Bill’s slides are here, and mine are embedded below.

Thanks to Paul for the invite, and to the audience for braving an intermittently (very) wet Manchester evening to spend a few hours discussing Linked Data, the Semantic Web, and related topics; it was fun.

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Before going any further, let’s get a few things crystal clear;

1. The recent success of the Linked Data meme is long overdue, very welcome, and entirely capable of carrying the Web of Data far beyond its current niche adherents. A lot of my current work involves arguing that more organisations should adopt this approach;
2. The Resource Description Framework, RDF, is a key — and powerful — piece in W3C‘s Semantic Web Architecture. Since its earliest days, I have played various parts in advocating the potential of RDF and will continue to do so;
3. RDF is an obvious means of publishing — and consuming — Linked Data powerfully, flexibly, and interoperably. I will continue to argue this, and to advocate its wider adoption.

So far, so good.

The problem, I contend, comes when well-meaning and knowledgeable advocates of both Linked Data and RDF conflate the two and infer, imply or assert that ‘Linked Data’ can only be Linked Data if expressed in RDF.

This dogmatism makes me deeply uncomfortable, and I find myself unable to agree with the underlying premise.

The rest of this post attempts to explain why, hopefully more lucidly than I or those with whom I was debating managed on Friday evening via the largely unsuitable medium of the 140 character tweet.

Andy Powell started things off lucidly enough on Friday, asking;

“is there an agreed name for an approach that adopts the 4 principles of #linkeddata minus the phrase, ‘using the standards (RDF, SPARQL)’ ??”

I was amongst those to respond, suggesting as I usually do that;

“well, personally, I’d argue that Linked Data does NOT require that phrase. But I know others disagree…  ”

Other pieces of that conversation can be extracted from the stream; start by scrolling to the bottom, find Andy’s tweet, and work back toward the top.

It’s worth noting that two of those arguing most vehemently against me were former colleagues Ian Davis and Leigh Dodds. I have massive respect for the technical prowess of both (which is certainly greater than my own), and have learned a great deal from Ian in particular over the years that we have known one another. This issue, though, is one on which we have long disagreed, and it was interesting to see the subject of many a difference of opinion in the bars of various conference hotels spill into this public arena.

Anyway, now let me try to explain what I meant.

Perhaps the most commonly cited definition for Linked Data is the one to which Andy was referring; Sir Tim Berners-Lee‘s Linked Data – Design Issues document. It’s worth noting that this document is clearly flagged (in the current version amended on 18 June 2009, at least) as being both a ‘personal view only’ and ‘imperfect but published.’ So a very long way from being a ‘standard,’ ‘specification,’ or ‘definition,’ but certainly still a pretty good starting point, and one to which I often direct clients and others.

Berners-Lee begins,

“The Semantic Web isn’t just about putting data on the web. It is about making links, so that a person or machine can explore the web of data.  With linked data, when you have some of it, you can find other, related, data.”

(my emphasis)

That sounds good, doesn’t it? Indeed, we talked about that on the Linked Data panel I moderated at the recent Semantic Technology Conference, and I’ve embedded the video here.

It is the next section of Berners-Lee’s document that is used to validate the view that Linked Data needs RDF;

“1. Use URIs as names for things

2. Use HTTP URIs so that people can look up those names

3. When someone looks up a URI, provide useful information, using the standards (RDF, SPARQL)

4. Include links to other URIs. so that they can discover more things.

(my emphasis)”

On one reading, an unambiguous validation of the view with which I disagree. On another, a suggestion of best practice, expressed as part of a ‘personal view’ with which we are perfectly entitled to take issue.

Would the zealots be calmed by the simple insertion of ‘preferably’ or ‘ideally,’ immediately after point three’s second comma? Maybe. Or perhaps the fires of Linked Data’s self-appointed Inquisition would be stoked for Berners-Lee himself.

Talk of Linked Data, Open Data, the Web of Data and related concepts in recent years have led to a quite remarkable shift in attitude amongst individuals, public bodies and private corporations. Almost everywhere my work takes me, clever people are seriously grappling with the implications of consuming from or contributing to these emerging ecosystems. Not all of their questions have good answers, and not all of the technological, strategic and business implications have necessarily been fully worked through. But these people are asking the questions, and they are asking them in all seriousness.That is a dramatic and welcome shift.

Some, such as the BBC, Thomson Reuters and the UK Government’s Central Office of Information are sufficiently persuaded of the benefits to take risks and to open the previously closed in taking a lead. Others will follow, as fears are assuaged, doubts eased, and benefits realised.

Despite this undoubted progress, the green shoots of a Linked Data ecology remain delicate. By moving from a message that stresses the value of unambiguous and web-addressable naming (HTTP URIs), providing ‘useful information,’ and enabling people to ‘discover more things’ by linking toward a message that elevates one of the best mechanisms (RDF) for achieving this to become the only permissible approach, we do the broader aims great harm.

Yes, those already in the club will probably be very pleased with the purity and functionality of the toys in their playground. But they will have barred a far larger group with data to share, a willingness to learn, and an enthusiasm to engage. At best, they will have slowed the growth of the pool of Linked Data quite dramatically. At worst, they will have created an increasingly irrelevant backwater that more pragmatic people will simply route around. Perhaps, in their pragmatism, those people will now never look seriously at RDF and its power, scared away by the fervour of those who sought to elevate it too high, and too fast.

What are we after? More Linked Data, or more RDF? I sincerely hope it’s the former.

So let’s see loads more Linked Data, and plenty of evangelism as to why RDF could be the best way to do it. But let’s not ostracise the vast majority of potential participants, contributors and beneficiaries in the world of Linked Data, just because they haven’t wholeheartedly embraced RDF yet.

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As European readers are doubtless aware, the EC has traditionally been a generous funder of research across Europe’s member states, with Digital Libraries, the Semantic Web and more owing much to the largesse of Europe’s massive ‘Framework Programme‘ funding cycles. We’re currently in the midst of the Seventh Framework Programme, and a few hundred of the academics and technologists hoping to secure some of the €Millions available for ‘Technologies for Information Management‘ have gathered in soggy Luxembourg to hear what they can bid for, to hear how to bid, and to engage in the funding world’s rather bizarre equivalent of Blind Date by pitching their wares to prospective partners.

I’ve been asked to talk about some of the trends and issues around ‘Big Data,’ to provide a context for the technological discussions to follow, and to illustrate some of the ways in which cutting edge implementations of the sort likely to be proposed might solve real problems.

My slides are on Slideshare and embedded, above, and begin by suggesting that the use of ‘the language of catastrophe’ in describing the ‘flood’ of information around us perhaps sets everything off on the wrong foot. Yes, there’s a lot of information out there… but there’s not too much, and maybe we shouldn’t be attempting to control all of it anyway…

European Commission-funded projects were amongst the first to make serious attempts to ‘control’ and ‘manage’ the early Web, with some suggestions that we could (and should) catalogue Web pages just like books in a library. Some of those laboriously curated, instantly obsolete, and hopelessly under-representative Web ghettos still exist today; but the mainstream Web has moved far beyond them, embracing more scalable and effective combinations of machine processing and lightweight community recommendation. Even in their heyday, those for whom these resources were created were all too often to be found applying their efforts to routing around these obstructions to the free flow of information across the Web.

As the volume of data available to us grows, it presents massive new opportunities as well as significant technological and social challenges. Twitter is just one example of the rise of the ‘real-time’ Web, and connected devices such as the iPhone and Google’s Android devices fundamentally shift the ways in which we consume and contribute to the ever-accelerating flows of data.

Use, re-use and control of data, too, are increasingly topical issues with which we should be concerned. The rise of licensing frameworks such as CC0 and the Open Data Commons are part of an attempt to reduce ambiguity in the ways that data may be repurposed, and expectations grow daily that data will be available; whether from Government, community groups or the private sector. Privacy, security, provenance and trust all come into play, with a path to be diplomatically steered between those too blasé to recognise the real issues at stake and those too cautious to countenance progress perceived to be at their expense.

Moving the quantities of data involved is becoming a serious challenge, too, and a generation of researchers accustomed to ‘simply’ throwing data into the Cloud for later analysis, sharing or retrieval must increasingly grapple with latency and bandwidth. Physical proximity of data to computation might actually matter again, and more than one of the Cloud’s biggest players have been heard to suggest that physical media might actually be the most cost-effective way to move these mountains of data around the globe.

I look forward to seeing what the nascent projects likely to coalesce over the next 24 hours contribute to understanding and progress with any or all of these… and hope that my presentation plays its part in shaping their thinking, their proposals and their outcomes.

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The notions of core and context are, of course, most often associated with Geoffrey Moore, and one of his sites defines them, thus;

Core

“Any activity which creates sustainable differentiation in the target market resulting in premium prices or increased volume. Core management seeks to dramatically outperform all competitors within the domain of core. (Note this use of the term is unrelated to either core competence, which describes differentiated capability, or core business, which describes categories accounting for a high percentage of overall revenues.)”

Context

“Any activity which does not differentiate the company from the customers’ viewpoint in the target market. Context management seeks to meet (but not exceed) appropriate accepted standards in as productive a manner as possible.”

Writing in last weekend’s Financial Times, Gerrit Wiesmann tells us that;

“We’ve been waiting for trains since 1840, the year a British parliamentary committee invented mass transportation by ruling that rail traffic should be exclusively in the hands of the companies that owned the track. It’s an odd notion now, but in the years before that decision, a debate raged about how to use rails. In the 1820s, the British railway visionary Thomas Gray called for a national network for use by private vehicles. He reckoned traffic in and out of London could be handled by 12 parallel ‘rail-ways’.”

Here, as elsewhere, ideas given serious consideration at the birth of an industry are superseded as that industry matures and sustainable business models begin to emerge.

There will always be areas in which technology companies invest their own human capital rather than buying in services and products from third parties. The traditional view, largely captured in Moore’s terminology, holds that companies gain most by focussing their own efforts upon the differentiating aspects of their business whilst making use of supporting services from third parties to enable concentration upon those differentiators. It will tend to be cheaper and ‘easier’, so the argument goes, to pay for commodity services from a third party rather than develop everything in-house from scratch.

In the early stages of any technological wave, there is an understandable tendency to develop and control far more of the stack within a single organisation. Various players enter a nascent market, and attempt to shape it to their needs at the same time as laying the foundations for what they hope will be a successful product or service. Without agreement on standards and specifications, there is very little interoperability. With an emphasis upon attracting and growing a customer base, there is little incentive to make it easy for users to compare offerings with – or move to – the competition. With a fluid understanding of the final product and its differentiating features, there is little clear understanding of that which will be ‘core’ as opposed to that which will merely be ‘context.’ Internal and external pressures encourage, and almost require, an approach that is closed and all-encompassing.

The problem, it seems, is in making that move from a nascent market toward the point at which certain aspects of the technology stack are fit for commodification; the point at which a healthy and competitive ecosystem can begin to emerge that increases customer choice whilst lowering development and running costs. Looking at aspects of the Cloud Computing and SaaS arenas, we must surely be reaching the point at which numerous homegrown technology stacks become increasingly counterproductive? In the Semantic Web space, too, that early burst of innovation is becoming unnecessarily expensive to maintain as one company after another continues to concern themselves with segments of the problem space that might easily be made a commodity.

Look, for example, at the number of Semantic Technology companies continuing to pour effort into building, scaling and maintaining a basic ontology. The ontology is rarely the point of the company. It is simply something they need to have in order to get on with the business at hand. How many of them are ‘wasting’ time recording the fact that Gordon Brown is the UK Prime Minister, or that Beverley is in East Yorkshire, which is in England, which is in the United Kingdom, which is in Europe?

A recent conversation with Hapax CEO Mark Redgrave confirmed the extent to which they are having to focus upon ontology construction with Amplify. Refreshingly, though, he was extremely open to the notion of gaining value from a more open and generic ontology upon which Hapax and others could build, add value, and compete. In the SaaS space, too, Apprenda CEO Sinclair Schuller has some interesting ideas with regard to enabling others to build their own Software as a Service offerings on top of a common platform that begins to look increasingly like a commodity. It will be interesting to see the extent to which the reality of his company’s SaaSGrid is able to match that vision.

I have spent (too much!) time in the formal standards making process, and would be the last to even consider suggesting that freeform innovation and commercial creativity be snuffed out in favour of protracted and painful rounds of negotiation, specification and never-ending compromise.

However, it seems apparent that early innovators in a given market (Amazon with EC2, Salesforce, etc) often see little incentive to open up and behave less proprietarily. It is in their interests for every competitor to have to reinvent all the wheels that those early entrants first conceptualised. The shift needs to be driven by their competitors, some of whom will be sufficiently successful that they disrupt the market conditions in which incumbents dominate to such an extent that customers are incentivised to consider switching.

A little reinvention is a good thing. It encourages creative thinking, and probably leads to refinement, iteration, and further innovation. Perpetuated at the expense of opening up a nascent market, it becomes a tool of monopoly and ultimately counter-productive for all concerned.

Perhaps it is only at this point that those at the top of a market segment are able to realise the benefits of letting go a little, and of relegating much of what they do to the status of mere context.

Image of a bicycle with square wheels © Michael Vroegop 2007, and licensed with a Creative Commons Attribution License.

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