Something to think about, that goes beyond the issue of multi-byte data ( a problem that can be solved ).
Law is a process of communication that reflects and re-inforces what is and is not “OK.” Even though we have only a few major systems of law (Anglo-American, Civil, tribal, communist, etc), the complexity of law is why “lawyer” can stand as it’s own as a profession. As lawyers, we interpret the interpretations of culture, thereby recreating culture in an infinite loop.
So, as we think about the relationship between law and the semantic web, we see just how hard it is to develop cross-cultural ontologies. It’s hard, because defining what a group is, is one of the functions of “culture,”–that is, it’s one of the things that separates cultures.
One aspect of the Obama Administration that I most look forward to, is the manner in which Obama has that conversation with the nation, and the way in which a broader ontological approach to policy and international relationships takes hold.
In fact, both Michelle Obama and Barack Obama come from the legal elite, which means that the conversation will show a balance of the populism which characterized his communication throughout the campaign, as well as the “pragmatism,”–a form of foundational conservatism.
Finding a way to reconcile tomatoes and tomah-toes is what this article is aboot/about:development of multilingual ontologies “New Method For Building Multilingual Ontologies That Can Be Applied To The Semantic Web.”
Definitely worth a read, as is this blog by David Provost:
Solutions like Nstein’s and others can help to reduce the expense of human tagging or even introduce tagging where there’s been no human available to perform this task. Utlimately, costs can only be reduced to zero and businesses rely on revenues and profits for success. Nstein is cognizant of this fact and tries to point its customers in the right direction – for example, once a publisher’s content has been tagged it can be tailored to produce a feed based on a person, place, or thing. For some publishers this can represent a new and very welcome revenue stream. Another example is a common trait of NLP technology, which is the publication of additional content links that are related to the primary article on a given page. Again, some publishers will find the resulting performance an improvement over their current state of affairs.
