Malian linked data

Part of our promise in the CAISE paper as well as the ISWC outrageous idea paper was that we would make our market information data Linked Open Data. In a number of student projects, we can then investigate the benefits of sharing and re-using this data in all kinds of innovative ways. This remained an unrealised promise until now.

I am proud to announce that as of now, rural Africa (more specifically the RadioMarche data) is officially a part of the Linked Open Data cloud. This linked data will allow us to experiment with all kinds of data-mashups. Also it will hopefully function as a small exemplary step towards bridging the digital divide -as per the outrageous idea.

Currently, all the data from the RadioMarche server is in the Linked Data server. It contains the 12 communique’s consisting of 31 offerings. All in all, there are 721 RDF triples (which is not that much, but nice anyway). Each offering has a URI, it belongs to a communique (also a URI), it has a Product type (URI) and a contact person (URI), which is associated with a zone (URI) and a village (URI). The villages, zones and Product types are linked to DBPedia and Geonames. This can be exploited for example by re-using the geonames geo-coordinates or by the relations to other products in DBPedia.

As a URI basename, I now use, though this will change in the future (ill lose the /collections/ part). Each of the URIs is redirected to our server. Based on the HTTP request an HTML page is shown (in case of a normal web browser) where you can see the associated data. If an RDF request is made, the server responds with a set of RDF triples describing the resource.

An example: is the URI of a single offering. If you go there, you see it is related to communique The offering is related to the Person who in turn is related to the Zone On this last page, you see this zone (Mafoune) is linked to its counterpart in both DBPedia and Geonames. You can click on the URIs, which shows you the remotely hosted data. With a bit of imagination, you can think of the potential use of this integration.

There is a SPARQL endpoint to the data, where you can try out a SPARQL queries such as the one below, listing all persons that have offered Shea butter in the past: 
PREFIX rdf: < >
PREFIX rm: < >
PREFIX rdfs: <

?p rdf:type rm:Person .
?o rm:has_contact ?p .
?o rm:prod_name ?pn .
?pn rdfs:label ‘Beurre de karite’}


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