Note: this workflow was also ported to the latest version of the LarKC Platform!
See New Urban LarKC
alpha Urban LarKC
The so-called alpha Urban LarKC is the first prototype build over the LarKC platform to demonstrate its applicability to address a Urban Computing scenario.
To learn more about Urban Computing in LarKC goto UrbanComputing.
To learn more about the activities in LarKC WP6 goto LarkcProject/WP6.
General Scenario
This scenario is about a user that wants to plan his movement, by possibly using a combination of transportation means, towards a particular destination that can be a known place or some dynamically-chosen goal place, like a monument - selected between the relevant ones of a city -, an event - among those published on the Web - or a friend - whose position can change over time.
If the user does not know in advance what the destination is of his route, he could express some requests or ambitions and the destination is selected on the basis of those preferences; for example, the user says that he would like to go and visit some interesting monuments or venues of a city, or that he would like to attend some music concerts or cultural event that night, or that he would like to meet some of his friends that happen to be in the same city.
In order to fulfill the user request, numerous distributed and heterogeneous data sources should be accessed and several different parameters should be taken into account to calculate the "most desirable" path for the user. The impact of the dynamic destination selection on the pipeline is that, first of all, a query should be routed to an appropriate data source (an archive of points of interests, a source of events schedule, a localization systems for a social network) and should select some possible destinations; then, for each destination, a suitable strategy to find the most desirable path should be performed.
For all those reasons, therefore, this is a good scenario to demonstrate the advantages of using LarKC technologies over traditional solutions and custom implementations.
alpha Urban LarKC Scenario
A user in Milano would like to organize a day/night by visiting some interesting places, attending a music concert, etc. He therefore needs to:
- Find interesting destinations: monuments or relevant places, music or cultural events scheduled for that day, etc.
- Understand the most suitable way to reach them: shortest path or "sightseeing" path, most suitable transportation means (car, parking, subway, pedestrian)
alpha Urban LarKC Pipelines
The alpha Urban LarKC is therefore composed by 3 different pipelines:
- monument destination selection pipeline
- event destination selection pipeline
- path finding pipeline
Monument Destination Selection Pipeline
To select monuments in Milano:
- a Transformer analyzes the query to get the triple patterns to be passed to the Identifier
- the Identifier queries Sindice to get relevant RDF documents
- a Selecter filters the documents to extract information about relevant monuments and
- a Reasoner answers the query
Event Destination Selection Pipeline
To select an event happening today in Milano:
- an Identifier queries Eventful to get a list of events and passes the references to
- a Transformer, which translates the REST invocation results into a suitable RDF
- a Selecter passes on all the triples to
- a Reasoner, which answers the query
Path Finding Pipeline
The path-finding is a LarKC pipeline as well, in which the final Reasoner wraps an algorithm to compute the most suitable path. We however employ different strategies to identify and select a subset of the Milano topology data to reason on:
- By getting all the streets in the Milano center jurisdiction;
- By getting all the streets in a circle containing the start-end points;
- By getting all the main roads and two small circles around the start-end points.
alpha Urban LarKC Client application
The alpha Urban LarKC client is a Web-based application that easily lets the user find monuments and events in Milano and then calculate the path from his current position.
The client application is available on the Web at http://seip.cefriel.it/alpha-Urban-LarKC/.
A demonstration video that explains how it works is available at http://seip.cefriel.it/alpha-Urban-LarKC/alpha-Urban-LarKC-demo.htm.