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
PlanetData
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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
.
Deliverable D12.1.2
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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.
Deliverable D12.1.2
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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
Deliverable D12.1.2
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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
PlanetData
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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
Deliverable D12.1.2
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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
.
Deliverable D12.1.2
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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/
Deliverable D12.1.2
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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/
Deliverable D12.1.2
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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
:
PlanetData
Deliverable D12.1.2
Page
24
of (
27
)
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
Deliverable D12.1.2
PlanetData
Page
25
of (
27
)
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.
PlanetData
Deliverable D12.1.2
Page
26
of (
27
)
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
.
43
http://www.w3.org/TR/void/
Deliverable D12.1.2
PlanetData
Page
27
of (
27
)
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.
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