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On Knowledge-Based Representations for Actionable Data …

I bumped into a professional acquaintance last week. After describing briefly a presentation I was about to give, he offered to broker introductions to others who might have an interest in the work I’ve been doing. To initiate the introductions, I crafted a brief description of what I’ve been up to for the past 5 years in this area. I’ve also decided to share it here as follows: 

As always, [name deleted], I enjoyed our conversation at the recent AGU meeting in Toronto. Below, I’ve tried to provide some context for the work I’ve been doing in the area of knowledge representations over the past few years. I’m deeply interested in any introductions you might be able to broker with others at York who might have an interest in applications of the same.

Since 2004, I’ve been interested in expressive representations of data. My investigations started with a representation of geophysical data in the eXtensible Markup Language (XML). Although this was successful, use of the approach underlined the importance of metadata (data about data) as an oversight. To address this oversight, a subsequent effort introduced a relationship-centric representation via the Resource Description Format (RDF). RDF, by the way, forms the underpinnings of the next-generation Web – variously known as the Semantic Web, Web 3.0, etc. In addition to taking care of issues around metadata, use of RDF paved the way for increasingly expressive representations of the same geophysical data. For example, to represent features in and of the geophysical data, an RDF-based scheme for annotation was introduced using XML Pointer Language (XPointer). Somewhere around this point in my research, I placed all of this into a framework.

A data-centric framework for knowledge representation.

A data-centric framework for knowledge representation.

 In addition to applying my Semantic Framework to use cases in Internet Protocol (IP) networking, I’ve continued to tease out increasingly expressive representations of data. Most recently, these representations have been articulated in RDFS – i.e., RDF Schema. And although I have not reached the final objective of an ontological representation in the Web Ontology Language (OWL), I am indeed progressing in this direction. (Whereas schemas capture the vocabulary of an application domain in geophysics or IT, for example, ontologies allow for knowledge-centric conceptualizations of the same.)  

From niche areas of geophysics to IP networking, the Semantic Framework is broadly applicable. As a workflow for systematically enhancing the expressivity of data, the Framework is based on open standards emerging largely from the World Wide Web Consortium (W3C). Because there is significant interest in this next-generation Web from numerous parties and angles, implementation platforms allow for increasingly expressive representations of data today. In making data actionable, the ultimate value of the Semantic Framework is in providing a means for integrating data from seemingly incongruous disciplines. For example, such representations are actually responsible for providing new results – derived by querying the representation through a ‘semantified’ version of the Structured Query Language (SQL) known as SPARQL. 

I’ve spoken formally and informally about this research to audiences in the sciences, IT, and elsewhere. With York co-authors spanning academic and non-academic staff, I’ve also published four refereed journal papers on aspects of the Framework, and have an invited book chapter currently under review – interestingly, this chapter has been contributed to a book focusing on data management in the Semantic Web. Of course, I’d be pleased to share any of my publications and discuss aspects of this work with those finding it of interest.

With thanks in advance for any connections you’re able to facilitate, Ian. 

If anything comes of this, I’m sure I’ll write about it here – eventually!

In the meantime, feedback is welcome.

April’s Contributions on Bright Hub

In April, I contributed two articles to the Web Development channel over on Bright Hub:

Annotation Modeling: In Press

Our manuscript on annotation modeling is one step closer to publication now, as late last night my co-authors and I received sign-off on the copy-editing phase. The journal, Computers and Geosciences, is now preparing proofs.
For the most part then, as authors, we’re essentially done.
However, we may not be able to resist the urge to include a “Note Added in Proof”. At the very least, this note will allude to:

  • The work being done to refactor Annozilla for use in a Firefox 3 context; and
  • How annotation is figuring in OWL2 (Google “W3C OWL2” for more).

Stay tuned …

CANHEIT 2008: York Involvement

York University will be well represented at CANHEIT 2008
Although you’ll find the details in CANHEIT’s online programme, allow me to whet your appetite regarding our contributions:

Synced-Data Applications: The Bastard Child of Convergence

At the Search Engine Strategies Conference in August 2006, in an informal conversation, Google CEO Eric Schmidt stated:

What’s interesting [now] is that there is an emergent new model, and you all are here because you are part of that new model. I don’t think people have really understood how big this opportunity really is. It starts with the premise that the data services and architecture should be on servers. We call it cloud computing – they should be in a “cloud” somewhere. And that if you have the right kind of browser or the right kind of access, it doesn’t matter whether you have a PC or a Mac or a mobile phone or a BlackBerry or what have you – or new devices still to be developed – you can get access to the cloud. There are a number of companies that have benefited from that. Obviously, Google, Yahoo!, eBay, Amazon come to mind. The computation and the data and so forth are in the servers.

My interpretation of cloud computing is summarized in the following figure.


Yesterday, I introduced the concept of Synced-Data Applications (SDAs). SDAs are summarized in the following figure.


SDAs owe their existence to the convergence of the cloud and the desktop/handheld.

Synced-Data Applications: The Future of End-User Software?

I recently asked: Is desktop software is dead?

Increasingly, I am of the opinion that desktop software is well on its way to extinction.

In its place, Synced-Data Applications (SDAs) have emerged.

One of the best examples I’ve recently run across is Evernote. Native Evernote applications exist for desktops (as well as handhelds) and for the cloud (e.g., via a Web browser). Your data is replicated between the cloud (in this example, Evernote’s Webstores) and your desktop(s)/handheld(s). Synced-Data Applications.

And with Google Gears, Google Docs has also entered the SDA software paradigm.

With SDAs, it’s not just about the cloud, and it’s not just about the desktop/handheld. It’s all about the convergence that this software paradigm brings.

A revised version of the figure I shared in the previous post on this thread is included below.

Once again, it emphasizes that interest is focused on the convergence between the isolated realm of the desktop/handheld on the one hand, and the cloud (I previously referred to this as the network) on the other.

It’s much, much less about commercial versus Open Source software. And yes, I remain unaware of SDA examples that live purely in the Open Source realm …