It is a quite remarkable feeling to watch as the pieces fall into place and the picture, anticipated for so long, is finally revealed in all its splendour. As with any jigsaw that lacked a guiding picture on the box, the final result is that inevitable mix of vindication and surprise. Some areas of the picture are wholly unexpected, some look as one predicted, whilst across most of the image there are new facets to explore in familiar faces, anticipated dioramas to compare with long-held expectation, and presumptions to challenge or validate.
Recent advances in the business of Cloud Computing form just such a picture, and reach out to encompass previously unrelated aspects of Web 2.0, the Semantic Web, Platform Computing, Software as a Service (SaaS) and the economics of Disruption. Not merely some game of buzzword bingo on an unprecedented scale, it is becoming increasingly easy to see the opportunities for a significant shift in the way that we access computational resources; and to recognise that the walls separating organisations from their peers, their partners, their competitors and their customers will become ever-more permeable to the flow of data upon which those distant machines will compute.
There is much to understand that is already known in related fields, and much to discover that only becomes possible in this space. One early challenge is in carving a discrete niche for the place toward which we are moving with such rapidity. Far more than ‘just’ the Cloud; an evolution on from the playful flippancy that diminishes so many of Web 2.0’s poster children; and difficult to relate to the mainstream misconceptions of the Semantic Web’s complexity. Yet this new place is the sum of these parts, and far greater than they can ever be alone. So do we extend the already ephemeral notion of Cloud Computing? Do we appropriate the ‘next big thing’ label of Web 3.0? Or do we need a healthily fresh attitude to business computing’s apparently insatiable desire to apply labels?
First, though, let us consider the shape of this thing that is taking on more substance with each passing day.
Reporting on last week’s Web 2.0 Summit in San Francisco, CNET’s Dan Farber notes that
“The cloud was omnipresent,”
before going on to close his report with;
“cloud computing won’t be very compelling without what is variously called Web 3.0 or the Semantic Web.”
Indeed.
For too long, the emphasis in Cloud Computing circles has been almost exclusively upon provision of rapidly scalable and ad hoc remote computing on top of cost-effective commodity hardware. The Cloud play from Salesforce, Amazon’s EC2 and the rest has been dominated by the implicit assumption that these Cloud-based resources are an extension of the corporate data centre; a way to simply reduce the costs of enterprise computing.
There is value in this business, but there are bigger opportunities.
Nick Carr is amongst those to fear that a small number of players may come to dominate the provision of Cloud resources. He outlines many of these arguments in his latest book, The Big Switch, and more recently has been involved in an interesting discussion with Tim O’Reilly on the topic. Justin Leavesley shares some of Talis‘ views on the economics behind all this over on Nodalities, broadly agreeing with Tim O’Reilly;
“It’s pretty clear that utility cloud computing is highly capital intensive so it should come as no surprise that there are powerful economies of scale to be had. But the bottom line is that you are talking about plant and power. These are rival goods, scarce resources that are created and consumed. This is not different from many utility industries with one exception: the distribution network has global reach, already exists and is very cheap compared to existing utility distribution networks. It is a lot cheaper to access a computing resource on the other side of the planet than it is to send electricity or gas across the globe… [So] what is to stop economies of scale turning this into a global natural monopoly?
Actually, unless there are some large network effects, quite a lot stops single companies ruling entire industries. For a start, without network effects, economies of scale tend to run out: the curve is usually U-shaped. Telecoms, Gas, rail companies have strong network effects from their infrastructure-it makes little sense to have duplicate rail networks or gas networks in a country. Utility computing does not have this advantage because the distribution network is not owned by them.”
Continuing the conversation, Carr captures the usual widely held perception of Cloud Computing nicely;
“The history of computing has been a history of falling prices (and consequently expanding uses). But the arrival of cloud computing – which transforms computer processing, data storage, and software applications into utilities served up by central plants – marks a fundamental change in the economics of computing. It pushes down the price and expands the availability of computing in a way that effectively removes, or at least radically diminishes, capacity constraints on users. A PC suddenly becomes a terminal through which you can access and manipulate a mammoth computer that literally expands to meet your needs. What used to be hard or even impossible suddenly becomes easy.”
This is quite true, but continues and further entrenches the misapprehension that the Cloud is little more than an adjunct to the corporate data centre; a misapprehension that we shall get down to challenging in a moment.
First, though, there is a growing recognition that today’s market leaders will inevitably need to become more interoperable if this business segment – and they – are to grow. The proprietary nature of their offerings today may allow them to innovate ahead of the standards process (that will be shaped in large part by the lessons they learn), and the relatively high cost of switching to a competitor today may give each the critical mass upon which to invest and grow, but the characteristics of the current market are clearly the characteristics of a nascent market; computing’s new Wild West. As so often before, standardisation, true competition, mainstream adoption and commoditisation will all follow as we move toward phases 2 and 3 of Gartner analyst Thomas Bittman’s intriguing ‘evolution of the Cloud Computing market.’ Similarly, Erica Naone offers a useful overview of Cloud Computing’s open source component in Technology Review this month. None of the projects she covers are a significant challenge to Amazon’s EC2, Microsoft’s Azure, Salesforce’s force.com or Google’s App Engine… yet. But together they help to keep these commercial entrants honest, and remind all of us that switching costs can be brought very low indeed if the pain of the status quo becomes too great.
Writing ‘Welcome to the Data Cloud?‘ for ZDNet last month, I began to explore the important role that data could and should play in the Cloud;
“Just as ‘we’ used to duplicate and under-utilise computational resources, so we do something very similar with our data. We expensively enter and re-enter the same facts, over and over again. We over-engineer data capture forms and schemas, making collection exorbitantly expensive, whilst often appearing to do all we can to limit opportunities for re-use. Under the all-too-easy banners of ’security’ and ‘privacy’ we secure individual data stores and fail to exploit connections with other sources, whether inside or outside the enterprise.
In a small way, the efforts of the Linked Data Project’s enthusiasts have demonstrated how different things should be. The cloud of contributing data sets grows from month to month, and the number of double-headed arrows denoting a two-way linkage is on the rise. Even the one-way relationships that currently dominate the diagram are a marked improvement on ‘business as usual’ elsewhere on the data Web; even in these cases, data from a third party is being re-used (by means of a link across the web) rather than replicated or re-invented. Costs fall. Opportunities open up. Both resources, potentially, improve. The strands of the web grow stronger.“
It is here, in the use and reuse of data, that the potential of the Cloud will be realised. Back in the previously cited conversation between Nick Carr and Tim O’Reilly, O’Reilly himself came very close to saying so;
“In short, Google is the ultimate network effects machine. ‘Harnessing collective intelligence’ isn’t a different idea from network effects, as Nick argues. It is in fact the science of network effects - understanding and applying the implications of networks.
I want to emphasize one more point: the heart of my argument about Web 2.0 is that the network effects that matter today are network effects in data. My thought process (outlined in The Open Source Paradigm Shift and then What is Web 2.0?, went something like this:
- The consequence of IBM’s design of a personal computer made out of commodity, off- the-shelf parts was to drive attractive margins out of hardware and into software, via Clayton Christensen’s ‘law of conservation of attractive profits.’ Hardware became a low margin business; software became a very high margin business.
- Open source software and the standardized protocols of the Internet are doing the same thing to software. Margins will go down in software, but per the law of conservation of attractive profits, this means that they will go up somewhere else. Where?
- The next layer of attractive profits will accrue to companies that build data-backed applications in which the data gets better the more people use the system. This is what I’ve called Web 2.0.
It’s network effects (perhaps more simply described as virtuous circles) in data that ultimately matter, not network effects per se.”
(my emphasis)
Talis CTO Ian Davis would appear to agree, commenting;
“People need to be investing in their data as the long term carrier of value, not the applications around them… the data is more likely to persist than the software so it’s important to get the data right and take care of it.”
Salesforce CEO Marc Benioff, too, used his Dreamforce User Conference this month to move a company long associated with the ‘data centre extending’ Cloud firmly in the direction of embracing data and the network. As Krishnan Subramanian noted on Cloud Ave before the keynote,
“Till now, the Force.com platform served business users to develop apps that can be used internally within an organization. They have to tap into Force.com APIs from outside platforms to offer customer facing web apps. With the new initiative, it becomes easy for customers to allow the internet users to “interact” with their data.”
Over on VentureBeat, Anthony Ha had more;
“Salesforce.com wants to become an even big player in the cloud computing market with a new service called Force.com Sites, which allows companies to host public-facing web applications in the Force.com platform. That means Salesforce — nominally a maker of customer relationship management (CRM) software, but also an increasingly important platform for business-related applications — is moving closer to direct competition with cloud giants like Amazon Web Services and the Google App Engine.”
Locked away within an organisation, and only accessed by that organisation’s applications, data cannot be put to full use. Much of the value in each individual datum lies in comparing it to other measurements, in delving into detail and in pulling right back to observe the bigger picture.
Organisations believing that either the big picture or the detail reside within their own systems alone are woefully misguided. Even the most specialised, the most proprietary, the most confidential of data only reveal their true value when placed in context, and that context is all the richer when informed by numerous perspectives.
Cloud Computing, and the various *aaS movements, have finally brought us to a place where the fiercely guarded and tightly delineated boundaries between the organisation and those outside it may become permeable in ways that should benefit the organisation rather than threaten it. Data is just a resource. In the terminology of Geoffrey Moore most data is often mere context, and there are savings to be made both in reusing the data of others or in re-selling necessary context to those prepared to pay. Some data, of course, is core to the business, and this may continue to receive the same reverence and protection that we misguidedly apply to the entire database today. Even here, though, the opportunities afforded by (controlled?) sharing may outweigh any desire to maintain data protectionism.
The language of Groundswell offers opportunities to go further, to embrace and to exploit the behaviours and the motivations of customers and the wider Web.
There is clearly far more to write in clarifying this view of both the components and the whole, but as it passes 2,000 words this particular blog post has perhaps gone on long enough.
For now, then, I should conclude by asking what role the Semantic Web has to play in any of this.
The Semantic Web, with its unadulterated recognition of the primacy of the web’s hyperlink? The Semantic Web, designed from the outset to convey context and relationships derived from data spread across the Web? The Semantic Web, supported by technologies that operate openly and at Web scale?
Isn’t it obvious yet?
Returning to the Web 2.0 Summit with which this post began, another presentation was from Kevin Kelly, founding editor of Wired Magazine. As I wrote this post, I referred to Steve Gillmor and Nicole Ferraro, from whose reports I inferred that Kelly had built upon an earlier presentation (that I greatly enjoyed), in which he argued;
“You have to be open to having your data shared… which is a much bigger step than just sharing your web pages or your computer.”
Fact-checking before hitting publish, I notice that last week’s video is now up, here, and Kevin’s championing of the primacy of data in the cloud resonates with every word I’ve just written.
Yep. Here we go, on a journey toward Kevin Kelly’s “World Wide Database.”
In subsequent posts I’ll explore some more of the detail, and I hope you’ll stick around for the journey.
Storm Clouds image © ‘shidairyproduct‘ 2008. Shared on Flickr, and licensed with a Creative Commons Attribution License. Converted to a jigsaw by Big Huge Labs.
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Paul Miller works at the interface between the worlds of Cloud Computing and the Semantic Web, providing the insights that enable you to exploit the next wave as we approach the World Wide Database.
14 Comments until now.
[...] The presentation was reported at the time by Steve Gillmor and Nicole Ferraro, but video is now also available. I explore the implications of Kelly’s premise in the context of Cloud Computing here. [...]
Great post to start your new blog with, Paul. Thanks.
[...] Cloud Computing is so much more than a computer in the Cloud [...]
Perfectly agree with your views, cloud computing has to be a milestone on the journey towards a data cloud.
The hitch as I see it is this – organizations have grown too attached to outmoded notions of captive computing power, captive IP! and captive data to realize the benefits of a open approach to all these. Though the connections from cloud computing to cloud data are apparent, we have to be aware of the perception chasm people and organizations will have to cross to open up their data, for the vision of semantic web to come to life.
Speedier adoption of cloud computing will be a first step, especially if done by the traditionally paranoid segments like financial services, who ironically will benefit most from using the ideas from the semantic web!
Mahesh – thanks for the comment. I would agree that organisations have grown used (for good reasons and bad) to the notion of ‘captive’ computing, IP and data, and there’s a lot of work to do in changing that mindset.
I think that we’ve already seen the shift away from captive computing with growing adoption of Cloud computing, and the more recent move to open Cloud-based services up as more than simply an adjunct to the data centre.
Initiatives such as OpenCalais over at Thomson Reuters show the kinds of things that begin to happen when we’re a little less precious about our data, and that trend will also accelerate as we begin to see further compelling demonstrations of the benefits.
[...] 2006 June 2006 May 2006 April 2006 Incoming LinksAllan's Library: Web 2.0 PublishingCloud Computing is so much more than a computer in the Cloud …Panlibus » Blog Archive » Clay Shirky in Conversation – Here Comes …links for [...]
[...] known as Web 3.0. Here’s a linkdump from my Friday eve surfing: Paul Miller: Cloud Computing is so much more than a computer in the Cloud OpenCalais: Life in the Linked Data Cloud: Calais Release 4 Richard Cyganiak: Web of Data Kevin [...]
Two weeks ago I sat on a panel discussion on Cloud Computing with some of the heavy hitters inthe game. As an independent software vendor, my part of the presentation was to discern truth from hype in all of the claims being made. Needless to say, I got a lot of feedback–so much so that I wrote a follow up article on it:
http://www.smartertools.com/blog/archive/2008/11/20/cloud-computing-challenges-benefits-and-the-future.aspx
It is important for us to remember what Cloud Comuting is and what it is not.
Be well,
Jeffrey J. Hardy
http:www.smartertools.com
[...] delighted that a modified version of my very first post for this blog was reproduced as a guest post on ReadWriteWeb this [...]
[...] Cloud Computing is more than a Computer in a Cloud by Paul Miller (hat tip to ReadWriteWeb) Share and Enjoy: [...]
Great post Paul.
Seems there are a few issues to sort through with cloud computing and the semantic web.
1 First, what level of capability is being provisioned — infrastructure (IaaS), Platform (Paas), and/or Software (Saas)? There are some definitional differences depending on which providers you talk to.
2 Second, when you speak about Platform as a Services, then one of the major considerations is whether the applications require transactional logic (as in ACID principles used with databases), or whether the processing can be non-transactional (ala Google, Yahoo, MSN, etc. and anyone else who has to read, index, and search against a very large amount of pages and files, very fast.)
3 Third, the convergence of semantic web of data and cloud has already begun, and there are some very interesting examples of linking together of different sources and kinds of information (e.g., database, document, flat file, web page, etc.) . Here the question is one of how far you need to go to make sense of different forms of information — data, text, table, graphic, image, video, audio, sensor feeds, etc. You need a broad repertoire of techniques that are specific to the type of “sign system” your working with. John Sowa says that “conceptual graphs” become the lingua franca through which these different ways of encoding ideas can be interrelated.
4 Fourth, problems of semantic processing at scale become performance issues. The grail for everyone is to reason in “polynomial time”. That is, as you add more instances, or the amount of knowledge representation, or path length of reasoning increases, the reasoning system performance should grow linearly rather than exponentially (e.g, 2 seconds for the first 10, 2 minutes for the next 100, 2 hours for the next 1000. Semantic web reasoning today doesn’t scale. It may work pretty well for RDFs kinds of inferencing, but degrades pretty rapidly when you start working with the additional semantic of OWL. Cloud computing techniques, it turns out, can help a lot to scale semantic inferencing. This is already happening. However, it means changes some software architecture and engineering practices.
5 Fifth, semantic web (description logic) reasoning itself hardly exhausts the topic of knowledge representation and reasoning. There is lots of interesting stuff people deal with that goes beyond description logic, for example: conditional situation awareness, causality, conflict, uncertainty, counterfactuals, reasoning over goals, desires, and beliefs. Questions of guilt or innocence, or life and death, or conflicting values, are about much more than logical truth or falsity of language statements. While reasoning is often divided into four general categories: induction, abduction, deduction, and analogy, it is more accurate to say that there probably as many forms of reasoning as there are forms of knowledge representation. Computers in the coming era will need to handle multiple kinds of knowledge, information and reasoning as well as combine them. From a performance point of view, the goal remains to handle all forms of reasoning in “polynomial time.” Here too, there have been advances which demonstrate the practicality of this, as well as its applicability to cloud computing.
Mills makes a very good point with regard to the alphabet soup of acronyms available to us: SaaS, IaaS, PaaS, etc. Even though each of theses is different, the purveyors of each portray their respective offerings as whatever the customer needs.
At SmarterTools we are developing products for SaaS–strictly defined. Microsoft’s Azure is likely best referred to as PaaS. Conventional co-location Cloud Computing is likely IaaS (Think Amazon Web Services).
The mind reals. Merriam-Webster provides a Dictionary-as-a-Service, but it is no help to us here.
Be well,
Jeffrey J. Hardy
http://www.smartertools.com
Related article on Cloud computing:
http://www.smartertools.com/blog/archive/2008/11/20/cloud-computing-challenges-benefits-and-the-future.aspx
Mills – some good points, as usual…
There does seem to be some emerging clarity around the IaaS/ PaaS/ SaaS/ *aaS bundle, as people become more explicit about whether it’s a *computer* they’re after, a *capability* to build something of their own, an *application* or whatever.
Given existing attitudes to corporate data, I do wonder if we’re more likely to see the semantic problems to which you refer being addressed on private Clouds long before they take hold at scale across the open Web…
Jeff
Hi, and thanks for stopping by. I read your http://www.smartertools.com/blog/archive/2008/11/20/cloud-computing-challenges-benefits-and-the-future.aspx with interest back in November, and will definitely be keeping an eye on what you’re doing at SmarterTools…