One of the blessings of living in Austin — and it’s important to remember them this time of year when you feel your eyeballs melting out when you step into mid-afternoon sun — is its legacy of work in machine learning and AI. Here we have a very active interest group, Semantic Web Austin run by Juan Sequeda, who has, over the last year or so, brought some very visible researchers in Semantic Web to town to teach hands-on tutorials.
If the concept of “Semantic Web” is foreign to you, let me try to capture
its essence succinctly. Presently one can conceive of the Web as a web of
documents: presentation and data are represented as web pages. My web document
points to Ryan’s document and Lauren’s document. Now imagine a résumé on the
Web. This résumé is a series of facts (and gross exaggerations 
), these
have nothing per se to do with the document construct you learn from
books called a résumé — the thing with a name at the top, horizontal rules under section headings, etc. that, purportedly, employers like to read. Non-human examiners of my résumé web page
care only about the facts, not the prettiness of the artifact. Thus, the Semantic Web is one in which meaningful
data is presented (as a résumé) for humans, but also presented (as the
essential facts of the résumé) for machines such that relationships between the various data can be utilized by semantically-aware web applications.
Both Tom Heath
and Peter Mika
gave great presentations full of ideas and hands-on activities to the Semantic
Web Austin group. From Tom I learned the basics of RDF, the language for
enumerating data-facts to machines, and how to build a basic RDF document.
Peter showed us RDFa and illustrated that HTML and RDF data can be written
into the same document. That was a “whoa” moment for me.
Because I hadn’t had a chance to integrate these lessons from the SemWeb
Austin sessions, my understanding was a bit shaky. The only way, I decided, to
actually figure this out was to find a project that would give me opportunity
to work with these respective ideas.
About this time my yearly review concluded and I was about to update my
résumé, an activity I exhort you to do after reviews. Yet résumé-writing had
always irritated me: writing a document and then trying to port it to various
formats, and then Mithras help you if you need to “skew” these documents to
particular employers quickly.
Thus I decided I needed to write my résumé in some sort of meta-language so
that I could publish to both LaTeX and HTML and “skew” to particular employers
quickly. This was the goal of m4resume.
The output is
Steven Harms
XHTML+RDFa résumé. If you’re interested in how I learned RDFa well enough
to be able to embed it into XHTML, and are curious how I was able to
disintegrate that into a series of M4 macros, you may want to read on in this
exceedingly technical post. Oh by the way, this very post also has an RDF / Semantic Web payload:
check it out.
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Yesterday Lauren and I went to Semantic Web
Austin’s event with Peter
Mika of Yahoo!
Research.
Peter delivered an excellent presentation on getting started with
RDFa.
I feel like one of the biggest challenges with getting started with Semantic
Web is that it’s so hard to get up and running quickly. Being a
W3C
specification, the documentation doesn’t immediately lend itself to easy
practical implementation. It seems that most of the time introductions for
beginners dance around specifications, semantics, IETF councils, and
theoretical specifications.
I think it probably turns off a lot of people actively working to advance the
cause. And the cause is worthy! Making the data on the web informative to
non-human agents will make for a far better internet experience, but the first
step has to be making it possible for Perl/Python/Ruby hackers, CMS tool
authors, PHP people etc. to actually think “Oh, I’ll embed these SemWeb”
features.
The last programmer-friendly product that integrated web of data concepts at
the user-programmer level was years ago when Matt at WordPress put in FOAF
ontology references in the WordPress code. I could be wrong here, but I’ve not
seen massive adoption as yet. Sometimes I feel like throwing my hands up and
saying “Can anybody give me a coherent story on how to do this, you know like
a ‘Hello, World’?”
Peter’s presentation was very accessible and “hands-on.” This was a welcome change.
Helpful resources are:
In the early evening we headed down south and met up with our friends Ryan and Jamie. After a bit of visit discussing semantic technology (Ryan works for the University’s library system and they’re certainly in the business of considering how to expose relationships between data stores), we headed to Trudy’s south. I had a great gulf shrimp chimichanga and a fine margarita.
We headed back to their home and Ryan cracked open a Glenfiddich 15-year
single malt which was smooth and oaky with richness. We had made substantial
progress into it, and conversing with our lovely ladies when we were joined by
Matt and Nicole. We hadn’t all been together just hanging out in many months,
so I really enjoyed it.
Most of the time when we see one another it’s during a dinner or a party, so
it was nice to have a quiet evening just catching up.
I found this presentation on information shadows by Mike Kuniavsky via Daniel’s site. Given my interest in Symbolic Systems, it really hit a sweet spot. Here’s a short abstract:
My presentation, called Information Shadows: How ubiquitous computing serializes everyday things (1.2MB PDF) is my attempt at showing how ubiquitous computing technology is, in essence, turning whole classes of everyday objects into serials, or services, by creating pervasive digital access to the objects’ metainformation, their information shadows. In the process, I talk about blenders, timeshares, Cuddle Chimps, City Carshare, and Exactitudes. I think it’s a fun talk, and I’m really happy to have had the opportunity to articulate these ideas in this forum.
Source
Around the 3rd section I lost the flow of the argument, so I wrote out this précis to try to help me keep the ideas straight. If, after seeing the original, you want to see an attempt at condensing the material read on.
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