Author Archives: Martin Belam

#ge2010: Digital timeline charts campaigning and media innovation online

It was always obvious that at the end of the election campaign there would be a slew of articles declaring that it had or hadn’t been “the internet election”. I decided back in March to start collecting examples of campaigning and media innovation around the election and putting them into a digital election timeline, so that when we got to polling day I’d have a timeline of events.

I chose to use Dipity as my tool. The free version allows you to create up to three timelines. Within a topic you give each event a title and a timestamp. Optionally you can add a description, image and link URL to each event. Dipity then builds a timeline using Flash, and the events can also be viewed as a plain chronological list, or in a ‘flip-book’ format. If you link to a video on YouTube, Dipity automatically embeds the video in the timeline.

To get the data to go into the timeline I relied quite heavily on Twitter. I made sure that I subscribed to the Twitter streams of the major parties, and to election Twitter streams from broadcasters like Channel 4 and the BBC.

During the day, every time I saw a link on Twitter that I thought might lead to an interesting bit of the digital campaign I marked it as a favourite. At night, I would then spend 20 minutes looking back through the day’s favourites, taking screengrabs, and entering the details into Dipity. I also had help from various people within news organisation who began sending me messages about content and services they had launched.

The timeline has around 150 events in it now, and I’ve been continuing to update it in the aftermath of the indecisive result.

A few things stood out. From the political parties, the Conservatives #cashgordon Twitter fiasco was amusing, but worrying. It seemed that the people who look likely to be commissioning the nation’s digital infrastructure in the next couple of years couldn’t commission a website which got basic security right. Worse, instead of holding their hands up to a “Web security 101” SNAFU, they tried to shift the blame to “left-wing” hackers, an example of tribal politics at it’s worst.



For their part, the Labour decision to turn their homepage over to a Twitterstream during the Leader’s Debates was a brave, but I believe, misguided one. First time visitors would have been perplexed by it, just at a moment when the nation was focused on politics and they had a chance to introduce floating voters to key elements of the Labour manifesto.



The Liberal Democrats Labservative campaign was a favourite of mine for sheer attention to detail. Fictional leader Gorvid Camerown even had a profile on Last.fm, where he enjoyed nothing but the status quo. The campaign was clever, but whether it increased the Liberal Democrat vote is impossible to judge.



It seemed to me that as the campaign progressed, the cycle of social media reaction got faster and faster. There were plenty of spoof political posters early in the campaign, but on the eve of the poll it seemed like it took less than ten minutes for the first spoofs of The Sun’s Cameron-as-Obama front page to appear. Likewise, within minutes of the Landless Peasant party candidate appearing behind Gordon Brown giving a clenched fist salute in Kirkcaldy, a Facebook fan page for Deek Jackson had been set up and attracted over 500 joiners. It has now reached 4,000.

It has been a really interesting exercise. I definitely feel that compiling the digital election timeline personally kept me much more engaged in the campaign.

Would I do the timeline differently in the future? In retrospect I may have been better off putting the events into a mini-blog service like Tumblr, and powering the Dipity version from that. As it is, the data is locked into Dipity, and can’t be indexed by search or exported. I have though uploaded around 100 of the screengrabs and images I used to a Flickr set so that people can re-use them.

A history of linked data at the BBC

Martin Belam, information architect for the Guardian and CurryBet blogger, reports from today’s Linked Data meet-up in London, for Journalism.co.uk.

You can read the first report, ‘How media sites can use linked data’ at this link.

There are many challenges when using linked data to cover news and sport, Silver Oliver, information architect in the BBC’s journalism department, told delegates at today’s Linked Data meet-up session at ULU, part of a wider dev8d event for developers.

Initally newspapers saw the web as just another linear distribution channel, said Silver. That meant we ended up with lots and lots of individually published news stories online, that needed information architects to gather them up into useful piles.

He believes we’ve hit the boundaries of that approach, and something like the data-driven approach of the BBC’s Wildlife Finder is the future for news and sport.

But the challenge is to find models for sport, journalism and news

A linked data ecosystem is built out of a content repository, a structure for that content, and then the user experience that is laid over that content structure.

But how do you populate these datasets in departments and newsrooms that barely have the resource to manage small taxonomies or collections of external links, let alone populate a huge ‘ontology of news’, asked Silver.

Silver says the BBC has started with sport, because it is simpler. The events and the actors taking part in those events are known in advance. For example, even this far ahead you know the fixture list, venues, teams and probably the majority of the players who are going to take part in the 2010 World Cup.

News is much more complicated, because of the inevitable time lag in a breaking news event taking place, and there being canonical identifiers for it. Basic building blocks do exist, like Geonames or DBpedia, but there is no definitive database of ‘news events’.

Silver thinks that if all news organisations were using common IDs for a ‘story’, this would allow the BBC to link out more effectively and efficiently to external coverage of the same story.

Silver also presented at the recent news metadata summit, and has blogged about the talk he gave that day, which specifically addressed how the news industry might deal with some of these issues:

How media sites can make use of linked data

Martin Belam, information architect for the Guardian and CurryBet blogger, reports from today’s Linked Data meet-up in London, for Journalism.co.uk.

The morning Linked Data meet-up session at ULU was part of a wider dev8d event for developers, described as ‘four days of 100 per cent pure software developer heaven’. That made it a little bit intimidating for the less technical in the audience – the notices on the rooms to show which workshops were going on were labelled with 3D barcodes, there were talks about programming ‘nanoprojectors’, and a frightening number of abbreviations like RDF, API, SPARQL, FOAF and OWL.

What is linked data?

‘Linked data’ is all about moving from a web of interconnected documents, to a web of interconnected ‘facts’. Think of it like being able to link to and access the relevant individual cells across a range of spreadsheets, rather than just having a list of spreadsheets. It looks a good candidate for being a step-change in the way that people access information over the internet.

What are the implications for journalism and media companies?

For a start it is important to realise that linked data can be consumed as well as published. Tom Heath from Talis gave the example of trying to find out about ‘pebbledash’ when buying a house.

At the moment, to learn about this takes a time-consuming exploration of the web as it stands, probably pogo-sticking between Google search results and individual web pages that may or may not contain useful information about pebbledash. [Image below: secretlondon123 on Flickr]

In a linked data web, finding facts about the ‘concept’ of pebbledash would be much easier. Now, replace ‘pebbledash’ as the example with the name of a company or a person, and you can see how there is potential for journalists in their research processes. A live example of this at work is the sig.ma search engine. Type your name in and be amazed / horrified about how much information computers are already able to aggregate about you from the structured data you are already scattering around the web.

Tom Heath elaborates on this in a paper he wrote in 2008: ‘How Will We Interact with the Web of Data?‘. However, as exciting as some people think linked data is, he struggled to name a ‘whizz-bang’ application that has yet been built.

Linked data at the BBC

The BBC have been the biggest media company so far involved in using and publishing linked data in the UK. Tom Scott talked about their Wildlife Finder, which uses data to build a website that brings together natural history clips, the BBC’s news archive, and the concepts that make up our perception of the natural world.

Simply aggregating the data is not enough, and the BBC hand-builds ‘collections’ of curated items. Scott said ‘curation is the process by which aggregate data is imbued with personalised trust’, citing a collection of David Attenborough’s favourite clips as an example.

Tom Scott argued that it didn’t make sense for the BBC to spend money replicating data sources that are already available on the web, and so Wildlife Finder builds pages using existing sources like Wikipedia, WWF, ZSL and the University of Michigan Museum of Zoology. A question from the floor asked him about the issues of trust around the BBC using Wikipedia content. He said that a review of the content before the project went live showed that it was, on the whole, ‘pretty good’.

As long as the BBC was clear on the page where the data was coming from, he didn’t see there being an editorial issue.

Other presentations during the day are due to be given by John Sheridan and Jeni Tennison from data.gov.uk, Georgi Kobilarov of Uberblic Labs and Silver Oliver from the BBC. The afternoon is devoted to a more practical series of workshops allowing developers to get to grips with some of the technologies that underpin the web of data.