Ontology Alignment (is not the SameAs but is CloselyRelatedTo) Reconciling Worldviews

For the next three days, I’ll be reporting from the 8th International Semantic Web Conference (ISWC), taking place near Washington DC. A lot of what’s going on here is very technical, so rather than repeat everything I’m hearing, I’m going to talk about the broader themes that I see emerging. After this conference, I may try to tie them together into one comprehensive post.

This is my first theme. It’s about ontology alignment but is nevertheless very interesting. Yes, actually, it really is.

An ontology is basically a taxonomy of concepts and categories and the relationships between them – it’s sort of like a network but includes heritability (if I specify properties about some group, like “dogs can bark,” then it carries down to things within that group, so we know that Shih Tzus can bark). Ontologies are pretty key to the Semantic Web because expressing relationships between concepts is essentially defining those concepts – I could turn philosopher and argue that the meaning of something can only be found in the way it relates to other things. Or I could not, and just argue that defining things in terms of their relationships is a really useful way to do it, especially if the point is to make machines understand those things and be able to reason about them. That’s why a large percentage of the people here are obsessed with building ontologies about certain things (like jet engines).

But ontologies are personal. What if I think of “Shih Tzu” as a sub-category of “pets” but you think it belongs under “dinner proteins?” Or how about if a liberal defines a homosexual relationship as a type of family and a conservative thinks it belongs under sexual perversion? There’s no way the world would ever be able to agree on one definitive ontology. Nor should it. The way we categorize things, the way we cut up and connect up everything in the world is key to who we are, how we think, and what we do. I – an atheist and cognitive psychology nerd – would go so far as to say that the human soul exists in our subjective, idiosyncratic ways of linking up information. So to impose a single ontology on the whole world – no matter how well thought out and exhaustive it is – would be tantamount to mind control or soul stealing.

To their credit, most semantic technologists I’ve talked to think this way also. That’s why they’re encouraging ontologies to be fruitful and multiply and represent as many worldviews as there are ontology-builders (though ideally there would be more than 15. (I’m joking, I’m sure there are over 22 people who can build ontologies)). But having a bunch of rivaling ontologies out there that define and categorize things in unique ways doesn’t sound like much of an organized system of data, right? That’s true, and that’s why a lot of other people are involved in aligning ontologies – matching up the instances of some concept that shows up in different ontologies.

But…they’re still not doing it that well. That’s something Pat Hayes brought up during his keynote this morning. His topic was “blogic,” or, the new form of logic (formal logic) that’s required for the web. One of his problems with using traditional logic for the web is that people are mapping instances between different ontologies using the relationship “SameAs” – even though the fact that they come from different ontologies means they’re clearly not the same as each other. People are usually aware of that, but there’s still not much they can do because there’s no “SortOfSameAs” or “SameAsInThisOneParticularWay” relationships in traditional logic that they can use instead.

Ontology alignment is still a Big Problem and it’s acknowledged as such by much of the Semantic Web community. If anyone knows of good solutions in the works, I’d love to hear about them or add to this post with some comments.

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Semantic Embed: Part 1

In her quest to bring you the most authentic, up-to-date news about the evolution of the web, this reporter is venturing where few go: straight to the heart of NYC’s little-known Semantic Web community. It is there, buried in rule interchange formats and Unicode, hidden behind coke-bottle glasses and tablet PCs, that she hopes to find the people who are actually building the web.

Last night was my second New York Semantic Web Meetup event, so I knew a little more about what to expect (free pizza and liberal use of PowerPoint, unusually high Y to X chromosome ratio). The night was divided between two speakers: Mike Cataldo (CEO of Cambridge Semantics, which uses semantic web technology to solve businesses’ problems) and Lee Feigenbaum (a VP at Cambridge Semantics and co-chair of W3C‘s SPARQL working group – which I’ll explain later). It alternated between pretty heavy business-talk (“…and that’s game-changing!”) and tech-talk (“Supplant the mystifying OPTIONAL/!bound method of negation with a dedicated construct), but here’s what I was able to scrape together:

Cambridge Semantics
So Cambridge Semantics provides “practical solutions for today‚Äôs business problems using the most advanced semantic technology” – what does that mean? Essentially, they make it easier to get the data a company needs out of the applications that keep it locked up. A cool feature is that they have a plug-in to use Microsoft Excel as both a source for the data and as an interface for looking at it.


Apparently, there are a couple companies using Cambridge Semantics technology now, including a biopharmaceutical firm in Belgium and a startup called Book Of Odds that calculates the odds of various everyday activities.

SPARQL

As Lee Feigenbaum told me later, if SPARQL is working the way it should, most people shouldn’t even know that it’s there. That said, it’s probably useful to know a little about this core Semantic Web technology, if only to get a better idea of what the Semantic Web might be capable of.


SPARQL is a query language – it’s built for asking questions (and getting back the right answers). It’s got to be able to ask questions that pull together data from a lot of different sources in new, complex ways. The example query Feigenbaum gave in his talk was: “What are the names of all landlocked countries with a population greater than 15 million?” To answer that question, SPARQL first has to know about words like “country” and “population” (that “population” is a property of “country,” for example, and that “population” should refer to a number) and then combine information from different databases to get the right answer. What SPARQL does, then, is a whole lot more powerful than what Google does (Google just matches words in your question to popular pages where the same words show up). Try typing the example question into Google: when I did, the first hit was an entreaty for the world to help “the landlocked heart of Africa” and the second was actually a reference to Feigenbaum’s lecture. I’d tell you how long it took to get the right answer, except that I got sick of looking through the irrelevant documents somewhere on the sixth page of results.


So it’s easy to see how SPARQL can be a great piece of technology. It’s also easy to see why SPARQL is a semantic web technology – it can only come up with answers if the information it’s looking at is written in a computer-understandable language – RDF in this case. One of the main things that gets people excited about the Semantic Web is it’s question-answering ability, and SPARQL is what’s going to make that possible.*

*Note: actually what Feigenbaum was talking about last night was SPARQL 2 – the next version of SPARQL that he’s helping to develop at the W3C. In the interests of space and your waning interest, I’m not going to outline the differences between SPARQL and SPARQL 2 – if you’re really concerned about it, take a look at Feigenbaum’s presentation slides yourself.