Almagame is the software that Tim Wray mentions in his post, vocabulary alignment, meaning and understanding in the world museum, as using a technique called “interactive alignment.”
From the homepage:
Amalgame (AMsterdam ALignment GenerAtion MEtatool) is a tool for finding, evaluating and managing vocabulary alignments. We explicitly do not aim to produce ‘yet another alignment method’ but rather seek to combine existing matching techniques and methods such as those developed within the context of the Ontology Alignment Evaluation Initiative (OAEI), in which different alignment methods can be combined using a workflow setup. The Amalgame Alignment server will feature:
- A workflow composition functionality, where various alignment generators can be positioned. Their resulting mapping sets can be used as input for filtering methods, other alignment generators or combined into overlap sets.
- A statistics function, where statistics for alignment sets will be shown
- An evaluation tool, where subsets of alignments can be evaluated manually
Vocabulary and metadata workflow
The Amalgame toolkit realises the second step of a workflow specified by the Europeana Connect project for SKOSifying vocabularies and converting collection metadata into the EDM (Europeana Data Model). The first step, conversion of XML data into RDF, is supported by the XMLRDF tool.
Amalgame paper at TPDL 2011
We’re happy to announce our paper about Amalgam was accepted as a full paper for the International Conference on Theory and Practice of Digital Libraries 2011 (TPDL 2011).
The extensive online appendix also contains a rich use case description.
I think you will want to grab the paper, which has the following abstract:
In many heritage institutes, objects are routinely described using terms from predefined vocabularies. When object collections need to be merged or linked, the question arises how those vocabularies relate. In practice it often unclear for data providers how well alignment tools will perform on their specific vocabularies. This creates a bottleneck to align vocabularies, as data providers want to have tight control over the quality of their data. We will discuss the key limitations of current tools in more detail and propose an alternative approach. We will show how this approach has been used in two alignment use cases, and demonstrate how it is currently supported by our Amalgame alignment platform.
I am downloading/installing the software.
I am curious if a similar approach, albeit without converting data into RDF, could be used to create alignments of unstructured vocabularies? Along with reasons for the mappings between vocabularies?
Reasoning in part that there are far more non-structured vocabularies where access could be enhanced with mappings to other vocabularies, along with reasons for the mappings.