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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Much has been written about growing Enterprise use of social media (usually Twitter, these days) to successfully track and mitigate customer complaint. Many have been quick to spot that the disproportionately high cost of satisfying (or, more cynically, silencing) these early adopters is unlikely to scale effectively as an increasingly large cohort of customers move onto these services, and it must remain an open question as to whether ComcastCares and its peers can survive any move to the mainstream in recognisable form.

It appears, though, that Enterprise engagement in the social sphere changes the game far more significantly than merely enabling a select few twitterati to jump the Customer Support queue, and that this change is worth effort and investment in order to ensure that it does scale. What’s actually happening is that a relationship is being enabled between a brand and what Seth Godin might recognise as its tribe; a relationship in which interactions are no longer driven predominantly by the desire to seek redress. Rather than only raising those issues serious enough for us to have written letters or endured telephone muzak in the past, we now comment on issues at the periphery of a brand. Collectively, we’ve moved from simply complaining about the worst failures of companies, their products and their employees, toward emitting an impressive stream of FYIs. Individually insignificant, and possibly unimportant, together these light touches on and around a brand build into an ever-changing and valuable commentary that brands and the corporations they front would do well to take notice of. The minor niggles about an otherwise exemplary service, the human touches that made us smile, the odd inconsistencies in a polished persona; none are enough to make us pick up the phone, but we comment upon them endlessly in Twitter, Facebook, FriendFeed and elsewhere, and by tapping into this fundamentally honest stream of consciousness there is much for those about whom we comment to learn. Good companies probably already know about fundamental failings in a product long before their customer support operation melts down under the weight of complaints or their quarterly sales targets are seriously under-achieved. Do they have as good a handle on the things we love? Do they have a clue about the minor gripes of customers outside their pre-launch polling groups? Do they know about the gut reaction to a colour, a touch, a smell, or a careless word that persuaded a likely prospect to buy a technically or aesthetically inferior product from the competition instead? All this and more is there for the taking in the stream of online chatter freely directed their way.

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Driving home last night, listening to podcasts from the BBC, The Guardian and John Willis, I began to wonder about the ‘inevitability’ of Open Source in the Enterprise. I shared the initial idea on Twitter and had some useful responses overnight;

“Thought; Open & Closed Source coexist well in enterprise. BUT once you deploy Open Source tool can you ever get budget back for Closed ver?”

Conversation was clearly constrained by Twitter’s 140 character limit, and several respondents (incorrectly, but understandably) assumed that I was simply suggesting Open Source Software to be cheaper. It may be, but it doesn’t have to be. And that wasn’t the point.

For the avoidance of doubt, let me first expand upon that brief tweet in order to clarify what I meant. Then we can explore the issues in a little more depth and see whether the premise holds water.

Thankfully, we appear to have moved beyond the ridiculous polarisation of recent years that saw Open Source evangelists square off against Microsoft junkies and other proponents of closed source proprietary solutions. Naive notions that ‘free’ software would not cost anything to deploy and maintain have faded from the conversation, enabling growth in for-profit ventures to support deployment of all that ‘free’ software. In essence, we have reached (or are rapidly approaching?) a healthy balance; a point at which Open and Closed Source solutions co-exist within many Enterprises, with each solution selected on its merits rather than for the flavour if its religious dogma.

So far, so good; and it is against this background that my question should be considered.

The essence of my question, actually, isn’t one of Open versus Closed at all. The essence is about budgets and politics, and the ways in which organisations manage them. A traditional on-premise installation of proprietary software is generally held to be a Capital item in the budget. It’s a single – and sizeable – allocation of funds once every 3-7 years that results in ‘ownership’ of an asset. Even if an Open Source deployment actually ends up costing almost the same over the lifetime of the installation, the vast majority of those costs are in terms of people who are either employed or brought in as contractors from outside. Those people are recurring items of expenditure in the budget; smaller amounts, more often.

In choosing to procure a new piece of software, it probably doesn’t ‘matter’ whether it’s Open or Closed. Instead, the decision should (correctly) be made in terms of the ability of the chosen solution to meet a set of business requirements. Sometimes the best solution will be closed source, sometimes it will be open.

But once an enterprise has opted for an Open Source solution, various internal considerations take over;

• the budget holder (probably) gains a number of staff dedicated to supporting and customising the new solution, either on the payroll or as external consultants. The size of the budget holder’s empire grows visibly larger;
• the CFO sees the unpleasant pain of large Capital investments removed from their books, replaced by a more manageable steady trickle of recurring costs each and every year.

At that point, I’d argue, it must effectively be impossible to turn back from an Open Source solution to a future Closed Source replacement. The switching costs, perceived loss of ‘power’ and perceived hit to a bottom line accustomed to the steadiness of recurring costs all combine to dissuade numerous stakeholders from making the switch away from Open Source. Any proprietary competitor would have to be far better than both the incumbent and all the other Open Source alternatives to stand any chance at all, and in a mature software world where most applications are actually pretty comparable that seems unlikely in the extreme.

So, I’d propose, the decision to move to Open Source is actually made on a reasonably level playing field but the decision to move away from Open Source takes place in an environment so stacked against Closed Source that it’s unlikely to happen. If that is true, we will see a gradual movement of various Enterprise applications towards Open Source as purchasers select each application on its merits (inevitably, some proportion of those will be Open Source). However, we’ll see almost no movement the other way, leading to the eventual dominance of Open Source across the Enterprise. QED. Or maybe not?

And, for some reason, my background in Archaeology comes bubbling to the fore, offering the Roman Army’s fossa punica as an analogy; you can get in [to Open Source], but you can’t easily get out.

An email conversation this morning suggests that vendors of Closed Source solutions are aware of the threat, at least subconsciously. Rhys Wilkins, for example, pointed to the relatively low incentive for piecemeal replacement of software from companies such as Microsoft that tend to bundle ‘desirable’ and less desirable products together in packages. Their customers are prepared to continue paying for the desirable products (Exchange, say) and as they have to keep paying for the bundle whether they use all of its pieces or not there is a disincentive to gradually bring in alternative offerings.

Hosted subscription applications (SaaS) such as Salesforce only serve to confuse this picture still further. They’re not Open Source by any means, but in budgetary terms this new generation of subscription software is a recurring rather than Capital item of expenditure. Will we therefore (as Justin Leavesley suggested in an email) effectively see a race between those trying to push Open Source Software into the Enterprise and those trying to evangelise the benefits of entrusting previously internalised processes and applications to proprietary Clouds? And what happens when Open Source meets Open Data and the Cloud, and some of today’s proprietary silos begin to leak out onto the open Web?

But that, I think, is probably the subject of a subsequent post.

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A short post, sparked by two related items that arrived by Twitter and email almost simultaneously.

Via Twitter, TechnologyReview reports that it’s getting easier to visualise massive data sets without the traditional supercomputer.

Via email, the UK’s Joint Information Systems Committee (JISC) announces its contribution of £200,000 to a joint funding call with the United States’ National Science Foundation (NSF) and National Endowment for the Humanities (NEH), and Canada’s Social Sciences and Humanities Research Council (SSHRC). The scope of the call? The challenge of working with Big Data. I’m very keen to see the bids to that particular call… and to see the innovation that answering its challenges will (hopefully!) spark.

Add to that my post last month about Amazon’s Public Data sets, and  the signs are getting ever-stronger that there are real opportunities here.

It’s getting easier to manage massive data sets. Those data sets are increasingly addressable over the Web. There’s growing interest in working across and between data sets, and there are even licenses to ensure that researchers can do what they need to.

Interesting times, indeed.

Deepak pointed to an Amazon page, which briefly reported that;

“Developers and businesses can now run their Amazon EC2 instances in the EU to help achieve lower latency, operate closer to other resources like Amazon S3 in the EU, and meet EU data storage requirements when required. The new European Region for Amazon EC2 contains two Availability Zones enabling you to easily and cost effectively run fault-tolerant applications with the same scalability, reliability and cost efficiency achieved with Amazon EC2 in the US.”

Amazon CTO Werner Vogels and Evangelist Jeff Barr were close behind, using Twitter to share the same news, and pointing to longer blog posts on Werner’s blog and the Amazon Web Services Blog. A nice example of Twitter at work.

As for the news they were reporting; it’s good to see local availability for EC2 resources join the existing European sites for S3 storage.

Werner’s post outlines a three-part rationale for the move, broadly characterised as;

• lower latency (faster) access to the servers for customers in Europe,
• cheaper use of data stored in the European parts of S3,
• compliance with European regulatory requirements regarding storage of personal (and other) data outside Europe.

All are useful, and different customers will certainly emphasise each differently. I wonder which was the most commonly cited? ‘Compliance’ was a major stumbling block to using EC2 with certain data in the past, but I wonder if customers for whom that was an issue have traditionally been that important in the grand scheme of things at Amazon?

So; speed, price, or privacy?

“Trying to get my head round what The Cloud actually IS (other than something that soaks you every time you go outside). Thoughts welcome”

I was amongst those to respond, as I had just posted my first entry on this shiny new blog and felt it was relevant to Peter’s question.

Peter takes a different tack this morning, devoting his editorial to asking the same question, and noting that he will

“discuss our joint findings in the next edition [of Digital Business]“

As well as being (obviously) very interested in the answer, I also hope that Peter is able to take a moment to share his thoughts on the relative merits of both approaches to information gathering. Which gave him the most data? Which was quickest? Which was ‘best’?

The next issue of Digital Business will land on desks on 3 December. I look forward to enlightenment.