Hiiiii everyooneee!
there are lots of novelties here!
Thanks to Daniel on the Baetle’s ml I found Launchpad: a code hosting platform which offer lots of functionalities to developers (more than what is offered by Google code hosting system although it’s inexplicable less spread)for example linking a bug with projects affected by him and other bugs if a user marks it as already fixed elsewhere. Even if they don’t adopt any automatic algorithm to link bugs, this is the only existing tentative of bugs linkage and offers lots of suggestions to my work. Moreover, considered that there’s no other dataset available online that allows clients to browse their RDF bug data through a Sparql endpoint or particular dereferenceable URIs, I can link Hackystat bugs not only to bugs of other Hackystat servers but also to bugs on Launchpad using their Rest Api (even if they’re neither RDF nor Linked Data they’re better than nothing, and Launchpad has a veeeeery “large” dataset).
Moreover I’ve read also an interestin article on this well known “Web of Data Discovery” issue published on the Nodalities Magazine. There it’s written:
As we have learned from the Web of Documents and SEO, the basic idea is to let the owner of a linked dataset do the ‘annotation part’ (i.e. telling about the content and the features of her dataset) and then let a search engine - or semantic indexer, for what it’s worth - do the dirty job of crawling these
This annotation part can be performed using the Vocabulary of Interlinked Datasets (voiD) which is a vocabulary aimed to bridge data publishers and data users, so that users can find the right data for their tasks more easily using the voiD description about a linked dataset. With discovery of datasets we mean the identification of datasets given certain attributes, trying to answer the question: given a set of attributes, which available resources match the desired set and what is their location? They’re trying to take the problem I’m encountering right now: how could I reach the other available datasets online related to the mine?
As soon as the search engine has the RDF triples from the voiD description in its index it can answer arbitrary complex queries such as :
SELECT ?dataset FROM http://sw.joanneum.at/void/demo/
demo3.rdf {
?dataset a void:Dataset;
dc:subject http://dbpedia.org/resource/
Proceedings . ?datasetSrc a void:Dataset;
foaf:homepage http://dbpedia.org/ ;
void:containsLinks ?linkset .
?linkset void:target ?dataset.
which will return all datasets that have data about proceedings and which are linked from DBpedia.
In this way my doubt about how to find dynamically all the other datasets relate-able to mine are solved!
According to that article, to make my dataset indexed by semantic search engines, I have to publish a sitemap with a particular sitemap extension containing a reference to the document describing my dataset by means of the voID vocabulary.
More-more-over I’ve found good suggestions about content-negotiation and cool uris definition.
I have finally a better defined idea of a Bug Report (thanks to Launchpad) and a mock-up is coming soon at least for what regards Issues.
Well, today I’m going to make Hackystat LiSeD servers able to let clients browse Hackystat data (I’ll try through a Sparql endpoint, otherwise I’ll use an URI lookup endpoint).
stay tuned 
myriam
P.S.
To summarize the main objectives to reach in the less time as possible are:
- find projects having the same tags
- find users with a specific level of Karma (equal or greater or lesser than a value) and/or “knows” something
- find issues marked as ‘duplicate’ by users or having the same tags
