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Way back in 1979, before YouTube’s three founders could either walk or talk, The Buggles claimed that “Video Killed the Radio Star.” Queen countered in 1984 with Radio Ga Ga, in which Freddie Mercury sang (of radio);

We watch the shows, we watch the stars
On videos for hours and hours
We hardly need to use our ears
How music changes through the years.

Let’s hope you never leave old friend
Like all good things on you we depend
So stick around cause we might miss you
When we grow tired of all this visual
You had your time you had the power
You’ve yet to have your finest hour

As many of you know, I’ve been running a poll over the past week, to understand whether my future podcasts should remain audio-only (my not-very-well-disguised preference), or start to include more video. And, at least for the type of content I create, it would appear that the lyrics by Queen’s Roger Taylor are spot on; audio wins.

There’s some more detail to tease out of the results, after the break…

Seventeen individuals completed the survey over a period of seven days. Asked “Which type of podcast would you like me to produce?” (the only mandatory question), 15 selected ‘Audio only,’ 2 selected ‘Both audio and video,’ and none selected ‘Video only.’ Amongst the (optional) comments, there was a recognition that video would have value if there were more to watch than just two talking heads. I don’t see any point peppering a video with screenshots of a web page that the viewer could just visit for themselves, but there is certainly value in showing people how to complete some task or process. Luckily ( ) my podcasts don’t involve that degree of minutiae…

“A video version would be a little more trouble for us, a lot more for you, and for what? To watch badly-lit panelists stare into their webcams? Stick with what you have. It’s great.”

The remaining questions were optional, but most respondents chose to answer them.

Asked ‘How often do you listen to my podcasts,” 50% reported listening to “all” or “most of them,” 30% had heard “one or two,” and 18% had not listened to any.

Most of my podcasts tend to run for between 40 minutes and an hour. Asked about their preferences for length, 70% of respondents stated a preference for the current length. There were, of course, a number of caveats in the comments. These broadly suggested that a podcast should be as long as it needed to be, rather than padding a conversation in order to reach some arbitrary length. That’s pretty much what I do just now, so that’s good.

When I started podcasting, I used to slave over the audio for hours. I edited out every ‘um,’ every ‘ah,’ every plosive, and every pause for reflection. Now I don’t bother. Instead, I add a short intro and edit out the worst of the howlers (coughing fits, retracted statements that might make lawyers twitch, etc). From my perspective, that gives the best balance between editing time and listening quality, and the survey’s respondents agreed. One respondent said I shouldn’t bother doing anything at all to the audio file, 12 said “do what you do just now,” 2 asked that I “do more to edit the ums and ahs,” and one opted for “edit to the max – give me the sound bites, and voice overs and summaries.” I think I’ll quietly ignore that last one, and keep going as I am.

So… keep doing audio, keep them about the current length, and stick with the current level of editing. Isn’t it great when a survey tells you what you want to hear?

That said, there may be scope for doing some talking heads-type video at events. That sort of video is about capturing atmosphere as well as getting the interview… and would probably be much shorter. 5-10 minutes, maybe. We’ll see…

Disclaimer: lots of wordy verbiage, crammed full of caveats, hedges, and warnings about sample size, survey methodology, and bias.

And as for the songs? Well, judge for yourself. The Buggles video off YouTube doesn’t appear to want to embed (who knew that WordPress had a taste filter?), but here’s Queen…

Related articles

• A conversation with Richard Wallis, an experiment, and a survey (cloudofdata.com)

Image via CrunchBase

The more I learn about BuzzData, the less sure I am that it belongs in the Data Market club. That doesn’t mean that the site isn’t useful, or valuable, or relevant to lots of different people. Far from it. But it seems clear that BuzzData’s current focus is upon doing something very different to the other companies I’ve spoken to during this series.

Described by Nick Edouard, BuzzData’s EVP Business Development & Marketing, as a “GitHub for data,” BuzzData concerns itself with providing a place in which groups can collaborate around a set of data. This data might be a public resource that they’ve found for free on BuzzData itself, or it might be a corporate database or spreadsheet that has been uploaded to a private area of BuzzData to be worked on collaboratively. More like Huddle or Box than Infochimps or Factual, BuzzData seems primarily interested in delivering a data-centric perspective on the increasingly important task of collaboration. Whether the company can make that particular niche big enough for themselves and (if successful) the inevitable flurry of copycat competitors remains to be seen, but they’re off to a good start.

Following up on a blog post that I wrote at the start of 2012, this is the fifth in an ongoing series of podcasts with key stakeholders in the emerging category of Data Markets.

Like most of my podcasts, this one is audio-only. I am conducting a short survey this week (only one question is mandatory) to gauge interest in alternative forms of podcast, and would be grateful if you could take a moment to record your view. I shall summarise the findings on Friday.

Related articles

• Data Market Chat: Tyler Bell discusses Factual (cloudofdata.com)
• Data Market Chat: Chris Hathaway discusses AggData (cloudofdata.com)
• Data Market Chat: Hjálmar Gíslason discusses DataMarket.com (cloudofdata.com)
• Data Market Chat: Flip Kromer discusses Infochimps (cloudofdata.com)

I originally recorded a podcast with Infochimps’ Flip Kromer way back in December 2009, when most of today’s data markets were just starting out. We spoke again last week, as part of my current series of Data Market Chats, and it’s interesting to begin exploring some of the ways in which Infochimps and its peers have evolved.

Describing Infochimps variously as a “SourceForge for data” or an “Amazon for data,” Flip argues that the site’s real value lies in bringing data from different sources together in one place. This, he suggests, is part of allowing customers to “bridge the gap from data to insight.”

Despite his impatience with some of the complexities of the Semantic Web ideal, Flip willingly embraces the lightweight semantics emanating from projects such as the search engine-backed schema.org. He also recognises the value of good metadata in making data easy to use, and in introducing a degree of comparability between data sets from different sources.

Towards the end of the conversation, Flip provides his perspective on some of the other players in this space. Microsoft’s Azure Data Market, for example, is Saks Fifth Avenue to Infochimps’ Amazon; one has ‘the best’ socks, whilst the other has all the socks.

Following up on a blog post that I wrote at the start of 2012, this is the fourth in a series of podcasts with key stakeholders in the emerging category of Data Markets.

Like most of my podcasts, this one is audio-only. I am conducting a short survey this week (only one question is mandatory) to gauge interest in alternative forms of podcast, and would be grateful if you could take a moment to record your view. I shall summarise the findings on Friday.

Related articles

• Data Market Chat: Tyler Bell discusses Factual (cloudofdata.com)
• Data Market Chat: Chris Hathaway discusses AggData (cloudofdata.com)
• Data Market Chat: Hjálmar Gíslason discusses DataMarket.com (cloudofdata.com)
• Data-as-a-Service startup Infochimps swaps out CEO (gigaom.com)
• Infochimps Acquires Y Combinator Startup Data Marketplace, Expanding Brand Holdings and Online Presence (prweb.com)
• What does a single day of Flickr uploads look like as real photos? (infochimps.com)

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Openness is undeniably cool right now, at least if you move in the slightly odd circles that I do. Openly available scientific papers are disrupting the world of scholarly publishing (which may not be all good, but that’s a post for another day). Openly available university courses are finally beginning to work out how to offer meaningful accreditation to students. Openly accessible data from government agencies around the world bulks out almost every data marketplace, and anchors many an analysis. Openly available code for cloud infrastructure or networking is challenging the hold of the tech world’s giants. Everywhere you look, ‘incumbents’ are apparently being ‘challenged’ and ‘disrupted’ by the power of open.

The truth, of course, is a little more complex and a lot more nuanced, as business models shift and evolve just like they always have. In sustainable systems, some people still need to be rewarded (often through being paid) for their effort. And in sustainable systems, paying someone can often be a pretty straightforward means of ensuring that you have a throat to choke if something breaks; big companies adopting open source often seek a proper financial relationship with someone who installs and maintains the ‘free’ software or hardware they’re depending upon.

One area of openness that I’ve been involved with for about ten years is that of open licensing for both creative works and data. And it’s come a very long way.

Here in Europe, for example, the (badly flawed) 2003 Public Sector Information Directive is under review, and there’s every likelihood that the replacement will make a number of sensible moves toward greater openness, transparency, and reusability for publicly funded data. As the EPSI Platform site notes today, Andrés Nin proposes going a step further than the European Commission is currently contemplating, by instituting a common open license across Europe;

“The creation of a single public information re-use space in Europe requires much more, it requires a common European OpenData license applicable to all data generated by European public administrations.”

I would certainly welcome a model license that European member states might be enabled to use. I’d also welcome — and support — vigorous efforts to dissuade individual member states or ministries from their usual practice of tweaking and otherwise modifying perfectly good documents in order to demonstrate how ‘special’ or ‘different’ their circumstances apparently are. When will they all realise that they are neither as special nor as different as they like to think?

But — and it’s a big but — it seems unwise, premature, and unhelpful to even begin to suggest that such a license might be mandated across Europe. It isn’t required, and attempts to develop a single document that everyone could accept would be an unhelpful distraction that would result in something so bureaucratic, so ringed in opt-outs and prevarications, as to be utterly worthless. It would also, in all likelihood, be one of those exercises in which the process very quickly subsumed the point. A prime candidate for, in the words of an old boss, being too busy to be effective.

Related articles

• Branding academic publishers ‘enemies of science’ is offensive and wrong (guardian.co.uk)
• Open Data: Europe Starts to Get It (opendotdotdot.blogspot.com)
• Open Data in Europe gets a huge boost from new EU rules (thenextweb.com)

Richard Wallis

Our conversation is also an excuse for an experiment. I have been producing audio-only podcasts here and elsewhere for a number of years, but have always tended to avoid producing video. It’s more effort, it requires more bandwidth at both ends of the conversation, and I’ve never really been convinced that it adds very much to a conversation between two people. Anecdotal evidence would also suggest that my current podcasts are consumed in environments where video would not work; washing dishes, walking dogs, and sitting on buses.

However, rather than just continue to presume that my biases are correct, I’ve decided to give video a try. Richard kindly agreed to participate, and the result is available on YouTube and embedded here.

An audio-only version is also available for download if you prefer. The introductory remarks in this version are slightly different to those on the video, as they come straight from the original conversation.

It’s perhaps unfair to draw too many conclusions from this first attempt, but a few things are immediately apparent. The whole process takes an awful lot longer. The files are larger, so processing and uploading times increase 2-3 fold. Uploading a separate audio file also takes a bit of time. Simply dumping the Skype recording into iMovie worked just fine… but I’ve (so far) not managed to find any way to balance the audio levels. Garageband lets me do this with my audio-only podcasts, but iMovie doesn’t seem to, so Richard’s side of the conversation comes across as quite a bit louder than mine.

Having done one, I’m still not convinced that the video adds anything to the conversation. But what do you think? If you’ve listened to any of my podcasts, please take a moment to complete the short survey over at SurveyMonkey. Your responses will help me to decide where to go next.

Many thanks.

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It was all going so well. The first three podcasts in the Data Market Chat series got scheduled painlessly, recorded without technical hiccups, and published on time. Several others were also scheduled, and more were in negotiation. Everything appeared to be proceeding far more smoothly than similar projects have in the past.

Then I got ahead of myself. I got over-confident. I trailed the guest and release date for podcast number four… before it was actually recorded. I should have known better. Suddenly, and oh-so-predictably, the wheels fell off. First, one guest got a migraine. Then another lost power in a series of snow storms. Then a third had his travel plans upended, putting him on a plane when he was meant to be talking to me. And so it continued. These bumps hit every activity, and we’ve all learned to expect them and to work around them. But to go from no problems at all to nothing but problems was unexpected.

So, podcast 4 was not published earlier this week as I said it would be. Some of you, I know, noticed.

But… Flip Kromer of InfoChimps was successfully recorded this evening, and will go online next Tuesday.

And it looks as if the others are falling back into line again.

With any luck, things should now be back to normal. But I’ve learned my lesson. I’m not going to announce a guest and publication date for a podcast until the audio file is safely on my computer… and safely backed up.

Related articles

• Data Market Chat: the podcasts are a-coming… (cloudofdata.com)

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With Iceland’s DataMarket.com, Founder Hjálmar Gíslason is on his fourth startup, and ready to expand overseas. Focused upon becoming “Google for datanumbers,” DataMarket concerns itself with collecting and providing access to quantitative data; numbers from governments, international agencies, and commercial providers around the world.

Alongside the business of collecting data and making it available for download, DataMarket has invested in providing tools with which users can visualize data (typically in the form of a graph) and even compare results from diverse sources. Hjálmar sees these tools as part of a strategy to ensure that it is

“more desirable to use data on DataMarket than at the source.”

Hjálmar also discusses his view that four characteristics of data make it profitably sellable; proprietariness, timeliness, analysis, and curation.

Have a listen to learn more about DataMarket, and to hear Hjálmar’s thoughts on an industry segment that his company has done much to shape. And check back on Tuesday for the next podcast in the series; Ian Davis of Kasabi.

Following up on a blog post that I wrote at the start of 2012, this is the third in a series of podcasts with key stakeholders in the emerging category of Data Markets. Other conversations, all of which will be published here, have been scheduled with AggData, BuzzData, Factual, Infochimps, Kasabi, and Microsoft. I am still adding conversations to the series, and intend to talk with more companies and with analysts and investors with insight to share. 

Related articles

• Nurturing the market for Data Markets (cloudofdata.com)
• Data Market Chat: the podcasts are a-coming… (cloudofdata.com)
• Data Market Chat: Tyler Bell discusses Factual (cloudofdata.com)
• Data Market Chat: Chris Hathaway discusses AggData (cloudofdata.com)

Image by Kevin Krejci via Flickr

The CloudCamp unconference returned to London for the 14th time this evening, regaling a capacity crowd in the Crypt below Clerkenwell’s St James Church with several hours of discussion and debate on the somewhat elusive topic of ‘Big Data’.

Rather rough notes of the proceedings follow, after the break.

LEF‘s Simon Wardley kicked proceedings off as usual, once again managing to pepper an on-topic canter through the topic with a seemingly never-ending stream of Flickr images of cats… and analogies to electricity. You possibly had to be there? His core message, though? There’s nothing new under the sun… and the cycles of change just keep on coming.

Next, Peter Matthews from CA Labs, on “is big data mutually compatible with the cloud?” Erm, yes. Data volumes with big data are so large that it’s difficult to move it around… which creates opportunities for lock-in that vendors may wish to seize. And then he was out of time.

Next, Fujitsu’s Mark Wilson on ‘Structuring Big Data.’ He’s actually talking about Linked Data, a topic I’ve dug into before here and over on semanticweb.com – Linked Data could be/ might be the effective realisation of the decade-old Semantic Web dream. Big Data means masses of unstructured or semi-structured content, presenting a management headache of previously unanticipated proportions. Linked Data, he argues, creates the mechanism to link all of this data together from across disparate sources. Yes, but it’s easier to say than to do… And in 5 minutes he really couldn’t explain enough to persuade the audience. Linked Data should be “the optimal reference source,” he said. It should be “a broker for all data sources,” and we should “think about integration, not duplication.” Yeeeeees… But.

Next, Canonical’s Nick Barcet, talking around scalability, Ubuntu, package management, configuration management, etc. Not wholly sure what the point was, I’m afraid.

Next, Chris Swan from UBS – big data and security. “If you’ve got security controls that aren’t properly monitored, then they don’t matter.”

Next, Tom Leyden of Amplidata – Big “Unstructured” Data in the Cloud. Data storage to increase 30x over the next decade, but staff will only increase 50% over the same period. Challenge in the 90s, as existing storage and analysis technologies struggled to cope with new data volumes. Seeing similar problems today with data streaming from sensor web, etc. Traditional file systems cannot cope. Object Storage the way forward ?

Next, Alex Farquhar – “Cloud v Big Data.” Not really versus… but intersection of the two. Too much discussion of his company, Forward. Just talking about how his company uses cloud to provision IT resources. Might work as a conference presentation or case study – not sure it fits as a 5 minute lightning chat. Around 60TB of data at Forward. Diverse and vital. Using Hadoop cluster – 24 nodes on-premise. Rationale (proximity to the cluster) seemed odd. That can be true, but not clear that it really needs to be the case here?

Next, Alaric Snell-Pym, on Scaling Hadoop. Trying to overcome Hadoop’s I/O bottleneck. Explaining basics of Hadoop and Map/Reduce – no one else has. Explains use of HDFS and ‘selective reading’ to manage lots of small tables and overcome the problems of I/O.

Next, Matt Wood from Amazon. Talking about genetics and the human genome. It’s an analogy. Human Genome Project took years and millions of dollars. Development of gene sequencing machines led to a step change – dramatic drop in cost of sequencing DNA. Like the cloud, anyone? But… the machines create an analysis challenge, because they generate so much data. Cloud offers “collection of productivity tools” to help scientists work with this data collaboratively and (relatively) affordably. A perfect example of a lightning presentation, unlike most of those who preceded him.

And finally, an impromptu slot from HP’s Joe Weinman. A quick overview of current thinking behind his latest book. This one could have gone for much longer… Good stuff.

And that’s the lightning talks finished. Now, the panel, and Simon Wardley’s search for “experts” and “volunteers.”

…and unfortunately, your scribe was ‘volunteered’ as an ‘expert’ by Mr Wardley… and here end the notes. It was great to have Amazon’s Werner Vogels sneak in, and lob comments into the panel, though…

Great event, though with the usual mix of people you wish could have talked for longer… and people you wish wouldn’t have spoken.

Related articles

• The brave new world of big data & Hadoop (venturebeat.com)
• Big VCs Invest In Big Data Startup Continuuity (techcrunch.com)

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Last week, open standards body OASIS unveiled yet another shiny new standards effort. The OASIS Topology and Orchestration Specification for Cloud Applications (TOSCA) Technical Committee hopes to make it “easier to deploy cloud applications without vendor lock-in,” and to support moving from one cloud to another. The usual suspects — the likes of IBM, CA, and Cisco — are on board. The usual holdouts — Google and Amazon, of course — are not. So what is TOSCA trying to achieve? How does it fit alongside all the dead, dying, or ponderously deliberating cloud standardisation efforts that have gone before? And without the giants of the cloud, is there really any point bothering?

As I’ve probably mentioned before, involvement in various national and international standardisation efforts played a big part in my early career. I went to the working group meetings in odd (but often beautiful) locations. I participated in the conference calls. I engaged on the mailing lists. I drafted and edited and reviewed the documents. I completely buy into the idea that there is a place for foundational standards, developed through consensus-building and maintained for the long haul by organisations that stand apart from the vested interests and their competing agendas.

I also believe that there’s a time and a place for these standardisation efforts. Do it too soon, and we end up ossifying something that needs to be in a state of flux. When you don’t know what the best way to prepare a meal is, it’s too soon to print the recipe book. We need to try different approaches, and we need to be able to throw away the attempts that didn’t work out. More worryingly, standardisation efforts can be used for political ends. They can be little more than a rod with which to beat the (usually dominant) competition. At best a distraction, or a talking shop for those unwilling or unable to just get on and do something. At worst, one amongst a toolchest of dirty tricks in a broader war for hearts, minds, and — ultimately — wallets.

The cloud market is a fascinating place. There are leaders and there are followers. There is innovation, and there is competition. There is agreement, and there is debate. For all the rhetoric, and all the posturing, we really don’t yet know the right answer to many of the cloud’s questions.

Maybe TOSCA and the Open Data Center Alliance and IEEE and the rest are — still — too early, and should be content to let the market thrash out a few more of these issues before anyone tries to write anything down? And when it is time to write some stuff down, let’s make sure we focus on specific, finite, tangible, atomic tasks rather than “the cloud.” As Dave Roberts commented in regard to TOSCA’s scope;

“That goal is so large, that I think it’s probably unbounded. When problems get unbounded, the best you can ever hope to achieve is to solve a large enough subset of the problem that the solution is still interesting. If you can’t achieve that, people ignore the solution because it fundamentally doesn’t help them. There is always an ‘interesting’ part of the problem space that they have to solve a different way, and that undercuts the use of the partial ‘solution.’”

And as for Tosca? Things didn’t end well for her, did they? Might TOSCA’s fate, too, be sealed?

Related articles

• Tech giants back standard for cloud portability – InfoWorld (infoworld.com)
• Proposed spec aims to nix cloud lock-in (gigaom.com)
• On TOSCA and Cloud Standards. MyPOV (diversity.net.nz)

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Chris Hathaway sees basic location information scattered across the websites of hundreds — or thousands — of coffee shop chains, hotel groups, and fast food joints, but argues that it’s almost impossible to do anything more sophisticated with the data than find your closest Starbucks. His company, AggData, is attempting to fill what he sees as a gap in the market; scraping addresses and other facts off company websites to create simple files of store locations that can then be enriched with coordinate data and sold.

Customers for this data include competitors, market researchers, consultants, and even the companies themselves; as is so often the case, it can be easier to buy data on store locations from a third party than to find the authoritative sources within your own organisation. AggData is strongest in the US today, but also offers a growing body of data for other countries. Although the data files are structurally simple, Chris sees plenty of opportunity to continue collecting and selling data to a growing community of customers.

Unlike Factual, which was the focus of last week’s podcast, AggData is not currently interested in combining data from different sources. Customers download separate files on the locations of Starbucks, Peets and Tim Hortons, and not a single aggregated set of coffee shop locations. The AggData model is also predicated upon using their own scripts to extract data from third party sites; asked if he would accept a file of WalMart store locations supplied by WalMart, Hathaway explained why he would — and does — decline.

Have a listen to learn more about AggData, and to hear Chris’ perspectives on the potential role of semantic technologies in making his job easier. And check back on Thursday for the next podcast in the series; Hjálmar Gíslason of DataMarket.com.

Following up on a blog post that I wrote at the start of 2012, this is the second in a series of podcasts with key stakeholders in the emerging category of Data Markets. Other conversations, all of which will be published here, have been scheduled with BuzzData, DataMarket.com, Factual, Infochimps, Kasabi, and Microsoft. I am still adding conversations to the series, and intend to talk with more companies and with analysts and investors with insight to share. 

Related articles

• Nurturing the market for Data Markets (cloudofdata.com)
• Data Market Chat: the podcasts are a-coming… (cloudofdata.com)
• Data Market Chat: Tyler Bell discusses Factual (cloudofdata.com)