vocabulary alignment, meaning and understanding in the world museum by Tim Wray.
From the post:
We live in a world of silos. Silos data. Silos of culture. Linked Open Data aims to tear down these silos and create unity among the collections, their data and their meaning. The World Museum awaits us.
It comes to no surprise that I begin this post with such Romantic allusions. Our discussions of vocabularies – as technical behemoths and cultural artefacts – were lively and florid at a recent gathering of researchers library and museum professionals at LODLAM-NZ. Metaphors of time and tide – depicted beautifully in this companion post by Ingrid Mason, highlight issues of their expressive power of their meaning over time and across cultures. I present a very broad technical perspective on the matter beginning with a metaphor for what I believe represents the current state of digital cultural heritage : a world of silos.
Among these silos lie vocabularies that describe their collections and induce meaning to their objects. Originally employed to assist cataloguers and disambiguate terms, vocabularies have grown to encompass rich semantic information, often pertaining to the needs of that institution, their collection or their creator communities. Vocabularies themselves are cultural artefacts representing a snapshot of sense making. Like the objects that they describe, vocabularies can depict a range of substance from Cold War paranoia to escapist and consumerist Disneyfication. Inherent within them are the world views, biases, and focal points of their creators. An object’s source vocabulary should always be recorded as a significant part of it’s provenance. Welcome to the recursive hell of meta-meta-data.
Within the context of the museum, vocabularies form the backbone from which collection descriptions are tagged, catalogued or categorised. But there are many vocabularies, and the World Museum needs a universal language. LODLAM-NZ embraced the enthusiasm of a universal language but also understood the immense technical challenges that follow vocabulary alignment and, in many cases, natural language processing in general. However, if done successfully, alignment does a few great things: it normalises the labels that we assign to objects so that a unity of inferencing, reasoning and understanding can occur across vast swathes of collections; it can provide semantic context to those labels for even deeper, more compelling relations among the objects and it can be used to disambiguate otherwise flat or “unsemantified” meta-data, such as small free-text fields and social tags.
Vocabulary alignment is the process of putting two vocabularies side-by-side, finding the best matches, and joining the dots.
Tim’s message is not one of despair.
In fact, he describes how researchers have brought humans back into the picture, seeking to take advantage of what machines do best (simple matches) and what humans do better, more complex matching.
He references a paper and software that I will posting about separately that allow humans to refine mappings.
My only caution is that even human refinements are time and culture bound. That is a refinement that is useful today is a time and cultural artifact (in the archeological sense) that may need replacement today for use by visitors from another culture but certainly when the users are in a later time period.
That is we need to build systems that manage (record/track?) changes in semantic meaning rather than attempting to create semantic edifices designed to hold back the tides of semantic change.