Aakash: A Disruptive Innovation in the Truest Sense
Much has been, and will be, written about the Aakash tablet.
[With apologies for the situational monsoonal imagery ...] As I awash myself in Aakash, I am particularly taken by:
- The order of magnitude reduction in price point. With a stated cost of about $50, marked-up prices are still close to an order of magnitude more affordable than the incumbent offerings (e.g., the iPad, Android-based tablets, etc.). Even Amazon’s Kindle Fire is 2-3 times more expensive.
- The adoption of Android as the innovation platform. I take this as yet another data point (YADP) in firmly establishing Android as the leading future proofed platform for innovation in the mobile-computing space. As Aakash solidly demonstrates, it’s about the all-inclusive collaboration that can occur when organizational boundaries are made redundant through use of an open platform for innovation. These dynamics just aren’t the same as those that would be achieved by embracing proprietary platforms (e.g., Apple’s iOS, RIM QNX-based O/S, etc.).
- The Indian origin. It took MIT Being Digital, in the meatspace personage of Nicholas Negroponte, to hatch the One Laptop Per Child initiative. In the case of Aakash, this is grass-roots innovation that has Grameen Bank like possibilities.
“An innovation that is disruptive allows a whole new population of consumers access to a product or service that was historically only accessible to consumers with a lot of money or a lot of skill. Characteristics of disruptive businesses, at least in their initial stages, can include: lower gross margins, smaller target markets, and simpler products and services that may not appear as attractive as existing solutions when compared against traditional performance metrics.”
- Like Aakash, I am of Indian origin. My Indian origin, however, is somewhat diluted by some English origin – making me an Anglo-Indian. Regardless, my own origin may play some role in my gushing exuberance for Aakash – and hence the need for this disclaimer.
- I am the owner of a Motorola Xoom, but not an iPad. This may mean I am somewhat predisposed towards the Android platform.
Targeting Public Speaking Skills via Virtual Environments
Recently I shared an a-ha! moment on the use of virtual environments for confronting the fear of public speaking.
The more I think about it, the more I’m inclined to claim that the real value of such technology is in targeted skills development.
Once again, I’ll use myself as an example here to make my point.
If I think back to my earliest attempts at public speaking as a graduate student, I’d claim that I did a reasonable job of delivering my presentation. And given that the content of my presentation was likely vetted with my research peers (fellow graduate students) and supervisor ahead of time, this left me with a targeted opportunity for improvement: The Q&A session.
Countless times I can recall having a brilliant answer to a question long after my presentation was finished – e.g., on my way home from the event. Not very useful … and exceedingly frustrating.
I would also assert that this lag, between question and appropriate answer, had a whole lot less to do with my expertise in a particular discipline, and a whole lot more to do with my degree nervousness – how else can I explain the ability to fashion perfect answers on the way home!
Over time, I like to think that I’ve approved my ability to deliver better-quality answers in real time. How have I improved? Experience. I would credit my experience teaching science to non-scientists at York, as well as my public-sector experience as a vendor representative at industry events, as particularly edifying in this regard.
Rather than submit to such baptisms of fire, and because hindsight is 20/20, I would’ve definitely appreciated the opportunity to develop my Q&A skills in virtual environments such as Nortel web.alive. Why? Such environments can easily facilitate the focused effort I required to target the development of my Q&A skills. And, of course, as my skills improve, so can the challenges brought to bear via the virtual environment.
All speculation at this point … Reasonable speculation that needs to be validated …
If you were to embrace such a virtual environment for the development of your public-speaking skills, which skills would you target? And how might you make use of the virtual environment to do so?
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.
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.
Google Chrome for Linux on Bright Hub: Series Expanded
I recently posted on a new article series on Google Chrome for Linux that I’ve been developing over on Bright Hub. My exploration has turned out to be more engaging than I anticipated! At the moment, there are six articles in the series:
- Google Chrome for Linux: Building from Source
- Google Chrome for Linux: Testing and Contributing
- Google Chrome for Linux: The WebKit Web Browser Engine
- Google Chrome for Linux: The V8 JavaScript Engine
- Google Chrome for Linux: Why V8 Bests WebKit’s JavaScript Engine
- Google Chrome for Linux: Android Availability
I anticipate a few more …
It’s also important to share that Google Chrome for Linux does not yet exist as an end-user application. Under the auspices of the Chromium Project, however, there is a significant amount of work underway. And because this work is taking place out in the open (Chromiun is an Open Source Project), now is an excellent time to engage – especially for serious enthusiasts.
CANHEIT 2008: Enhanced Abstract
The program specifics for CANHEIT 2008 are becoming available online.
The enhanced abstract for one of my presentations is as follows:
From the Core to the Edge: Automating Awareness of Network Topology through Knowledge Representation
Ian Lumb – Manager Network Operations, Computing and Network Services (York University)
Abstract
Like many other institutions of higher education, York University makes extensive use of Open Source software. This is especially true in the case of monitoring and managing IP (Internet Protocol) devices. On the monitoring front, extensive manual configuration is currently required to make monitoring solutions (e.g., NAGIOS) aware of the topology of the York network. And with respect to managing, NetDisco automatically discovers assets placed on the network, but is unable to abstract away unnecessary complexity in, e.g., rendering schematics of the network topology. These and other examples suggest that NAGIOS and NetDisco operate in the realm of data, and possibly information, but are unable to envisage network topology from a knowledge-representation perspective. Thus the current focus is on applying a recently developed knowledge-representation platform to such routine requirements in network monitoring and management. The platform is based on Sematic Web standards and implementations and has already been proven effective in various scientific contexts. Ultimately our objective is to extract data automatically discovered by NetDisco, represent it using the knowledge-based platform, and transform a topology-aware representation of the data into configuration data that can be ingested by NAGIOS.
A visual representation of the approach is illustrated below.
CANHEIT 2008: York Involvement
- A BoF session on QoS (I blogged about this a little while back …)
- A presentation on semantic topologies
- A presentation on datacentre design and implementation
- A presentation on DRP
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 …
