LDIF – Linked Data Integration Framework 0.1
From the webpage:
The Web of Linked Data grows rapidly and contains data from a wide range of different domains, including life science data, geographic data, government data, library and media data, as well as cross-domain datasets such as DBpedia or Freebase. Linked Data applications that want to consume data from this global data space face the challenges that:
- data sources use a wide range of different RDF vocabularies to represent data about the same type of entity.
- the same real-world entity, for instance a person or a place, is identified with different URIs within different data sources.
This usage of different vocabularies as well as the usage of URI aliases makes it very cumbersome for an application developer to write SPARQL queries against Web data which originates from multiple sources. In order to ease using Web data in the application context, it is thus advisable to translate data to a single target vocabulary (vocabulary mapping) and to replace URI aliases with a single target URI on the client side (identity resolution), before starting to ask SPARQL queries against the data.
Up-till-now, there have not been any integrated tools that help application developers with these tasks. With LDIF, we try to fill this gap and provide an initial alpha version of an open-source Linked Data Integration Framework that can be used by Linked Data applications to translate Web data and normalize URI aliases.
More comments will follow, but…
Isn’t this the reverse of the well-known synonym table in IR?
Instead of substituting synonyms in the query expression, the underlying data is being transformed to produce…a lack of synonyms?
No, not the reverse of a synonym table, in synonym table terms, we would lose the synonym table and transform the underlying textual data to use only a single term where before there were N terms, all of which occurred in the synonym table.
If I search for a term previously listed in the synonym table, but one replaced by a common term, my search result will be empty.
No more synonyms? That sounds like a bad plan to me.
[…] Word For It Patrick Durusau on Topic Maps and Semantic Diversity « LDIF – Linked Data Integration Framework NoSQL should be in your business… […]
Pingback by R2R Framework « Another Word For It — June 29, 2011 @ 9:03 am