Ah December, the month of the top ten list and the year in review.

I love it; it’s like a cram session for people like me who don’t pay good attention. Come January, I’ll put my head back down, and ignore what the rest of the world is doing. But for now, I’m energized as I belatedly stumble across everything that happened in 2011. (Hey, look, it’s html5. And is that a sparkly vampire chasing it?)

The folks at semanticweb.com have the standard “Best of the semantic web in 2011” round up post running, and there’s a lot of good stuff there. Siri of course remains the golden child of the semantic app world, even if it sometimes acts like, well, a computer. And just as in 2010, some of the most excitement and movement came around open data, linked data, government data and big data. All that data without clear models to structure it makes a modeler nervous, but it’s a good lesson in the need for pragmatism. If you can’t quickly develop and publish simple, general, reusable models (which mostly we can’t), people are going to move on without you.

Just as good is the site’s “Misses and misteps” article. I don’t think I’ve come across an annual post-mortem like this before, and I really appreciate everyone taking off the rose-colored glasses for a few minutes to take a critical look at the year. My favorite quote from it is this:

2011 was the year — well, the latest year — that the Semantic Web didn’t pan out.  The Semantic Web is the New AI: Technology that’s always on the verge of revolutionizing computing that never seems to deliver.  It’s a shame, but at least we’ve learned to focus on what’s practical and more likely to produce business value, semantic technologies such as text analytics are here-and-now rather than perpetually just over the horizon.

A little cynical? Maybe, but it fits my own view of the semantic world. We’re probably never going to achieve the full-blown vision of the semantic web’s original architects, and personally I’m okay with that. That vision is driving a lot of really practical sematically-influenced work that will infiltrate and improve all sorts of technologies and techniques, whether or not it results in a purely semantic solutions.

Also, for historical completeness, here’s a post I wrote for SmartBear’s Software Quality Connection rounding up 2010’s semantic web highlights. I get points for posting the link within the calendar year of the year I wrote the article, right? No? Well, here’s to more regular blogging in 2012.

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Is the semantic web a memex?

December 31, 2009

I agree with mc schrafel that the semantic web needs a better metaphor, or really any metaphor, to help people understand and embrace it. I’m just not sure the memex is the right one. It’s not a concept that’s easily recognizable by most people. And I’m not convinced that it’s an accurate metaphor.

Central to Vannevar Bush’s original description of the memex are paths of association between items, the connection made between point a and point b. While ontologies and semantic web apps let us label the relationship between two things, I’ve yet to see an application that lets you capture the path that led you to make that connection.

So for instance Zotero lets me say Paper 1 is related to Paper 2, but not that I followed a link to a citation in paper 1, which led me to a Wikipedia page, which led me to Paper 2. Paper 2 and Paper 1 may have a generally meaningful relationship that any reader would recognize: a shared author, similar subject matter. Or their relationship may be meaningful only to me: there was some association I made along the path from Paper 1 to Paper 2 that may not matter to anyone else. However, that association — the dynamic path leading to the association, not the static association itself — may be a source of information or inspiration to me. Where is the system that lets me preserve it?

To the best of my knowledge, that system doesn’t exist yet. Really, that’s not too surprising: we’re still working on representing the relationship between two things, much less the evolution and lineage of that relationship. There are thorny semantic and user experience questions related to the larger project, especially working across the boundaries of information systems and the semantic web does (or will). But it’s a worthwhile goal, and we should make sure that we make it there and aren’t satisfied with representing static associations. Why? Because doing so creates rich context, that starts to approximate the kind of implicit context humans generate all the time. It grounds are machine representations in human notions of time. And it facilitates that mysterious capacity humans have of sparking new ideas by juxtaposing two apparently unconnected things.

So my answer to my own question at the top of this post — and to dr. schraefel — is: not yet. But maybe someday.

A lot of applications claim to be “semantic”.  In some cases it’s easy to understand why. For instance, Zigtag ties its tags back to a taxonomy, so it knows that the tags “New York”, “NYC” and “The Big Apple” refer to the same thing. And that’s kind of semantic-ish.  True Knowledge is built around a sophisticated ontology that understands relationships as they change over time. That’s very semantic.

In other cases, it’s hard to understand where an app’s semantics are. As semantic search becomes more of a buzzword, the term “semantics” gets thrown around freely and, ironically for a word that means “meaning”, loses its meaning.

NetBase has generated a lot of excitement for what seems to be a truly semantic approach to search. They do parts of speech analysis on the text of documents, then put the concepts they find into relationship with each other.

All good, right? But this week, NetBase launched HealthBase, a “health research showcase”. HealthBase was intended to show off their technology. Instead, it pointed up some really big holes in it that make me wonder if there’s anything semantic going on here at all.

TechCrunch has a good story about searches on HealthBase producing questionable results. The most glaring error: a query for “AIDS” returns “Jews” as one of the disease’s causes. The software then goes on to helpfully suggest salt and alcohol as ways to get rid of Jews.

Speaking as a Jew, this suggests all kinds of wildly inappropriate jokes. Ply me with alcohol and salt, and I’ll tell you a few. Leave me sober and not hypertensive, and I’ll point out that this is not actually a case of conspiracy theory run amok, but just some really bad algorithms.

NetBase’s take on the situation was interesting. This is from their response to TechCrunch:

This is an unfortunate example of homonymy, i.e. words that have different meanings.
The showcase was not configured to distinguish between the disease “AIDS” and the verb “aids” (as in aiding someone). If you click on the result “Jew” you see a sentence from a Wikipedia page about 7th Century history: “Hispano-Visigothic king Egica accuses the Jews of aiding the Muslims, and sentences all Jews to slavery. ” Although Wikipedia contains a lot of great health information it also contains non-health related information (like this one) that is hard to filter out.

This is a funny answer: this is the exact problem NetBase’s technology is supposed to solve. Pointing out that it’s hard to solve doesn’t win you any points — you’ve got to actually solve the problem for that.

I’ve got to question what’s going on under the hood here. Granted, natural language processing is far from perfect. But if you’re truly analyzing how words are used in a document, you should be able to tell the difference between the noun that refers to a disease and the verb that refers to helping someone. It’s just coincidence that these concepts are represented by two words with the same spelling. If that trips you up, you must be doing keyword matching. Good old web 1.0, why would anyone fund this or pay for this, we already have search based on it, keyword matching.

Reading between the lines, there are other disturbing implications about Netbase’s approach. They don’t seem to analyze the context of their sources — Yes, Wikipedia contains a lot of non-health related content. Don’t use it for your health knowledge base! They don’t seem to take into account how many times a statement was made — if Jews and AIDS appear together only one time, consider it an outlier. And, they don’t seem to take time into account — AIDS has only been around since the 1980’s, so how could something that happened in the 7th century possibly be relevant?

HealthBase has been “fixed” since the initial uproar, or at least fixed enough to not categorize Jews as an agent of disease (thanks, NetBase!). But given the general cluelessness about semantics in their response, you’ve got to wonder if the fix consisted of tuning their text analytics, or hacking a bunch of workarounds into their code.