The Yonderist

Recently, the National Institute for Standards and Technology hosted a conference to establish a word/logic bank for thinking machines. Out of that conference came an agreement:

Information scientists announced an agreement last month on a “concept bank” programmers could use to build thinking machines that reason about complex problems at the frontiers of knowledge from advanced manufacturing to biomedicine.

The agreement by ontologists — experts in word meanings and in using appropriate words to build actionable machine commands — outlined the critical functions of such a bank. It was reached at a two-day Ontology Summit held during NIST’s Interoperability Week in Gaithersburg, Md. The decision to create a unique Internet facility called the Open Ontology Repository (OOR) culminated more than three months of Internet discussion. (Quote taken from Science Blog report. The OOR proposal is here.)

When I was an undergraduate in college, I was both an English and Philosophy major. (I know, what hope for me, eh?) Studying philosophy in the 1980s, before the rise of artificial intelligence (AI), ontology meant only one thing: the study of existence to determine what entities (we called them phenomena) were present, what categories (or types) into which those entities prevailed, and the relationships between entities.

With the rise of AI, there has been a need to re-use ontology with a different vector: ontology can also be a description (like a formal specification of a program) of the concepts and relationships that can exist for an agent or a community of agents. So far as I know, Tom Gruber and his colleagues were the first to re-use ontology in this way. Their use is not as far from the philosophical usage as they might believe: their goal is to establish a set of concept definitions expressly for knowledge sharing and re-use. To my mind, such a project isn’t that far from what philosophers were doing, especially within the phenomenological tradition. Their goal, at least in my reading of Heidegger and Bachelard and others, was a kind of concise mapping of the universe as humans understood it in order to understand the very principles of human understanding. (Levi-Strauss’ structuralism operated in much the same manner. Again, to my mind, which may now be proving itself divergent and/or errant.)

The point, for Gruber et al., is that one commits to an ontology — their term is in fact “ontological commitment” — in order to create agents that can then engage in knowledge sharing. There were several levels (layers, dimensions) to what Project Bamboo participants aspired to, but one was definitely at the deep infrastructural level of meta-data. One of the groups in which I participated was tasked with the job of teasing out the notion of foraging which was something that the larger group perceived as being a commonality among humanities practitioners. We go out. We search for data. Faced with the forest of data to be found in libraries, which really do feel like being lost in the woods sometimes (in a good way), and on-line, we forage. Sometimes we find what we wanted. Sometimes we find not the berries we were looking for, but a root which is even better. That is the nature of foraging. All of us, however, yearn for better breadcrumbs through our proverbial forests. Better search devices would seem to be a key to better, more efficient searches — though one does have to wonder if efficiency, within the humanities paradigm, doesn’t also lead to impoverishment. Building better searches would seem to be founded on not only the data being accessible, which is one of the shiniest promises of the digital age, but also the data being searchable. Often what we want to know about something isn’t contained within the object itself. Take, for instance, a digital audio file of a performance by Varise Conner of his “Lake Arthur Stomp.” Nothing in the file itself will tell you the name of the tune — there are no words, no refrain. Nothing will tell you who originated the song or who is playing it now, unless you can recognize the tune and/or the style of its performance. Or that it’s a melody in the Cajun repertoire. Or that its author was of Irish descent. Or that he lived in Vermilion parish. Or that he was also a sawyer. None of this is the data itself. It’s all meta-data and it turns out that meta-data is sometimes more important than the data itself, especially when it comes to finding the data. The problem is committing to a meta-data set. Some of you live in places where there is a university library, which usually adheres to the Library of Congress call system, and a local public library, many of which still use the Dewey Decimal system. It’s not as easy as switching gears from letters to numbers, from PS to 800. The ordering of entities and their groupings are different. Philosophy, for example, occupies a different place and is near different things in the two systems. And that’s just to catalog — in order to house and then to find — books and other printed materials. What do you do with other kinds of objects? Especially objects that will never actually be housed in a physical facility? (We begin to border on an infinite regression here, since what we are dealing with is housing data about objects which, it turns out, is really meta-data itself. Oh. My.) But that is the grail that humanists seek, because we really would like to get as much of the human universe into a form that is searchable and accessible. Why is that important? Well, precisely because so much human activity still lies outside the scope of libraries and archives. And that not only includes the majority of humanity on this planet, but the majority of the lives of even the hyper-connected. One could easily argue that any assessment of what humans are based on what is currently available is really only a small part of the story. And we’re looking to tell a big story. I am the father of a toddler, after all, and so the idea of putting things away in a place where you can later find them is central to my existence.