New in version 2021.01: access to data with SPARQL
New in version 2021.02: Open Data Hub Virtual Knowledge Graph and
description of underlying Knowledge Model
Changed in version 2021.05: moved technical information for tourism
and mobility to this section
The goal of the Open Data Hub project is to make available datasets containing
data about the South Tyrolean ecosystem, to allow third parties to
develop novel applications on top of them, consuming the exposed
data. These applications may range from a simple processing of
datasets to extract statistical data and to display the result in
different graphic formats like pie-charts, to far more complex
applications that combine data from different datasets and correlate
them in some useful way.
As seen in Figure 1, data originate from different
domains (Mobility, Tourism, and so on); they are gathered from sensors
and packed together by Data Providers. Sensors can be for
example GPS devices installed on buses that send their real-time
geographic position or a small electronic device on a plug of an
e-charging station that checks the if the plug is being used or not,
to let people know that the charging outlet is available.
Datasets are accessible through a REST API, the URL of each
endpoint is given along with other information in the description of
each dataset, see the lists of datasets in the remainder of this
section.
A Data Provider is any entity that shares their Open Data
with the Open Data Hub project, allowing their free reuse (ideally under a
free licence like or ) from any third-party that relies on
the Open Data Hub to build their application. These entities can be private
companies or enterprises, public bodies, and even private citizen, if
they have interesting data about South Tyrol to share.
The Open Data exposed by the Open Data Hub originate from data and datasets
owned by different actors (called Data Providers) which are
at this time mostly local public bodies. Since there is no direct
1-to-1 correspondence between Data Providers and datasets, we
currently offer a list of data providers whose data can be pulled
from Open Data Hub. Indeed, an Open Data Hub dataset can be composed of data deriving
from different providers, while a provider can submit to Open Data Hub
multiple types of data that will belong to more than one dataset.
The Open Data Hub's Data Providers are:
Autostrada del Brennero/Brennerautobahn management of the
A22 motorway infrastructure
Alperia/Neogy energy provider for South Tyrol
APPA Bolzano South Tyrolean agency for the environment
APPA Trento Trentino Agency of the environment
Bezirksgemeinschaft Burggrafenamt Comunità Comprensoriale
Burgraviato
Carsharing Alto Adige via its technological partner DB
Rent
CISMA bluetooth sensors
IDM Südtirol/Alto Adige trailblazer for economic
development in South Tyrol
H2 Südtirol Alto Adige energy company
HGV Hoteliers- und Gastwirteverband
Inno.vìe mobility solutions
LTS South Tyrol Association of Tourism Organisations
Municipality of Bolzano
Municipality of Merano
Municipality of Rovereto
Municipality of Trento
NOI Techpark technology and science park of South Tyrol
Route220, Nevicam and Driwe e-charging
stations provider
SASA public transport operator
SIAG Südtirol Informatica AG - Informatica Alto Adige
Südtirol Wein - Vini Alto Adige consortium of South Tyrol
Wines
A note about datasets
The Open Data Hub contains many datasets: a few have been provided for
testing purposes, other are meant for internal use only, and other
contain only a part of their data that is available as Open Data.
While the goal of the Open Data Hub project is to expose only Open
Data and the Open Data Hub team members always suggest to use to
third-parties releasing datasets, it is not yet possible for the
Open Data Hub team to guarantee the availability as open data of all the
data in the datasets, because the data licensing and its
distribution rights are decided by the copyright holder of each
dataset.
Since some of the datasets may contain data that can not be
distributed by the Open Data Hub team under an open licence like, e.g.,
or , a user will be able to retrieve from each dataset
only those data that are distributed as Open Data.
At the date of writing, datasets in the Mobility and Tourism domains are
available.
Whenever you query the data in the Open Data Hub, the snippet that you
retrieve always includes a block of information called
LicenseInfo, similar to the following one:
The highlighted line shows a licence, which in this case is
CC0, i.e., public domain and therefore freely reusable.
This block is always included as a child node within a JSON record
that starts with an ID and a number of additional information, which
may include also hyperlinks to resources that are external to the
Open Data Hub, like for example this example which refers to a webcam and
contains a link to an external provider where to find actual images
from that webcam (snippet code shortened for the sake of simplicity):
Whenever hyperlinks like the one shown in line 5 above
appear, it must not be implied that the license mentioned in the
LicenseInfo block (again, CC0) is applied to them:
everything contained in that link may be covered by a different
licence.
Indeed, the Licence mentioned in LicenseInfo
nodes refer only to content of the parent node–i.e., the one that
starts with “Id”, not to the content of any of the other
children nodes, including Streamurl and
Webcamurl.
The authentication layer is currently intended for internal
use only. All data in the dataset that you can receive from the Open Data Hub
are free to use and do not require any type of authentication.
The authentication layer can be of interest for developers who want to
collaborate in the development of Open Data Hub; Details on the implementation
are available in section Authentication in the Open Data Hub.
This section contains technical information
about the datasets in the Mobility Domain and how to access them using
the API that the Open Data Hub team developed and made available.
Figure 4 The dataset in the Mobility Domain at a glance.¶
Note
Recall that the API v1 for the Mobility Domain is now deprecated.
The description of each dataset includes the following information:
Output
The output format of the API call
E-mail contact
An e-mail contact for the dataset
API version
The versions of the API that can be used to access
dataset
StationType
The direct link to each
stationType included in the dataset
Use cases and info
Link to web sites that use the dataset and to
use cases based on the dataset
Web component
Link to Web Components developed on top of the
dataset (optional)
Sources
The list of Data Providers whose data compose the
dataset
Note
There is one StationType, namely
MobileStation which is a mobile probe no longer
active. It will always return an empty set of values, because
historical data are not available in the Open Data Hub.
The datasets in the Mobility domain are grouped in Traffic
and Mobility sub-domains as follows:
See also
The following howto will help you access data in the
Mobility domain:
The Mobility/Traffic sub-domain contains data about traffic (like e.g., real time
traffic load of a street, environmental measurement) that are useful
to plan a trip with an own means of transport, for example a car, or a bike.
The data for this datasets are collected by experimental
Bluetooth-based sensors and detectors currently located on various
points of the streets of Bolzano and soon in other location of
South Tyrol. Gathered data are then processed to obtain useful
information about the traffic; therefore, data in this dataset are:
The total number of vehicles detected
* An estimation of heavy and light vehicles
Collected data are also split within intervals (of e.g.,15, 30
minutes), for statistical and historical offline
analysis. Moreover, the data gathered by the Bluetooth devices
are used in the linkstation dataset.
In this dataset can be found Pollution and Air
Quality data (including, but not limited to, CO, NO2, PM 2.5,
PM10). Some portion of the data have been manually elaborated, with
the purpose to increase data quality.
The data for this dataset are collected by the same Bluetooth-based
sensors that are used to produce the Bluetooth dataset. Indeed, the data gathered by the sensors will
be used to produce statistics about a LinkStation, which is defined
as the path between an ordered pair of bluetooth stations.
the valid matches between pairs of Bluetooth sensors
(also called Bluetooth stations).
The number of matches per predefined time interval
(e.g., 30 or 60 minutes), like in the Bluetooth dataset
The estimated travel time and speed of the vehicle,
computed for every 15 minutes interval only.
The definitions and algorithm used in the computations are
extensively described in Section Data analysis complexity of
this pdf article.
The Road Weather stations are sensors that measure both
the road surface and the weather conditions. Data represent a
showcase from project CLEAN-ROADS, which offered open data
until 2016.
This datasets contains aggregated data collected by sensors drowned
in asphalt, but separated for each lane of a street. For people
that travel on Italian streets, these sensors are those large
rectangle boxes engraved in asphalt that you can seen also on
streets in the cities.
This dataset contains meteorological data provided by the Weather
and Avalanche Services of South Tyrol and Trentino, such as
Precipitation and Air temperature
This dataset contains the measurements of the weather
data, not the forecast.
This dataset contains data of the bike sharing service in
Bolzano and Merano, such as stations (for station based service -
Bolzano), areas (for free floating service - Merano), availability,
battery state, and other useful information.
This dataset contains all data of the carpooling service of the
Burggrafenamt/Burgraviato region in South Tyrol, including
carpooling users, car availability, and locations with accessible
destinations.
Note
Only users that have explicitly expressed their consent
to privacy are included, no sensitive data is stored or
exchanged.
This datasets exposes data about the existing e-charging stations
and plugs in South Tyrol and their status, including historical
data and usage. Data about station offering Hydrogen
recharged are also included.
Note
For this datasets are available also a number of
Web Components, see the use cases.
This dataset is not supported anymore and will
be removed from the Open Data Hub in the next future.
This dataset shows the real time position of buses operated by SASA
in South Tyrol and, through a few subsets, additional information
about lines, station boards, and news.
There are additional subsets that expose data in different formats:
Changed in version 2021.06: modified URLs of datasets and API; ordered
Tourism datasets lexicographically
This section contains technical information
about the dataset in the Tourism Domain and how to access them using
the API that the Open Data Hub team developed and made available.
Figure 5 The dataset in the Tourism Domain at a glance.¶
Datasets presented here are related to all kind of touristic
activities in South Tyrol. By exploring this domain, it is possible to
find information about winter and summer offers from local touristic
boards, information about weather, hotels and accommodation, Points of
Interests, and a lot more.
The following information is provided for each dataset in the Tourism domain:
Output
The output format of the API call
E-mail contact
An e-mail contact for the dataset
API version
The versions of the API that can be used to access
the dataset
Swagger URL
The URL of the swagger interface to the data
API URL
The URL of the browsable version of the dataset
Use cases and info
Link to web sites that use the dataset and
to use cases based on the dataset
Android App
Link to app for mobile phones developed using the
data in the dataset
Sources
The list of Data Providers whose data compose the
dataset
This dataset contains data about activities from LTS, including
local tours, hiking, running & fitness, cross-country skiing,
alpine climbing, e-bike, downhill, nordic walking, and many
more. This dataset offers LTS categorization and enhanced
filtering.
This dataset contains a collection of activities and Points of
Interest (PoI) in the South Tyrol region. The available
data have been extracted from different sources and also offer IDM
categorisation. This is a kind of superdataset, which includes
also poi dataset, activity dataset, and gastronomy dataset.
This dataset contains data about active events provided by LTS (TIC
Web): meetings, fairs, markets, performances, courses, music,
festivals, hikes, trips, guided tours, exhibitions, and so on. Data
about past events is also included.
This dataset contains data about PoIs from LTS, such as beauty and
wellness centres, bikes, castles, climbing halls, cocktail bars,
e-bike rentals, fashion shops, pharmacies, gas stations, car parks,
shops, ski schools, and many more. This dataset offers LTS
categorisation.
The Snow Report Data dataset contains detailed reports of all South
Tyrolean Ski Areas, including an aggregation of different
Datatypes. Status and conditions of Lifts, Slopes, Ski tracks,
Sledges, Measuring points (like e.g., snow height and last snow
day), and Ski Areas basic data are part of this dataset.
This dataset contains events location provided by LTS
such as info about a location (e.g. number of seats, number of
seats for disabled people, venue, etc.) or info to book an event
location (e.g. prices, room configuration, etc.). Data are
accessible in AlpineBits DestinationData format.
This dataset contains weather forecast for South Tyrol. Updated
daily at 07:00 AM and 11:00 AM (Sundays only at 10 AM), the
bulletin contains the following forecasts:
current and next day weather, and five days evolution in the
whole South Tyrol
for current and next day in mountain
current weather and next two days evolution for each South
Tyrolean districts.
All data is requested live through the Weather service of the
Province of Bolzano-Bozen (South Tyrol). Data is available in
English, German, and Italian language.
This dataset originates from data collected in the DAVINCI project, whose aims is to increase local
businesses by improving innovation and digitalisation of services.
The data consists of a list of actors that operated in the
creativity sector in South Tyrol and is used as data
source to generate a map for a dedicated Web Component
This dataset contains all places, offices, meeting rooms, and in
general all points of interest located in the various buildings
that compose the NOI Techpark in Bolzano-Bozen, Italy.
This dataset is used to create the interactive map of the NOI
Techpark.
This endpoint provides data from the AlpineBits Open Standard, whose purpose it to ease B2B data
exchange among actors involved in the alpine tourism.
Documentation for developers, including sample code snippets and
additional material can be found on AlpineBits dedicated page for
developers https://www.alpinebits.org/developers/.
New in version 2021.02: Description of the Knowledge Model
underlying datasets Accommodation, Gastronomy, and Event
New in version 2021.06: Description of the Knowledge Model
underlying the mobility domain
Some datasets in the Open Data Hub, namely Accommodation, Gastronomy, and
Event, are organised into a Virtual Knowledge
Graph that can be accessed using SPARQL from the dedicated SPARQL
endpoint. In order to define more
precise queries, this section describes the Knowledge Models (KM)
underlying these datasets; the description of each KM is accompanied
by an UML diagram which shows the KM at a glance.
Besides standard W3C’s OWL and RDF vocabularies, the Open Data Hub VKG
uses:
Diagrams use UML class diagram formalism widely adopted in
Knowledge Representation and in particular in the W3C’s
Recommendation documents for the Semantic Web. The following
additional notation applies:
Prefix
The default prefix used for classes and properties is
http://schema.org/. This means that, unless
differently stated, the definition of classes and properties,
including their attributes, rely on a common standard as defined
in schema.org’s vocabulary. As examples, see the
LodgingBusiness class and
the containedInPlace
property.
Hint
Other prefixes are explicitly pre-pended to the Class
or Property name, like e.g., noi:numberOfUnits.
Arrows
Arrows with a white tip denote a sub-class relationship, while
black tips denote object properties.
Cardinality
Cardinality of 1 is usually not shown, but implied; the
look across
notation is used. For example, the image on the right-hand
side–excerpt from the event dataset
VKG–can be read as 0 to N MeetingRooms are
ContainedInPlace Place.
Mobility Domain
The entire mobility domain has a unique underlying knowledge
model, which encompasses all the datasets and therefore also
allows an easier creation of cross-dataset queries. Since the
mobility domain gathers data from sensors, useful in this
domain is also the SOSA ontology, which uses sosa as prefix. You
can check the Classes and Properties of SOSA in the W3C’s
dedicated wiki page
The central concept is Station, of which all
StationTypes are subclass, while
Observation, LatestObservation, and
ObservableProperty are used to provide time-related
information of the data gathered and relate to
Sensor. Together with Platform,
Sensor make the relation between a Station and its
Sensors: For example, sensor EChargingPlug isHostedby an
EChargingstation Platform, which is also a Station.
The knowledge model is completed by the Feature
superconcept, which contains also Municipality and
RoadSegment, the latter defined by an
hasOriginStation and an hasDestinationStation.
The main class of this dataset is FoodEstablishment,
described by geo:asWKT, description, name, telephone,
and url.
A FoodEstablishment has
a PostalAddress–consisting of streetAddress,
postalCode, and AddressLocality–as address
a GeoCoordinates–latitude, longitude, and
elevation–as a geographical location geo
There are different (sub-)types of
FoodEstablishment, all sharing the same attributes:
Restaurant, FastFoodRestaurant,
BarOrPub, Winery, and
IceCreamShop.
The main classe in this dataset is Event, described by
a startDate, an endDate, and a description. Every
Event has an organizer, either a Person or
an Organization and a location.
A Person–identified by givenName, familyName,
email, and telephone–worksFor an Organization,
which has a name and an address, i.e., a
PostalAddress consisting of streetAddress,
postalCode, AddressLocality, and AddressCountry.
Finally, an Event has as location a
MeetingRoom–identified by a name– which is
containedInPlace a Place–which has also a name
or 
) from any third-party that relies on
the Open Data Hub to build their application. These entities can be private
companies or enterprises, public bodies, and even private citizen, if
they have interesting data about South Tyrol to share.
