With local elections looming this is a great 20-30 minute project for any journalist wanting to create an interactive Google map of council ward boundaries.

For this you will need:

• A Google account with Docs
• A Scraperwiki account
• Access to webspace to host an html file

Firstly we want to scrape the council ward geometry data held by MaPit by mysociety.org and spit it out into a CSV file format that is compatible with Google’s mapping tools.

Getting the ID for the council ward

Go to the MaPit homepage and use the postcode search for a point in the town/city you want the ward data for. In the example I’ve searched using a Preston postcode.

Then in the results page find the council you want data for and note down the id number next to it.

Adapting a scraper to scrape that council ward’s geometry

Now login to your Scraperwiki and visit this page for reclosedev’s council ward scraper. Click ‘Copy’ and you’ll be taken to a code editor page.

On Line 10 of the code you should see:

10: PARENT_ID = 2366  # Preston City Council

Change the 2366 value to the MaPit id of your council and change Preston City Council (anything after # is a comment and isn’t important to the code but it is useful to keep track of what you’re scraping).

Once you’d done this hit ‘Save Scraper’  the ‘Back to scraper overview’. This will take you to your own Scraperwiki page where the scraper is saved. It would be useful at this point to click on the pen symbol next to the scraper name and rename it ‘Your Council Ward geometry data’.

Then click RUN (or CTRL+R) to run your scraper, and wait a while for it to complete (usually no more than a couple of minutes).

When it has completed running, click Back to scraper overview (upper right) and on the section titled This scraper’s datastore click the swdata tab and you should see something similar to this:

The first column contains the shape/geometry data of the council ward and the third column contains its name. Does it look right? Then hit download (in the upper right of this image) and choose CSV as the format.

CSV or comma separate values is an open table format readable by Excel, OpenOffice and Google Docs and any text editor.

We’re going to use Google Fusion Tables to convert the data to a map.

Mapping the data

Head over to your Google Docs account (or Drive if you’ve been switched over) and hit Create > Table. When it asks you to import a new table choose and upload the CSV file you downloaded. On the next page you’ll be asked to specify the columns to import, leave this page as default and click Next.

On the next page name your table and attribute the data to the MaPit. Click Finish. We’re nearly there!

Under the Visualize menu item click Map and you’ll probably see a red blob similar to this.

If you want to make it prettier you can style this clicking ‘Configure styles’  and changing the settings for ‘Polygons‘.

When you’re happy with the settings for that click inside one of your council wards. You should get a window like this:

Not all that informative is it? To make it a bit more useful click ‘Configure info window’ then select the ‘Custom’ tab, delete what’s there and enter this code.

<div class='googft-info-window' style='font-family: sans-serif'>
 <h2><a href="http://mapit.mysociety.org/area/{id}.html" target="_blank">{name}</a></h2><br>
 </div>

Which will give you a link to the MapIt within the information box:

The final step is to embed this map in your webpage.

First click ‘Share‘ in the top right corner of the table page (not the Google+ sharebox) and change to either Public or Unlisted. Then hit File > About and note down the Numeric ID.

Go to the FusionTables LayerWizard and enter this id in the first box. For location column select ‘kml‘ then hit ‘Put layer on map‘.

Optional: Click ‘Add a search feature‘ and ‘select based search‘. For ‘Select Label‘ enter Search by ward name and for ‘Column to query‘ select ‘name’. Then add. What this allows you to do is to easily select the ward you want to view.

Zoom in to the Preview map to how you want the map displayed. Then copy and paste the code generated below into an html editor or plain text editor of your choice.

Replace lines 4-6

<style>
 #map-canvas { width:500px; height:400px; }
 </style>

with this

<style type="text/css">
 html { height: 100% }
 body { height: 100%; margin: 0; padding: 0 }
 #map-canvas { height: 100% }
 </style>

Then cut line 43

<div id="map-canvas"></div>

and paste it at the end of the page between </div> and </body> like so…

Save the file with the .html extension and try opening it in your browser. It should look a little like this.

Upload this page to your webspace. Now you can either link to it or embed it in an iframe. This sample code should work for most purposes.

<iframe id="ifrm" src="http://your.map.page/here.html" width="NUMBEROFPIXELS" height="NUMBER OF PIXELS">Your browser does not support iframes.</iframe>

Ta da!

This is really just scratching the surface of what Scraperwiki and Fusion Tables can do but I hope it served as an easy-ish introduction to them both. If this tutorial did not work for you or if you have any questions then leave a comment and I’ll help out as much I can.

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If you thought you couldn’t use the Google Maps API any more as a journalist, this update to the Google Geo Developers Blog should make you reconsider. From Nieman Journalism Lab:

“Certain web apps will be given blanket exemptions from charging. Here’s Google: “Maps API applications developed by non-profit organisations, applications deemed by Google to be in the public interest, and applications based in countries where we do not support Google Checkout transactions or offer Maps API Premier are exempt from these usage limits.” So nonprofit news orgs look to be in the clear, and Google could declare other news org maps apps to be “in the public interest” and free to run. (It also notes that nonprofits could be eligible for a free Maps API Premier license, which comes with extra goodies around advertising and more.)”

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Two experiments by news organisations with Twitter hashtags during today’s UK budget have raised an issue around ‘branding’ and how appropriate it is to social media.

The BBC, it seems, is encouraging users to adopt the #BBCBudget hashtag to flag their tweets as part of the ‘national conversation’. Channel 4′s Faisal Islam, above, feels it’s a waste of 3 characters.

But Channel 4 itself is trying something not too dissimilar: #C4cuts aims to crowdsource details of UK spending cuts. Ed Fraser, online editor for Channel 4 News, is quoted by Journalism.co.uk as saying the channel wants to “harness the power of social media and the wisdom of the crowd”.

But the crowd has already started doing this – Where Are The Cuts? most visibly and effectively, but also in niche areas by Voluntary Sector Cuts, Birmingham Budget Cuts (disclosure: run by my Birmingham MA Online Journalism students), and even The Guardian on library cuts.

I’m curious why Channel 4 didn’t decide to add to it, rather than going it alone with a ‘branded’ hashtag. Meanwhile, it raises a common issue with any crowdsourced project: who claims ownership on what is produced? By branding a hashtag (and there are good technical and editorial reasons* for doing so) you risk people thinking this is a marketing exercise – how do you avoid that distrust?

Opinions welcome…

*UPDATE: Ed Fraser says this “misses the point of hashtags – #c4cuts is to help group and identify cuts rather than brand”

I can see that from C4′s perspective (the editorial reasons mentioned above – it’s also why I use ‘brand’ in inverted commas – I’m not saying that C4 or BBC are trying to brand anything) but I’m talking about users’ perspectives. Some will be suspicious – and if there are other sites doing similar work that isn’t being linked to (for whatever reason) then those suspicions are likely to be increased.

UPDATE 2: CisionBlog have a visualisation of hashtagged tweets which gives a good indication why ‘branded’ hashtags may be useful on a subject so heavily tweeted:

FROM THE COMMENTS – UPDATE 3: The BBC’s Alex Gubbay explains:

“The potential benefits for us around using something like #BBCBudget are two-fold:

• “It easily allows our audience to follow all the tweets from our main accounts and key tweeters on the story (ie: @Peston @BBCStephanie @BBCLauraK etc.) in a hopefully more manageable way.
• “It gives both our audience and our teams a chance to filter the overall narrative where appropriate – based on prompts and the thrust of our on-air coverage.”

There’s a lot of very informed discussion in the comments – worth going through in full.

UPDATE 4 (March 24): The BBC’s Trushar Barot has blogged about the experiment and the reasons behind it:

“The key beneficiary of the hashtag experiment has been the Live Event Page on the BBC News website. One of our producers who was responsible for ensuring the best tweets went onto the page told me that having a dedicated BBC hashtag had made a huge difference editorially. Since the audience was proactively using the hashtag, it was easier for us to republish those tweets on the website, as their writers had made the choice to engage with us. It felt much more comfortable editorially than just taking tweets without someone’s permission – even if Twitter’s terms may allow us to do that.”

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Richard Pope and Jordan Hatch have been building a very useful site tracking recent budget cuts, building up to this week’s spending review.

Where Are The Cuts? uses the code behind the open source Ushahidi platform (covered previously on OJB by Claire Wardle) to present a map of the UK representing where cuts are being felt. Users can submit their own reports of cuts, or add details to others via a comments box.

It’s early days in the project – currently many of the cuts are to national organisations with local-level impacts yet to be dug out.

Closely involved is the public expenditure-tracking site Where Does My Money Go? which has compiled a lot of relevant data.

Meanwhile, in Birmingham a couple of my MA Online Journalism students have set up a hyperlocal blog for the 50,000 public sector workers in the region, primarily to report those budget cuts and how they are affecting people. Andy Watt, who – along with Hedy Korbee – is behind the site, has blogged about the preparation for the site’s launch here. It’s a good example of how journalists can react to a major issue with a niche blog. Andy and Hedy will be working with the local newspapers to combine expertise.

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PriceOfWeed.com is a great example of when you need to turn to crowdsourcing to obtain data for your journalism. As Paul Kedrosky writes, it’s “Not often that you get to combine economics, illicit substances, map mashups and crowd-sourcing in one post like this.” The resulting picture is surprisingly clear.

And news organisations could learn a lot from the way this has been executed. Although the default map view is of the US, the site detects your location and offers you prices nearest to you. It’s searchable and browsable. Sadly, the raw data isn’t available – although it would be relatively straightforward to scrape it.

As the site expands globally it is also adding extra data on the social context – tolerance and  law enforcement. (via)

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Last night OpenHeatMap creator Pete Warden announced that the tool now allowed you to visualise UK data. I’ve been gleefully playing with the heat-mapping tool today and thought I’d share some pointers on visualising data on a map.

This is not a tutorial for OpenHeatMap – Pete’s done a great job of that himself (video below) – but rather an outline of the steps to get some map-ready data in the first place.

[youtube:http://www.youtube.com/watch?v=yFy80kMcaRo]

1. Find a dataset to visualise.

You firstly need data that fits the geographical areas supported by OpenHeatMap (countries, constituencies, local authorities, districts and counties), and which suits geographical visualisation.

My first stop was the data.gov.uk RSS feed to see what recent datasets had been released, but you could also do advanced searches for “unemployment by county” etc. if you are looking for something specific to visualise.

Helpfully, each dataset description includes a field on “Geographical granularity”. This helps you quickly rule out those that only give country-level data (most of them). I ended up discovering the Scottish Neighbourhood Statistics page which allows you to download very specific data. Once on the site’s very helpful data download page I clicked on “Up to 100 indicators” and selected ‘Local authority’ from the first drop-down menu to ensure it matched up to the councils on OpenHeatMap.

I decided to map smoking data, downloaded it, and unzipped it. I then uploaded it to Google Spreadsheets (thankfully, the dataset was not too large).

2. Clarify the data

It’s at this point that the real work begins. Most datasets use a lot of jargon and codes, and you’ll have to spend time decoding those. In this case the zipped file contained a spreadsheet of “meta-data” that explained some of the codes used in the main spreadsheets. That cleared up part of my dataset, but there was a problem. Instead of local authority names, the spreadsheet (as is often the case) used codes.

I started scouring the web for a spreadsheet that might have those codes and what they meant. Eventually I found a page that listed them. Had the information been in a table, or even a list, I could have used the importHTML function in Google Docs (or Excel) to import the list. But it wasn’t, so I had 3 choices:

• Convert the codes manually into authority names
• Keep searching to see if I could find the same list in a better format
• Write a scraper to convert the list on that page into a dataset

I tweeted an appeal for someone to scrape the page (the data was relatively structured – each item was prefixed by a 3-digit number, for example – which should make it easier) and Tom Smith quickly did just that. However, the scraper had for some reason not managed to capture the Scottish codes (possibly because they used the same numbers as the English ones).

Once those codes and associated local authority names were added to my spreadsheet I could convert my own codes to local authority names by using the VLOOKUP formula.

In Google Spreadsheets this means typing something like this into an empty cell to the right of your data: =VLOOKUP(D2,A:B,2)

You need to adapt the formula as follows:

• D2 is the cell with the unknown code in it
• A:B is the range of cells which contain both the code your are looking for and the associated word (A:B is all cells in A and B columns; you might also use something like A2:B340)
• 2 (the “index”) is which of those columns contains the word you want to ‘pull’. 1 would be column A, because it is the first in your range. 2 is B.
• As a whole, then, the code looks at the code in D2, then looks across all the cells in A and B to find the same code. If it finds it, then it will ‘copy across’ whatever is in the B column next to that code.

3. Create a spreadsheet for OpenHeatMap to use

With all my codes converted to local authority names (which OpenHeatMap should recognise), I’ve got all the data I need.

I create a new spreadsheet that only contains the relevant data: local authority, and a value (in this case, the percentage of the population that smokes).

I change the header for the local authorities council to uk_council and the other column to value

OpenHeatMap will use the names in uk_council to decide what areas of a UK map to colour in – and it will use the numbers in value to paint them according to whether they are high, low, or near the middle ground.

Now, I publish the spreadsheet as a webpage by going to Share > Publish as webpage. And copy the URL that is generated.

Then it’s off to openheatmap.com and follow the instructions there.

At this point, I hit a problem – one of the local authorities is not recognised: Eilean Siar. That’s okay – I thought this might happen. On the webpage of local authority codes that one was followed by the parenthesis: (formerly Western Isles). This sort of change of name or alternative name is worth looking out for when gathering data as it’s the sort of thing that does tend to trip up scripts.

In my spreadsheet, I change Eilean Siar to Western Isles, go to Share > Publish as a webpage again and click ‘Republish now‘. Returning to OpenHeatMap, I try again, and it seems to have solved the problem. The map works.

It’s a wonderfully simple way to achieve something that would have required a lot of programming knowhow 6 months ago. The UK is notoriously problematic in the way that it uses a range of different geographical reference points (health authorities, police forces and other data sources use others still), so this is a massive step forward in being able to present regional differences in stories.

If you use OpenHeatMap or mapping data yourself, please let me know how you get on and any other tips you pick up.

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The following is cross-posted from Claire Wardle’s blog:

Late on Monday night, I wrote a short post in anticipation of the crowdmap I’d just set up for BBC London, which I hoped would provide a useful service the following day for the London tubestrike, 7^th September 2010.

It’s now Wednesday morning, and I can write, while still feeling slightly shell-shocked from the experience, that all in all, I’m very pleased with how it went.

I want to use this post to reflect on some of the things that worked, some of the things that didn’t work as well, and some things I will do differently if the next scheduled tube strike goes ahead.

Bottom line was that lots of people saw it: 18,860 unque visitors, and 39,306 page views from 55 countries. 13,808 were from the UK, 3863 from the US, and I can’t get over the fact that we had 2 people form Bermuda, 1 person from Uruguay, and 9 from Kenya, the home of the Ushahidi platform. The power of social media never ceases to amaze me.

We posted 202 reports yesterday. About 50 were sent directly to the map from the audience, either via the web form or the specific SMS channel we set up. The rest of the reports we took from twitter, either tweets in the #tubestrike stream or replies to the @BBCTravelalert account.

I can’t stress enough that getting the reports up wasn’t easy because of the time pressures. Every report, whether it was sent directly or not had to be physically approved. Nothing went straight up onto the map.

Yesterday I was ably assisted by Abigail Sawyer who works for the World Service and who wanted to see how the platform worked and how it might work in a Global context, and for 2 hours during the evening rush hour by Emma Jenkinson, a producer from BBC London who was drafted in as emergency help. We also had help from Steve Phillips, the BBC London transport reporter who was audiobooing, appearing on TV, and updating twitter like a mad thing.

During the two peak times, we were monitoring the SMS console, three twitter streams (#tubestrike, “tube AND strike”, @BBCTravealert), audioboo, emails and the BBC London facebook page.

For each report we needed to add or check:

1) a clear headline,

2) a description, which if it was from twitter we were cutting and pasting,

3) the official timestamp (which frustratingly never stayed connected to the actual time so drop down menus had to be used each time),

4) the geo-location by putting in the location box and waiting for the map to find it (we soon learned that if you just put in Waterloo, it defaulted to Waterloo in Canada so we had to write Waterloo, UK),

5) the category (tube, train, bus etc)

6) the verification status (we only ticked the verification box if the report had been supplied by our own reporters. We realised we couldn’t even verify information from the Transport for London website as commuters were contacting us and saying the TFL information was not up to date)

Only then could we finally approve it and then put it on the map.

Phew. Quite a process.

If you had an event which wasn’t so time sensitive or fast paced, it wouldn’t have been such an issue, but at times we were mopping sweat off our brows, feeling slightly under pressure, especially as we saw so many people tweeting about us from around the world!

That was the process.

In terms of things we learned along the way…

I) had originally chosen Google Maps as the default mapping tool, but half way through the morning rush hour we heard from Harry Wood who encouraged us to use Open Street Map, a free editable map of the whole world, created by volunteers. It is not for profit and apparently started in London. We quickly changed the settings with one click and were immediately amazed at the improved quality of the map. It was much more accurate.

2) Although we needed to use the inbuilt time stamp, we also realised people needed to quickly see on the map itself (rather than having to click through) when information had been sent, so at lunchtime we started each headline with a time stamp we typed in.

3) At lunchtime, we had collected 90 reports, but realised it was quickly going out of date. We therefore deleted all the earlier reports and started afresh, although we did manually input all station closures, which we realised was the key bit of information people were looking for. One major problem however was that by early afternoon word had spread and I saw people tweeting – ‘good idea, shame there isn’t more information on the map’, so I was torn between trying to make the map look impressive, and it actually being useful!

Things I wished we could have done:

1) Publicised it more beforehand. This was a crowdsourcing initiative but we didn’t talk to the crowd early enough to encourage people to take part, and to show then how it might be helpful. For obvious reasons, this was very much an experiment and the BBC was slightly nervous about shouting about something that hadn’t been tried and tested. As a result, I only published my short blog post on Monday night and we started tweeting about it on Tuesday morning but that was it. So the fact that we got the results we did, are pretty amazing (I’d say modestly!)

2) I wish we could have had more time to thank people and to let people know we’d used their information on the map. I did it a few times when I got a chance, and unsurprisingly we saw those people posting more reports.

Things I’d encourage Ushahidi to think about:

It feels churlish to make suggestions to the platform, when I think it’s amazing and I wouldn’t have the skills to make 1/100^th of the site, but as someone who used it under pressure in this situation, here are a couple of suggestions:

1) It would be useful if there was a scrolling news bars at the top, so we could put out top line information, which we know everyone would see by just going to the map. Something like ‘the circle line is suspended’ or ‘the roads are really starting to build with traffic’ was very hard to map. There’s no one spot on the circle line (for those who don’t know, it’s an underground line which runs in a continuous circle!)

2) It would have been great to add more information to the first speech bubble which appeared when you clicked on a dot, e.g. a photo, an audioboo, more detail etc. I don’t think everyone was always clicking through to the next page.

3) A way to visualise the timestamp more clearly from the map would have been great, e.g. the brighter the colour, the more recent the report. It was a shame to have to delete earlier reports.

4) A way to differentiate between good and bad news. Most of the information we were reporting was negative – tube line suspended, traffic jams etc. Sometimes we got tips or advice about how to avoid the problems, and it would have been great if we could have shown those in a different way.

Overall, we created a map, which at many points during the day was more accurate than the Transport for London website, and which was a live and updated version of what was happening out on the streets of London. And most importantly it was built by the people of London.

If more people had known about it and understood how to upload reports it would have been even richer and even more useful and accurate.

While I don’t wish another strike on anyone, I secretly hope there’s another one so we can take crowdmap for another test drive.

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This is one of the best BBC projects I’ve seen in a while: Dimensions maps key events, places and things such as the Pakistan floods, the Gulf oil spill and the Afghanistan-Pakistan border – over your postcode.

It’s a simple idea, but hugely effective.

The prototype comes not from the corporation’s News arm – it was commissioned by History. Commissioning Executive for the Multi-Platform Team Max Gadney writes:

“Our challenge was to make it relevant to audiences.

“This is a common desire. Commissioning editors often want stuff ‘made relevant’ – TV producers might translate this as putting a celebrity in it – one we can relate to (Who Do You Think You Are does this very well). How does digital media make something relevant?”

Currently this is a prototype, so feedback is welcomed. I hope that News will be rubbing their hands at the potential applications and making their own suggestions for improvements on those lines.

For once we may be able to stop comparing things to the size of Wales. Unless, of course, you have a Welsh postcode.

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(Read part 1 here; part 2 here and part 3 here)

The ‘breadth portfolio’ was only worth 20% of the Multimedia Journalism module, and was largely intended to be exploratory, but Alex Gamela used it to produce work that most journalists would be proud of.

Firstly, he worked with maps and forms to cover the Madeira Island mudslides:

“When on the 20th of February a storm hit Madeira Island, causing mudslides and floods, the silence on most news websites, radios and TV stations was deafening. But on Twitter there were accounts from local people about what was going on, and, above all, they had videos. The event was being tagged as #tempmad, so it was easy to follow all the developments, but the information seemed to be too scattered to get a real picture of what was going on in the island, and since there was no one organizing the information available, I decided to create a map on Google[

ii], to place videos, pictures and other relevant information.

“It got 10,000 views in the first hours and reached 30,000 in just two days. One month later, it has the impressive number of 77 thousand visits.”

Not bad, then.

Secondly, Alex experimented with data visualisation to look at newspaper brand values and the online traffic of Portuguese news websites.

“My goal was to understand the relative and proportional position of each one, regarding visits, page views, and how those two values relate to each other. The data I got also has portals, specialized websites, and entertainment magazines so it has a broad range of themes (all charts are available live here – http://is.gd/aZLXs)”

And finally, he produced a beautiful Flash interactive on Moseley Road Baths (which he talks about here).

All of which was produced and submitted within the first six weeks of the Multimedia Journalism module.

The other 80%: multimedia archive journalism

Alex was particularly interested in archive journalism and using multimedia to bring archives to life. As a way of exploring this he produced the Paranoia Timeline, a website exploring “all the events that caused some type of social hysteria throughout the world in the last 20 years.

“Some of the situations presented here were real dangers, others not really. But all caused disturbances in our daily lives … Why does that happen? Why are we caught in these bursts of information, sometimes based on speculative data and other times borne out of the imagination of few and fed by the beliefs of many?”

The site – which is an ongoing project in its earliest stages – combines video, visualisation, a Dipity timeline, mapping and the results of some fascinating data and archive journalism. Alex explains:

“The swine flu data came from Wolfram-Alpha[vi] that generated a rather reliable (after cross checking with other official websites) amount of data, with the number of cases and deaths per country. I had to make an option about which would be highlighted, but discrepancies in the logical amount of cases between countries made me go just for the death numbers. The conclusion that I got from the map is that swine flu was either more serious or reported in the developed countries. Traditionally considered Third World countries do not have many reports, which reflect the lack of structures to deal with the problem or how overhyped it was in the Western world. But France on its own had almost 3 million cases reported against 57 thousand in the United States, which led me to verify closely other sources. It seems Wolfram Alpha had the number wrong, there were only about 5000 reports, which proves that outliers in data are either new stories or just input errors.

“For the credit crunch[vii], I researched the FDIC – Federal Deposit Insurance Corporation[viii] database. They have a considerable amount of statistical data available for download. My idea was to chart the evolution of loans in the United States in the last years, and the main idea was that overall loans slowed down since 2009 but individual credits rose, meaning an increase in personal debt to cope with overall difficulties caused by the crunch.I selected the items that seemed more relevant and went for a simple line chart. My purpose was served.”

“Though the current result falls short of my initial goals,” says Alex, “it is a prototype for a more involving experience, and I consider it to be a work in construction. What I’ll be defending here is a concept with a few examples using interactive tools, but I realize this is just a small sample of what it can really be: an immersive, ongoing project, with more interactive features, providing a journalistic approach to issues highly debated and prone to partisanship, many of them used by religious and political groups to spin their own ideologies to the general audience. The purpose is to create context.”

Alex is currently back in Portugal as he completes the final MA by Production part of his Masters. You might want to hire him, or Caroline, Dan, Ruihua, Chiara, Natalie or Andy.

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(Read part 1 here and part 2 here)

The third student to catch the data journalism bug was Andy Brightwell. Through his earlier reporting on swimming pool facilities in Birmingham, Andy had developed an interest in the issue, and wanted to use data journalism techniques to dig further.

The result was a standalone site – Where Can We Swim? – which documented exactly how he did that digging, and presented the results.

He also blogged about the results for social media firm Podnosh, where he has been working.

Andy’s techniques included creating a screen scraper using Yahoo! Pipes and Google Spreadsheets, visualising and mapping opening times, and, of course, some old-fashioned research (a recurring theme in the MA data journalism work).

What is particularly interesting is how Andy shows readers his working – explaining inconsistencies in the data, how it is gathered, and issues with making comparisons. Spreadsheets are embedded.

Instead of ‘not letting the facts get in the way of a good story’, Andy is refusing to let a good story get in the way of the facts: we are invited to build on top of the sterling work that he has done.

His early visualisations, for example, showed that the West Midlands was the worst region for swimming pool provision. Then in a later one:

“By clicking on the visualisation you should be able to see a correlation between demand and supply. In the top left-hand corner click on facility m2/1000 (this shows the amount swimming surface area per 1000 people). Now click on participation rate – and the map looks remarkably similar, with the same dark areas, while the West Midlands is one of the lightest regions. In other words, where there’s the most availability of swimming – in the South West, South East and in East, there are more people swimming.

“Now let’s look at the West Midlands – one of the worst regions for supply and demand … As you can see, it’s Birmingham that’s the worst offender, in fact it’s significantly worse than other regions within the West Midlands.

“Of course there’s a health warning over all of this. The report does point out that, even in Birmingham, supply is able to meet current demand – which sort of contradicts the evidence that superior supply leads to more demand. However, what we can say with reasonable confidence is that with doubts over the 50 metre pool and the only pool to have been rebuilt so far is Harborne, it seems Birmingham does indeed have a long way to go before it has anything like the supply of pools some other parts of England enjoy.”

Video stories, Flash interactivity and mapping the local music scene

Three other MA Online Journalism students developed skills in different areas to add specialist expertise to their broad online journalism toolkit.

Chiara Bolognini refined her Flash skills to produce a website for the Basel Social Media Apero that combined animation, video, and a Twitter feed.

Ruihua Yao explored video and produced a series of video profiles of members of the Chinese community in Birmingham. Ruihua filmed the subject speaking in their native language, then dubbed the video with their stories in English. What emerges is a picture of very highly educated Chinese citizens unable to use their education to contribute to British society.

Natalie Chillington set herself the challenge of creating a live map of upcoming gigs in Birmingham that would automatically update when new entries were added to the Google Doc (which also fed a listings). Both were for a new site covering the music scene in the city, The Music Quarter.

This was a technically ambitious project which hit a number of obstacles along the way. To Natalie’s credit, she overcame all of these to produce something which looks simple, but is actually very complex. This post explains the stages Natalie went through in exploring automatically updated maps.

In the next and final part of this series (live Monday) I’ll be talking about Alex Gamela‘s work, which includes a Google map that has had over 80,000 views, a moving Flash interactive, and a piece of multimedia journalism combining video, visualisation and more data journalism.

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