During an internal activity in the place where I work i got the opportunity to organize a little hackathon about Open Data and Linked Data.
The activity was a use case in the "Cinema" domain where we used the Linked Data technologies in order to mix public and private Data with the aim to discover new insight in the Data and imagine new uses of these Graph of data.
I split the activity in many sub activity. In this way everyone could work on what preferred using the technologies one could.
Data Sources
We analyzed the domain and we discovered interesting source of data released as Open Data such as Freebase in RDF and the list of the "Cinema Theatre" of Milan.
Someone imported this data in the graph and created a sample link between a movie and the place where a person saw it.
We also tried to think about the private information the graph could contains and we realized that a lot of them are already in digital form, but are in the Social Network silos.
Someone else discovered this really cool open data release about cultural events in rome. We couldn't find the data at the end, what a pity!
Data Process
I described some methodology of simple data import, cleaning and reconciliation before the hackathon.
Someone in the group used Open Refine and the RDF extension in order to reconciliate a list of movies and places in data from an existing source.
In this way some movies from a local libray were linked to the freebase dataset.
Data Store
I presented a lab instance of the Virtuoso Store and the people used that in order to store and query the graph of data.
Data Queries
I presented some basic SPARQL queries useful in order to discover what's inside a triple store.
Someone edited that in order to get an idea of the Freebase graph and all the data linked to it.
Some interesting queries about "Genre of movies i am more interested in" were produced.
People with query skills found SPARQL very similar to SQL
Data View
I presented some tools useful in exploring a distribuited graph of data and for make a graph view from the result of a query.
Someone used lodlive for getting ispired and discover new relationship in the data.
Someone else used VisualBox in order to build a tag cloud of the genre linked with the movies he had in his library: take a look!
This basic hackathon has been appreciated by the public. They found the "Hands-on" session helpful in order to understand better the use case of the semantic web technologies and a good annex to the more theoretical courses we organized