codes.



The Norwegian Association of Local and Regional Authorities (KS)
6

and Statis
tics Norway maintain
a
registry of municipalities and counties
(
Kommunekatalogen
)
. The
data set has been converted
to RDF as a proof
-
of
-
concept
, but the
URIs haven't been made RESTful and outgoing links to
e.g.

DBp
edia

have

not yet been created.



The
Norwegian Research Council
7

maintains a
catalogue

of funded projects

(
Prosjektarkivet
).
This relates instruments and projects to organisations. This
catalogue

has been
converted

to RDF and
outgoing URIs
have

been created to the Enhetsregisteret. The
catalo
gue

is hosted on a
triple store

supplied by Computas.




5
http://www.brreg.no/english

6
http://www.ks.no/u/English

7
http://www.forskningsradet.no/e
n/

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

All the parties are, according to the Political Parties Act, obliged to report their income to a central
register. The Ministry of Government Administration, Reform and Church Affairs
,
8

maintains a
cent
ral
register of parties and their income (Partifinansiering.no).

This data for 2009 is available
in RDF / SPARQL, on Computas

triple store

and have been assigned URIs, but has not yet been
linked to the Kommunekatalogen.



Norsk Tipping
9

is a wholly state
-
o
wned company under the jurisdiction of the Ministry of Culture
with a special role in regulating gaming in Norway. Gaming funds benefit sporting and cultural
activities as well as voluntary humanitarian organizations all over the country through the
Grassr
oot
share (Grasrotandelen).

Grasrotandelen is a registry showing organisations that receive funding.
The registry has been translated to RDF but without the links to the organizations involved (in
Enhetsregisteret).



The main purpose of Trafikanten
10

is to p
rovide the public with up to
date travel information for
the public transportation system

in and around the counties Oslo and Akershus. The data is about
all public transportation, the current location and delays of route. URIs and RESTFul services
return
ing RDF

based on URI
-
lookups for this data have been created.



Markadatabasen is maintained by the Norwegian Ski Association.
11

It's a public source that provides
routes and real time status of preparation of ski slopes
. The data is available in XML. It is also
linked to Open Street Map. The data
is to be converted
to RDF and made available as a RESTful and
SPARQL endpoint. The data will be linked to public transport routes from Trafikanten.



All national
electric cars c
harging stations

are made publicly available as a dataset

by
the
Norwegian Electric Vehicle Association

through

Nobil
12
, and made available

in RDF

by the research
project SESAM4
13

on a triple store.
This data set has
been extended to include real
-
time availa
bility
by wrapping existing web services to RESTful services that return RDF trough HTTP
-
URI look
-
ups.



Tellus

is a national dataset
by the private entity
of accommodations, attractions and events produced
by the
Tellus
14

organisation. It has been made avail
able as a SPARQL endpoint with RESTful RDF
lookup by the Sesam4 project.



The Ministry of Culture
15

maintains a dataset of all
sports arenas

in Norway. This dataset has been
converted to RDF and made available as a SPARQL endpoint with RESTful lookup in RDF

by the
Sesam4 project.



The N
orwegian ICT Directorate (DIFI)
,
16

Tjenestemannsregisteret
,
is a dataset containing age and
gender distribution for all governmental agencies at different
locations. Organization

number
identifies the agencies and thus there ar
e potential links to Enhetsregisteret.



The Norwegian Public Roads Administration

(Vegvesenet
)
17

is responsible for the planning,
construction and operation of the national and county road networks, vehicle inspection and
requirements, d
river training and licensing.
Traffic information,
trafikkmeldinger
, is made
available t
h
rough a RSS feed that also exist in an XML version.
This

traffic

information
currently in
progress of

being

made

accessible in RDF format trough RESTful

look ups.



DIFI
18

emission data

is the official governmental reference data on emissions from means of
transportation. It contains emissions for busses, cars, trains etc. in g/km.




8
http://www.regjeringen.no/en/dep/fad.html?id=339

9
https://www.norsk
-
tipping.no/

(Norwegian only)

10
h
ttp://trafikanten.no/en/

11
http://www.skiforeningen.no/

(Norwegian only)

12
http://nobil.no/index.php?option=com_content&vie
w=article&id=17&Itemid=20

13
http://sesam4.net/

14
http://www.tellus.no/?set_lang=en

15
http://www.regjeringen.no/en/dep/kkd.html

16
http://www.difi.no/artikkel/2009/11/about
-
difi

17
http://www.vegvesen.no/en/Home

18
http://www.difi.no/artikkel/2009/11/about
-
difi

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

Brønnøysund Registry Centre
19

maintains SERES (Semantics Register for Electronic Services)
-

a
national metadata repository system. SERES is designed for the capturing, modelling, use,
administration and control of metadata used to define and specify services.

A brief description of other important Norwegian LOD sets
is given
in the following
.



Os
lo Kommune

Byantikvarens
20

guleliste (
Oslo
Municipality
,
The Cultural Heritage Management
Office's yellow pages) is a data set that contains information about architecturally and culturally
valuable buildings, sites and environments in Oslo. These data have

been converted to RDF by the
University of Oslo and are available through a SPARQL
-
endpoint an
d RESTful HTTP
-
URI look
-
ups.
21



Norwegian Petroleum Directorate
22

Fact Pages contain information regarding the petroleum
activities on the Norwegian continental she
lf. This information has been made accessible as RDF by
the University of Oslo.



NORAD
,
23

the agency for Development Cooperation in Norway has made statistical data
(Bistandsstatistikk) openly available. These data have been converted to RDF by Computas and
made available on Computas Linked Open Data Server.



LOS, maintained by the ICT
D
irectorate
24

contains topics for services provided by the
municipalities. It is used for navigation in municipality web
-
pages.

Table
1

provides a summary of the relevant RDF data sets for the two cases we are considering (regional
monitoring
–

case study #1, and environmental friendly behaviour
–

case study #2), where the na
me, source,
access mechanism, current hosting, estimated number of triples, and the relevance to the specific case are
provided for each data set.

Table
1

–

Summary of r
elevant Norwegian LOD data sets for the proposed case studies
.
25

Title

Author

URL to data set
homepage

Triples

Star scheme
score

(Lee,
2006)

Case study
applicability

Comments


Enhetregisteret

Brønnnøysund

Registry Centre
26

Computas

http://opendata.comp
utas.no/about/#BR
-
Enhetsregisteret

> 4.500.000

5

Case

study #1

RESTful RDF
WS Wrapper

Kommunekatalogen

KS
27

Univ
.
of Oslo

http://sws.ifi.uio.no/s
parqler/

Ca
.

2.000

3

Case

study
#1

Case
study #2

SPARQL

NFR

prosjektarkiv

Norwegian
Research
Council
28

Computas

http://opendata.comp
utas.no/about/#NFR
-
Prosjektkatalog

Ca
.
200.000

5

Case

study #1

SPARQL

Partifinansiering
2009

The Ministry of
Government
Administration,
Univ
.
of Oslo

http://heim.ifi.uio.no
/audus/rdf/partifinan
Ca
.

100.000

4

Case

study #1

RDF file dump




19
http://www.brreg.no/english

20
http://www.byanti
kvaren.oslo.kommune.no/

(Norwegian only)

21
http://sws.ifi.uio.no/project/gulliste/

22
http://www.npd.no/en/

23
http:/
/www.norad.no/en/front
-
page

24
http://www.difi.no/artikkel/2009/11/about
-
difi

25

The annotation in
italics
is based on

(
Mendes

et al, 2011)

data sets catalogue metadata schema.

26
http://www.brreg.no/english

27
http://www.ks.no/u/English

28
http://www.forskningsradet.no/en/

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Reform and
Church Affairs
29

siering.rdf

Grasrotandelen

Norsk
Tipping
30

Computas

http://opendata.comp
utas.no/joseki/

Ca
.

70.000

4

Case

study #1

SPARQL

Trafikkanten
sanntid

Oslo Kommune
31

Computas

http://opendata.comp
utas.no/trafikanten/i
d/stop/3010030

Ca
.
50.000

3

Cas
e
study #2

RESTful RDF
WS Wrapper

Electric car charging
stations

Nobil
32

Computas

http://opendata.comp
utas.no/nobil/id/char
gingStation/902

Ca
.

1.100

3

Case

study #2

RESTful WS
Wrapper (RDF
returning)

Idrettsanlegg

Ministry

of

Culture
33

Computas

http://opendata.comp
utas.no/joseki/

Ca
.
1.000.000

3

Case

study #2

SPARQL

Emission data

Norwegian ICT
Directorate
34

Computas

http://opendata.comp
utas.no/resource/emi
ssion/El
-
bil

Ca
.

150

4

Case

study #2

SPARQL +
RESTful WS
(RDF
returning)

Tjenestemanns
-
registeret

Norwegian ICT
Directorate
35

Computas

http://opendata.comp
utas.no/about/#Difi
-
Tjenestemannsregist
eret

Ca.
1.000.000

5

Case

study #1

SPARQL +
RESTful

WS

(RDF
returning
)

SERES

Brønnøysund
Registry Centre
36

Computas

http://opendata.comp
utas.no/about/#BR
-
Seres

Ca. 50.000

5

Case

study #
1

RESTful

WS
Wrapper

(RDF
returning)




29
http://www.regjeringen.no/en/dep/fad.html?id=339

30
https://www.norsk
-
tipping.no/

(Norwegian only)

31
http://www.oslo.kommune.
no/english/

32
http://nobil.no/index.php?option=com_content&view=article&id=17&Itemid=20

33
http://www.regjering
en.no/en/dep/kkd.html

34
http://www.difi.no/artikkel/2009/11/about
-
difi

35
http://www.difi.no/artikkel/2009/11/about
-
difi

36
http://www.brreg.no/english

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4

Use Cases Data Sets

In this section we will take each use case and provide a status of the data
sets, which

are needed for each of
the use cases. For the data sets that have been converted to RDF we will describe their structure and access
mechanisms, how the links have been
created to other data sets, discuss some issues related to data linking,
and outline some scenarios where the data sets could be used.

4.1

Data Sets for the Regional Development Use Case

The regional development use case is focused on monitoring innovations a
nd developments in various
sectors in regions and municipalities in Norway, therefore several governmental Norwegian data sets are
required for this use case.

The central point here is to select data sets that contain some quantitative data, that
can be pl
otted in various charts, and that relates to second (or lower) level administrative levels (count
ies
,
municipalities or lower)
, or where this information can be inferred from the data (e.g. through coordinates or
through an organizations location)
.

Figure
4

depicts the data sets needed for
this
use case.
Some of the open data sets have been converted to
RDF, and some of them are yet to be published as RDF. This
use case also requires some closed data sets,
marked as b
l
ack circles.
Close data sets in this context are data sets that we have permission to use for this
project, but the
owner has some restrictions on the use, or has

not made a decision on publication
or licenses.
Strong arrows represent links that
have been created between the data sets, and dashed arrows are potential
logical links that are yet to be created.


Figure
4

–

Data sets needed for the regional monitoring use cases

with potential links
.

In the following more d
etails on
each
d
ata
set

converted to

RDF

are given, following by a discussion on the
data sets to be converted to RDF, and examples of scenarios how the data sets will be used.

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Enhetsregisteret

(
Central
Coordinating Register for Legal Entities
)

A RESTful wrapper that returns LOD based on existing web services working against Enhetsregisteret

has
been created
.
An organization

(enhet) is identified with an URI that contains the organization number.
Looking
up such URIs will return data about the organization where the format is either human representable
(HTML) or machine representable (RDF) based on content negotiation.

URI structure for organizations (
e
.g. the organization Computas):



ID
-
URI
:

http://opendata.computas.no/lod/id/enhet/986352325



Data (RDF):

http://opendata.computas.no/lod/data/enhet/986352325



Page (
HTML):
http://opendata.computas.no/lod/page/enhet/986352325

Existing links:

•

SERES: Various variables in Enhetsregisteret are defined in SERES. For these variables a link is
made to a URI that is
dereferable

through the SERES RESTful LOD wrapper.

Potential
links to other
data sets:

•

Geonames: The
three
-
letter

country (ISO) code is u
sed to form a link to a geonames page that
describes the country in html. This geonames page is not available as RDF. No good RDF
-
data sets
were found that identifies countries with three letter ISO codes; hence it is not trivial to link the
country data i
n Enhetsregisteret to other data sets.

We will investigate how to create this link to
Geonames
.

•

Eurostat: Enhetsregisteret contains NACE codes. Codes that describe which domain(s) each
organization belong to. NACE codes are defined by Eurostat and also mad
e available as RDF by
them. Eurostat's NACE RDF data are dumped into one single RDF
-
file
,

meaning that the data for all
the NACE
-
codes
could

be retrieved
if

Eurostat HTTP
-
URI is
dereferenced
. The
national
NACE
codes
however, contain an additional fifth level
e
xtension

of the ones defined
by Eurostat. The codes
used in N
orway are specializations of the Eurostat
-
codes and consist of an additional digit. E.g.
62.010 for Norway
is more detailed that

62.01
in Eurostat.
The

link to Eurostat will therefore be a
generalization link. We will investigate how to create this link to Eurostat as well as if the national
NACE codes can be made available as a source to link to.

Grasrotandelen

Currently
the data set is made

available
t
h
rough SPARQL.

Example SPARQL query (executable at
http://opendata.computas.no/joseki/

) that will
return the

IDs

of
-

and how much money that has been given to
each of
the organizations

that has received funding

in the municipality Nome:

prefix : <http://opendata.computas.no/voc/grasrotandelen/>

prefix off: <http://opendata.computas.no/voc/grasrotandelen/>

SELECT ?s ?bidrag

WHERE {

GRAPH <
http://opendata.computas.no/dataset/grasrotandelen> {

?s a :Bidragsmottaker ;

off:kommune<http://opendata.computas.no/data/grasrotandelen.no/kommune/NOME> ;

off:bidrag ?bidrag.

}

}

Potential links to other data sets:

•

Central Place Name Registry (Sentralt

Stedsnavnsregister)
:

The grassroot share data set has a
potential link to the municipality name in the SSR. The matching to this will
be investigated.

•

Enhetsregisteret: The data set contains the
name of the organization that receives funding. Matching
to E
nhetsregisteret will be investigated.

Tjenestemannsregisteret

This data set is
available through a SPARQL endpoint

(
http://opendata.computas.no/joseki/
)

served on
Computas Linked Open Data Server. Pubby is used to make the URIs
dereferable

via RESTful operations.

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URI
-
structure (the organization Arbeidsdepartementet):



ID
-
URI:

http://opendata.computas.no/resource/tjenestemann/id/983893449



Data (RDF):
http://opendata.computas.no/data/tjenestemann/id/983893449



Page (HTML):
http://opendata.computas.no/page/tjenestemann/id/983893449

Potential
links to other
data sets:



The data links to Enhetsregisteret via organization number, the same id that uniquely
identifies
instances

within this
data set
.

Hence a same
-
as link could be made from Tjenestemannsregisteret to
Enhetsregisteret.

Partifinansiering 2009

These data used to be

available t
h
rough

a

SPARQL

endpoint at the University of
Oslo. The

content of this
endpoint has changed, making the
Partifinansiering data unavailable

through SPARQL. They are accessible
as a RDF file dump though, at the location:
http://heim.ifi.uio.no/audus/rdf/partifinansiering.rdf
. Each
resource
in this data set describes a local political party
,

such as Gjøvik

Pensjonistparti.

Potential links to other data sets
:

•

Enhetsregisteret:
The parties are defined as organisations, and
can therefore reference
Enhets
registeret, and will be investigated.

•

Kommuneregisteret:
The county and/or municipality
are

given in the data set, and hence a link to th
e
Kommuneregisteret can be made, and will be investigated.

Kommunekatalogen

Currently
the data set is
available t
h
rough SPARQL.

For e
xample
, the following
SP
ARQL query (executable
by appending it to

http://sws.ifi.uio.no/data?query=
) will
return

the

names of 10 municipalities:

prefix

foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?name

WHERE {

?s

foaf:name ?name .

}

LIMIT 10

Potential links to other data sets
:



DBpedia: The municipalities are described in
DBp
edia, and hence a link between these
will be
investigated
.

NFR prosjektarktivet

Access to this data set is c
urrently available t
h
rough SPARQL.

Example SPARQL query (executable at
http://opendata.computas.no/joseki/
) that will give projectIDs for all the
projects the

organization with
org
anization number

939377409

is responsible for:

p
refix

nfr:

<http://www.forskningsraadet.no/data/#>

prefix stuff: <http://purl.org/stuff/project/>

SELECT ?subject ?end

WHERE {

GRAPH <http://opendata.computas.no/dataset/nfr_prosjektarkiv> {

?subject nfr:orgnr_responsible_org

<https://ws.brreg.no/lod/enhet/939
377409> ;

stuff:targetDate ?end

}

}

ORDER BY ?end


Existing links
:

•

Enhetsregisteret
.

SERES

A RESTful LOD wrapper has been made on top of existing
W
eb services working against SERES. This
RESTful service works as a dictionary giving descriptions of defined terms in SERES and contains also links
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to related terms. Look up of a SERES term identified by an URI will result in either a human representable
d
escription (HTML) or a machine
processable

one,

in form of

an OWL ontology.

URI structure for an example term:



ID
-
URI:
http://opendata.computas.no/dict/guid
/Brø
nn
ø
ysundregistrene/Begrep/Enhet/4974



Data (OWL):

http://opendata.computas.no/dict/data/Brønnøysundregistrene/Begrep/Enhet/4974



Page

(HTML
):

http://opendata.computas.no/dict/page/Brønnøysundregistrene/Begrep/Enhet/4974

Data sets to be converted to RDF

This use case requires some other data se
ts to be made available as RDF, in particular
Statligpartistøtte

2011

and the
A
griculture
S
ubsidies
.

In addition two closed data sources
owned by the Norwegian Mapping Authority

(NMA)
37

are needed:
Ad
ministrative

Boundaries
38

containing various divisions of

a county or municipality,

and

Central P
lace
N
ames

Registry
39

containing official names of all places
.

The latter two will be converted from a
Web
Feature Service
40

representation.

Scenarios

The
above
-
mentioned

data sets are meant to support various scenarios in the use case.
A

typical use is
:



“Jens, looking to move to a new region

wants to find the density of a certain skill in a county.
”

L
ookup all organisations with a particular NACE code in all municipalitie
s in
Enhetsregisteret
.
This
data set

contains the number of employees for each organization. The municipalities can also be
found in
DBp
edia

where we’ll find population data for each municipality. We can then visualize the
number of employees per 1000 inhabitants and visualize this in a geo map.

Below are more examples that
illustrate
questions that

could be solved through this case study:



"P
er is a data journalist in a regional newspaper. He is writing a story about local farming
communities finding alternative subsidies beyond traditional farming subsidies
.
"



"Pål is a data journalist in a local online newspaper. He would like to see if
compa
n
ies in the region
receiving

research funding actually have an increase of employees
.
"



"Espen is a data journalist in a liberal newspaper. He's trying to find out if it is hard for 1
-
10
employees companies to get research funding, and if this is worse in s
om
e

regions than others
.
"



"Ola is a data journalist with a local TV station. He's currently researching if there are people
involved in more companies that are
particularly

good in getting research funding."



"Kari would like to see if there is a correlatio
n between SMBs getting research funding and the
distance to research institutions and universities."



"Ole wants to see if there is more research happening in municipalities that has a strong presence of
centre
-
right partied, than municipalities with
centre
-
left
.
"



"Hilde is researching the presence of subsidies given to companies involving politicians in
management or board
.
"



"Synne is mapping out what regions that have the most active politicians on board of companies
.
"



"Hans is researching population
development in a municipality versus the creation of new
companies
.
"



"Grete is looking into proximity to higher education and research funding
.
"

The data sets described above are meant to enable answers to the above questions (and to similar questions)
.




37
http://www.statkart.no/

38
http://www.statkart.no/nor/Land/Fagomrader/Grenser/

(Norwegian only)

39
http://www.statkart.no/nor/Land/Fagomrader/Stedsnavn/Internasjonalt/

40

http://www.opengeospat
ial.org/standards/wfs


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4.2

Da
ta Sets for the Environmentally
-
friendly
Behaviour

Use Case

The environmentally
-
friendly behaviour use case is meant to provide decision support
for
the most
environmental
-
friendly transportation options when faced with different transportation options for

a short
regional trip, given constraints like time, weather, traffic and private preferences. Therefore, public
transportation data (in real
-
time) and environmental data are required for this use case.
Figure
5

depicts the
data sets needed for
this
use case.
As in the previous use case, s
ome of the open data sets have been
converted to RDF, and some of them are yet to be published as RDF. This use case also requires
th
e
closed
data sets

that the previous use case requires
.


Figure
5

–

Data sets
needed

in the

e
nvironmentally
-
friendly

behaviour
use case
.

In the following more details on each d
ata
set

converted to RDF

are given, following by a discussion on the
data sets to be converted to RDF, and examples of scenarios how the data sets will be used.

Trafikanten
–

public transportation

The LOD are made available through an application running on a servlet where URI ca
lls return RDF (and
HTML) based on data (JSON) form the
t
rafikanten.no

API. In other word
s
: a Linked Data wrapper around
the Trafikanten API
.

A RESTful URI structure is defined for looking up various public transportation data with a
n

ID, e.g. stops
(buss/
metro/tram/boat/train stops). A URI look
-
up results in a human readable document (HTML) or
machine processable document (RDF) describing the identified resou
rce.


Which format to return depends
on
the
HTTP content negotiation.


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URI structure for stops:



ID
-
URI:
http://opendata.computas.no/trafikanten/id/stop/3011320



Data (RDF):
http://opendata.computas.no/trafik
anten/data/stop/3011320



Page
(HTML):
http://opendata.computas.no/trafikanten/page/stop/3011320

URI
-
structure for transport means:



ID
-
URI:
http://opendata.computas.no/trafikanten/id/transportType/8



Data (RDF):
http://opendata.computas.no/trafika
nten/data/transportType/8

Web services (API)

Various RDF returning search services are established. The services take parameters that are used in calls to
the original Trafikanten Web Services:
http://api
-
tes
t.trafikanten.no
.

Table
2

–

Examples
of
Trafikanten

queries
.

ID

Functionality

Example calls

Parameters

stopsByCoordinates

Get the (maximum 7)
Stops closest to the
given coordinates

UTM:
http://opendata.computas.no/
trafikanten/id/stopsByCoordi
nates/598611,6644712

WGS
-
84:

http://opendata.computas.no/
trafikanten/id/stopsByCoordi
nates/10.63627,59.91279

coordinate pair (X,Y)

UTM
: X = easting, Y = northing

or
WGS
-
84
: X = longitude, Y =
latitude

placesByString

Search for a given place.
The resulting RDF can

contain a number of
stops,
addresses

(with
coordinates)

or areas that match the
given place string
lexically or
geographically.

http://opendata.computas.no/traf
i
kanten/id/placesByString/Lysa
ker torg 45

<place>, a search string

that represents a place

(i.e. road address, area or stop)

travels


(from stops to
stops)

Find travel alternatives
from one or more given
stops to

one or more given stops
at a specified t
ime
(arrival before or
departure after)

Travel from Birkelunden (buss
or tram) to
L
ysaker (
bus

or
train):

http://opendata.computas.no
/traf
ikanten/id/travels/?time=181220
111242&fromStop=3010519&f
romStop=3010520&toStop=301
2552&toStop=3012551&isArri
valTime=false

?time

= <the time of
departure/arrival>

format: "ddMMyyyyHHmm"

?isArrivalTime

=
true if time of
arrival needs to

be before ?time.
false if time of departure is after
?time

?fromStop

= <id of a stop we
want to travel from>

?toStop

= <id of a stop we want to
travel to>

D
ata links to other
data sets:



The data links to the DIFI t
ransportation emission data. The transport types

(e.g.
http://opendata.computas.no/trafikanten/id/transportType/8
)

contain links to corresponding
transportation emission data. These

links are created manually by mapping the two
data set
s. Note
that not all transportation means are linked with emission data. There is not a 100% correlation
between the data sets. Emission data for trams are for instance not present.

Transportation emis
sions data

LOD are available through a SPARQL endpoint served on Computas Linked Open Data Server. Pubby is
used to make the URIs dereferable via RESTful operations.


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Example URI

structure (Electric car):



ID
-
URI:
http://opendata.computas.no/resource/emission/El
-
bil



Data (RDF):
http://opendata.computas.no/data/emission/El
-
bil



Page(HTML)
:
http://opendata.computas.no/page/emission/El
-
bil

Electric cars charging stations

The data have been made accessible as LOD through an

application running on a servlet where URI calls
return

RDF (
and HTML)
based on data (JSON) form the nobil.no API: a Linked Data wrapper around the
Nobil API
.

URI structure
:
A RESTful URI structure for looking up various public charging station data with a
n

ID, e.g.
charging stations. A URI look
-
up results in a

human readable document (HTML) or machine processable
document (RDF) describing the identified resource. Which format to return is depending on HTTP content
negotiation.

Example
URI structure for stops
:



ID
-
URI:
http://opendata.computas.no/nobil/id/chargingStation/902



Data (RDF):
http://opendata.computas.no/nobil/data/chargingStation/902



Page
(HTML):
http://opendata.computas.no/nobil/page/chargingStation/902

RESTful

Web services (API)

Various RDF returning services are established. The services take parameters that are used in cal
ls to the
original Nobil Web Services:
http://nobil.no/api/server/search.php

Table
3

–

Examples of
queries for e
lectric cars charging stations
.

ID

Functionality

Example calls

Parameters

chargingStationByCoordinates


Get the (maximum 10)
charging stations
closest (2000 km
radius) to the given
coordinates

http://opendata.computas.no
/nobil/id/chargingStationsB
yCoordinates/59.91673,10.7
4782

coordinate pair (X,Y)

X = latitude, Y = longitude

Kommunekatalogen

This data set is the same as the one used in the previous use case (see previous section).

Data sets
to be converted to RDF

This use case
can benefit from

other data sets to be made available as RDF, in particular

the air quality data
41

from the NILU,
42

c
ar sharing data, we
ather date

from
yr
.no,
snow ploughing real
-
time status,
and p
ublic
bicycles availabil
ity
:



Trafikkmeldinger

from The Norwegian Public Roads Administration

are available through RSS
and XML feeds. We are currently working on converting these data to RDF via a linked data
wrapper.



luftkvalitet.info

is a service from NILU that provides informa
tion in real time about the pollution in
various areas in Norway.



yr.no is the joint online
weather service

from the Norwegian Meteorological Institute (met.no)
and
the

Norwegian Broadcasting Corporation (NRK). They have a XML service available for 7 million
places in Norway for free.



Snow ploughing real
-
time status

is another service that is made available by the Oslo Kommune in
near future. This data set could relate t
o traffic information making it more sensible to take public



41
www.luftkvalitet.info

42
http://www.nilu.no

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transportation. The
data set

should therefore link to public transportation and made available in RDF,
and also connected to the weather information.



Oslo is equipped with around 3000 city
-
bikes
available for the public.
A real
-
time status of the
bike stands

(where bike stands are and how many are available) is publicly availab
l
e.
Clear Channel

is maintaining this on behalf of Oslo Kommune. The data is made available as a XML service. The
service
needs to be wrapped as RDF and interlinked with bike tracks and tour tracks.



Bike tracks and touring tracks in Oslo

is a
data set

that is made available from Oslo Kommune.
This should be connected to the city
-
bike stands and made available as a SPARQL/RDF

endpoint.

In addition, the administrative
boundaries

and place names mentioned in the previous use case are also
useful

here.

We will investigate if these data sets can be included.

Scenarios

The
above
-
mentioned

data sets are meant to support various scen
arios in the use case. For example, consider
the following scenario.
Peder is at work at Computas at Lysaker

Torg 45 on
December1
8. In his calendar
there is a meeting scheduled at Kongens gate 6 (in Oslo) at 14:00 o'clock. Peder needs to get to that
address
before the scheduled time. Hence he's looking for transportation alternatives that will get him there in time.

Step 1
:
Finding

the address of the destination

Intention
:
By looking up the address, Kongens gate 6, Peder intends to finds transportatio
n stops close by the
address and/or the specific coordinates of the address.

Action
:
Search for the destinat
ion

address in the
Trafikanten data set

•

Request:

http
://opendata.computas.no/trafikanten/data/placesByString/kongens%20gate%206

Action result: RDF content (by Oct. 19. 2011):

•



Address
:
Kongens gate 6

with locality
Moss

•



Address
:
Kongens gate 6

with locality
Oslo. Coord =

(10.74182, 59.90992)

•



Stop
:
Kongens gate (
i

Tollbugata
) with locality
Oslo.

ID = 3010025

•



Stop
:
Kongens gate (
i

Prinsens gate
) with locality
Oslo
.

ID = 3010026

•



Stop
:
Kongens gate

with locality
Kongsberg

The request results in RDF representations of five different places where
three of them are situated in Oslo
and two are not.

Step result
:



A list of destination stops
(3010025, 3010026)



Coordinates of the address in Oslo: (10.74182, 59.90992)

Step 2
: F
inding public transportation

stops by the destination

Intention
:
The most
precise result acquired from the previous step was the specific address in Oslo. In this
step Peder uses the coordinates of that address to find the closest transportation stops and their distance from
the address.

Action
:



Request:

http://opendata.computas.no/trafikanten/data/stopsByCoordinates/10.74182,59.90992

Action result: RDF content (by Oct. 19. 2011):

Various Stop
-
resources with different walking distan
ces to
the destinations
:


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ID

Name

Distance (minutes)

3010050

Stortorvet (ved

Glasmagasinet)

6

3010077

Rådhusplassen (trikk)

5

3010018

Dronningens gate (i Prinsens gt)

5

3010074

Bankplassen (
i

Kongens gate)

1

3010026

Kongens gate (i Prinsens gate)

3

3010025

Kongens gate (
i

Tollbugata)

1

3014017

Dronningens gate (i D
r
onningens g
ate)

5

3010075

Christiania torv

4

3014022

Wessels plass (i Prinsens gt)

4

3010017

Dronningens gate (
i

Tollbugata)

3

3010073

Bankplassen (
i

Kirkegata)

3

3010022

Wessels
plass (i Nedre Vollgate)

5

Step result
: A

list of destination
stops and

their distances to the destination address

Step 3
:
finding public transportation stops close by the user’s starting location

Intention:

This

step is similar to step 2. The stops close
to
Peder's starting position are found by using the
same service. The coordinates of Peder's position are found by using his phone GPS.

Action
:



Request:

http://opendata.computas.no/trafikanten/id/stopsByCoordinates/10.63627,59.91279

Action result: RDF content (by Oct. 24, 2011):

Various Stop
-
resources with differe
nt walking distances to
the destinations

ID

Name

Distance (minutes)

3012552

Lysaker stasjon (sydside Dr.vn)

5

3012551

Lysaker stasjon (nordside Dr.vn)

0

2190019

Fornebuveien

11

3012553

Lysakerbru (
i

Lilleakerveien)

5

2190007

Lillengveien

12

2190105

Tjernsmyr

10

3012549

Lysaker (Lysakerlokket)

5

2190005

Marstranderveien

7

3012554

Lysakerbrygge [buss]

7

2190004

Solliveien

3

3012550

Lysaker [tog]

1

3012547

Strandveien (Lysaker)

5

Step result
:
A list of start

stops and

their distances to the start position
.

Step 4
:
finding public transport alternatives

Intention
:
Find transport alternatives from the start position to the destination address.

Action
:
Use the service for finding travel proposals with the start stops and
their walking distances (in
minutes) from the start position and the destination stops and their walking distance from the destination
address.

•

Request:

http://opendata.computas.no/trafikanten/data/travels/?time=181220111400&fro
mStop=3012
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551&fromStop=3012552:5&fromStop=2190019:11&fromStop=3012553:5&fromStop=219
0007:12&fromStop=2190105:10&fromStop=3012549:5&fromStop=2190005:7&fromStop=
3012554:7&fromStop=2190004:3&fromStop=3012550:1&fromStop=3012547:5&toStop=3
010050:6&toStop=301007
7:5&toStop=3010018:5&toStop=3010074:1&toStop=3010026:3
&toStop=3010025:1&toStop=3014017:5&toStop=3010075:4&toStop=3014022:4&toStop=
3010017:3&toStop=3010073:3&toStop=3010022:5&isArrivalTime=true

Action result: RDF content (by Oct. 4, 2011):

Five travel propo
sals consisting of various travel steps (i.e.
arrival/departure time, transport type, start stop, end stop etc.)

Step result
:
Travel proposals for Peder to get from Lysaker

Torg 45 to Kongens gate 6 (in Oslo) before 14:00
o'clock at October 28.

Step 5:

adding emission data to the travel proposals

Intentio
n:
Add emission data to each travel proposal to that the user can include environmental friendliness

as a factor to base the choice of transportation alternative on.

Action
:
Multiply the distance of eac
h travel by the emission data found by following the link from the
transportation mean data to the emission data set.


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5

Next Steps

This deliverable provided a brief overview of the Norwegian open data sets relevant for the regional
development and the envir
onmentally
-
friendly behaviour use case, and focused on the current status of the
linked data sets to be used in the two use cases. The next steps, whose results are to be described in
deliverable D12.2.2, include the followings:



Provide RDF representation
s of the use cases data sets that are not yet converted to RDF
.



Create the missing links between the use cases data sets not already linked but for which logical
links exist (as shown
in
Figure
4

and
Figure
5
),

possibly based on
v
ocabularies/
o
ntologies
relevant
for the use cases
da
ta set
s. We will investigate different ways of creating the links, based on the
approaches surveyed in (Ferrara

et al).



Create RESTful URI
-
structures (LOD) for the RDF data relevant for the cases that currently only are
available through SPARQL
-
endpoints.



Possibly use vocabularies (e.g. VoID
43
)
to describe the datasets

used in the use cases
.




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References

[1]

A.

Ferrara
, A.
Nikolov
, and
F
. Scharff
e
.
A Survey on Data Linking for the Semantic Web
. To appear
2012.

[2]

T
.

B
.

Lee,

Linked Data
–

Design Issues

(2006)
,
http://www.w3.org/DesignIssues/LinkedData.html
,
2006
-
07
-
27

[3]

P. N. Mendes, S. Stadtmüller, C. Bizer (2011). PlanetData deliverable
D4.1 PlanetData data sets,
vocabularies and provisioning tools catalogue and access portal
, September 2011.

[4]

D. Norheim
, J. K.
M
jelva
,
D. Roman (2011).
PlanetData deliverable
D12.1.1 NorthPole Case studies:
definition, requirements and design
, October 2011.