OUseful.Info, the blog…

In several recent posts, I’ve been exploring in a rather clumsy and over complicated way how we can use Gephi to look at commenting behaviour around shared photos. In this post, I take a step back to look at a much simpler approach… Just plotting the comment graph…

So for example, take a CSV file along the lines of:

c-jd342,p189
c-cd546,p226
c-gh232,p226
where we use a simple CSV file to denote commenter ID and photo ID, and look at the result as a directed graph.

Here’s the graph with nodes sized by in-degree (large nodes are well commented photos):

And then for nodes sized by out degree (large nodes are people who have commented lots of photos):

Here we colour nodes by the out-degree and size it by in-degree, using colour range boundaries to help us colour the graph:

Using the Autoselect neighbour feature we can look at who commented on a photo:

and then what other photos they commented on:

The ego filter trivially shows us, at depth 1, the photos a person has commented on:

(If the photo nodes were sized according to the number of incoming comments from the original graph, we’d be able to see which popularly commented on photos an individual had commented on)

At ego filter depth 2, we can see who else has commented on the same photos:

Running statistics over the depth 2 ego filter graph and plotting the results would allow us to see which individuals have commented on a large number of the same photos as the ego filtered individual.

This is just a short post picking up on a point made in the post Gephi Bits 2: A Further Look at Comments on Social Objects in a Closed Community describing augmented user IDs.

It’s also confusing and I don’t think that useful – hence the strike through:
You will remember the setting is a dataset describing a set of photos uploaded to a website by users with a particular ID. Users can also comment and favourite each others’ photos. To try to separate out the different roles an individual may take (commenter, favouriter, or photo uploader), we might define a separate category alongside each edge definition to place the user in a particular role. For example, if we prepend a user ID with the tag f-, c- or p-, to dentaote favourtiing role, commenting role or photo owner role, we might end up with edge definitions that looks something like:

Okay – that’s enough for now; this post is more of a brain dump than anything, and one that’s getting overcomplicated and confusing, so apologies if it makes little or no sense. In the next post, I’ll show you how to do something much simpler;-)

Trying to scope out ideas for a talk I’m due to give in Manchester next week on open civic data, I came across quite a few examples of local councils making map based “data” available – on a map. For example, Milton Keynes Council has a nice collection of links to interactive maps :

The maps look very pretty, when they load… I don’t know if it was my connection that was particularly slow when I tried to grab the screenshot, but I never did manage to load any hi-res tiles…

Manchester City Council also offers a range of map based navigation for identifying local schools:

And if we tunnel down:

The point I wanted to make here is that what the councils are doing is more to do with displaying map based information than geocoded data. That is, it’s still hard for me to create my own map based views based on the stuff the councils are publishing.

The valuable goods for me in the role of a developer is flexible access to the raw data so that I can re-present it and make sense of it in a way that I decide.

So for example, in the case of the Manchester schools data, where I might decide to throw caution to the wind and plot all the schools on one map rather than present the information in the form of schools contained in arbitrarily drawn regions, it would be nice to be able to get a raw data feed of schools under the control of the Manchester local authority…

…which I seem to remember is something I can get from the data.gov.uk education datastore.

Looking through my own hacks, I found a description of a Yahoo pipe (that appears to have rotted:-( that will return schools given a local authority code… but what is the code for Manchester?

A quick google turned up a post by Simon Hume entitled Using SPARQL & the data.gov.uk school data which points to a handy service that uses a query of the National Statistics SPARQL endpoint to list council ID codes (I’m not sure if this can be extended to return a Council ID code based on a user-supplied postcode? If you know how to do this, please post a clue in a comment to this post;-)

Simon’s post also contains another rather handy example of a SPARQL query over the education datastore that will “call back all the schools in your local authority”, including the lat/long coordinates, so they can be easily placed onto a map.

This is the data, the useful stuff. The maps the councils have published that are shown above display some useful information, for sure, but it’s not data…

So here’s a thought: suppose that where councils feel they’re adding value by producing maps like the ones shown above (and I think that sort of display can provide a valuable service on a council website), wouldnlt it be great if:

1) the data they used to create the map came from a public datastore, such as one of the datastores on data,gov.uk, or maybe a queryable datastore local to the council; and

2) as a footnote to the page, or more likely on a page linked from it, a description was given of the query used to generate the data rendered on the information page.

Just a thought…

Yesterday, I took an hour out to do a spot of Telling outside a poll station for a local Isle of Wight council election (recounted here: Throughts on Telling….). Today I went along to the count…

The venue was a sports hall; along the back wall were the ballot boxes full sight. Numbered tables were arranged in a U shape, with counters sitting on the inside and observers stood outside the U, and announcements made as to what ballot was to be counted on what table. Boxes were brought to the appropriate table, and the parcel ties securing the lids cut off; ballot papers were then placed on the table and taken up by the counters. The first pass was to just count the ballot papers and arrange them so they were all the same way up. The papers were then taken away from the table, before being returned to it (I’m not sure why?)

The second pass was the actual count. Papers were sorted into piles corresponding to vote cast (only one vote per paper), and bundled in piles of 25 votes secured by a bulldog clip with clips open. When all the votes were counted, the open clipped bundles (corresponding to bundles for a particular candidate) were reallocated to different counters on the same table and counted again. If the tally was correct (25 papers in a bundle) it was reclipped with clips closed.

Bundles were then arranged by candidate in piles of four (i.e. 100 votes per pile) and checked off as bundles for the final count value. (A final unclipped pile in each column represented the remaining votes for that candidate.)

Where there was uncertainty as the validity of a ballot paper, the counter placed it into a wire in-tray. The returning officer adjudicated on the validity of votes in agreement with the agents or party reps. Typical rejected papers were no vote cast/no mark made, or two marks made. When rejection was agreed on, the paper was stamped with a red “rejected” mark and placed into a second wire in-tray. Where uncertain marks were made, e.g. a cross to the left of the ballot paper rather than in the square on the right, a decision was made by the returning officer, again acquiesced to by the agents, as to whether the voter had made a clear preference for one of candidates by the way they had made their mark. If agreed on, the vote was accepted.

A second sort of ballot was also being counted for local town council elections, where voters could make two marks on one ballot paper (which was a different colour to the Island council ballot paper); that is, they could vote for two candidates.

Piled ballot papers obviously doesn’t work in this case, so pieces of A4 paper, in landscape view with the names of the candidates down the left hand side in the same order as they appeared on the ballot paper were used to tally results. Each piece of paper had 25 (or was it 20?) columns and corresponded to one ballot paper. For piles of 25 (or 20?) papers, the votes on the top ballot paper were placed in the first column (a 1 marking a vote cast for the appropriate candidate), the second ballot paper the next column, and so on. Tallying across the rows gave the number of votes cast in that bundle for a particular candidate. Again, an open clips bulldog clip was used to secure a bundle of papers to a tally sheet. These were then recounted and if a match was made, reclipped with closed clips.

A second form (the ‘master sheet’), again with candidates names defining rows arranged down the left hand side, was used to collate totals from the tally sheets. Each column represented the votes cast as recorded on a particular ballot sheet. A desk calculator was then used to total across the rows. As two master sheets were required for the count I saw, the totals from the first sheet were added as an additional column on the second master sheet. Summing across the rows on this second sheet, and adding in the votes carried over from the first sheet, to give the final count. As a witness to the event, I was thinking it’d be handy to have something like, err, an iPad, laid out like the forms, but offering a simple spreadsheet view so that row totals could be calculated automatically, just to offer a quick check. As it was, I did a mental summation to check overall totals were right-ish…

The scope for error in this second style of vote seemed much more likely (several points of failure: creating the tally, counting the tally, transferring tally scores, summing rows, transferring master totals from one sheet to another, final summation). The checking process is further complicated by the fact that there is a mismatch between the number of ballot papers and the number of valid voting marks made; (not all voters voted for two candidates). It struck me that during the initial sort, ballot papers could be put into piles corresponding to 1 or 2 marks made as a way of trying to keep a matching overall vote count check in place (i.e. so it would be easier to check that the votes cast in the final result was more easily auditable from ballot paper bundles).

All in all, a fascinating experience…

In the previous post in this set (Gephi Bits 1: Comments on Social Objects in a Closed Community), I started having a play with comment and favourites data from a series of peer review activities in the OU course Design thinking: creativity for the 21st century.

In particular, I loaded simple pairwise CSV data directly into Gephi, relating comment id and favourite ids to photo ids. The resulting images provided a view over the photos that showed which photos were heavily commented and/or favourited. Towards the end of the post, I suggested it might be interesting to be able to distinguish between the comment and favorite nodes by colouring them somehow. So let’s start by seeing how we might achieve that…

The easiest way I can think of is to preload Gephi with a definition of each node and the assignment of a type label to each node – photo, comment or favourite. We can then partition – and colour – each node based on the type label.

To define the nodes and type labels, we can use a file defined using the GUESS .gdf format. In particular, we define the nodes as follows:

nodedef> name VARCHAR, ltype VARCHAR
p189, photo
p191, photo
…
c1428, comment
c1429, comment
…
f1005, fave
f1006, fave

Load this file into Gephi, and then append the contents of the comment-photo and favourite-photo CSV files to the graph. We can then colour the nodes (sized according to, err, something!) according to partition:

If we filter the network for a particular photo using an ego filter, we can get a colour coded view of the comment and favourite IDs associated with that image:

What we’ve achieved so far is a way of exploring how heavily commented or favourited a photo is, as well as picking up a tip or two about labeling and colouring nodes. But what about if we wanted a person level analysis, where we could visually identify the individuals who had posted the most images, or whose images were most heavily commented upon and favourited?

To start with, let’s capture some information about each of the nodes. In the following example, we have an identifer (for a photo, favourite or comment), followed by a user id (the person who made the comment or favourite, or who uploaded the photo), and a label (photo, comment or fave). (The ltype field also captures a sense of this.)

nodedef> name VARCHAR, username VARCHAR, ltype VARCHAR
p189,jd342,photo
p191,jd342,photo
p192,pn43,photo
..
c1189,pd73,comment
c1190,srs22,comment
..
f46,ww66,fave
f47,ee79,fave

Rather than describe edges based on connecting comment or favourite ID to photo ID, we can easily generate links of the form userID, photoID, where userID is the ID of the user making a comment or favouriting an image. However, it is possible to annotate the edges to describe whether or not the link relates to a comment or favouriting action. So for example:

edgedef> otherUser VARCHAR, photo VARCHAR, etype VARCHAR
pd73,p189,comment
srs22,p226,comment
…
ww66,p176,fave

Alternatively, we might just use the simpler format:
edgedef> otherUser VARCHAR, photo VARCHAR
pd73,p189
srs22,p226
…
ww66,p176

In this simpler case, we can just load in the node definition gdf file, and follow it by adding the actual graph edge data from CSV files, which is what I’ve done for what follows.

Firstly, here’s the partition colour palette:

The null entities relate to nodes that didn’t get an explicit node specification (i.e. the person nodes).

To provide a bit of flexibility over the graph, I loaded the the favourites and comment edges in as directed edges from “Other user” to photo ID, where “Other user” is the user ID of the person making the comment or favourite.

If we size the graph by out-degree, we can look at which users are actively engaged in commenting on photos:

The size of the arrow depicts whether or not they are multiple edges going from one person to a photo, so we can see, for example, where someone has made multiple comments on the same photo.

If we size by in-degree, we can see which photos are popular:

If we run an ego filter over over a photo id, we can see who commented on it.

However, what we would really like to be able to do is look at the connections between people via a photo (for example, to see who has favourited who’s photos). If we add in another edge data file that links from a photo ID to a person ID (the person who uploaded the photo), we can start to explore these relationships.

NB the colour palette changes in what follows…

Having captured user to photo relationships based on commenting, favouriting or uploading behaviour, we can now do things like the following. Here for example is a use of a simple filter to see which of a user’s photo’s are popular:

If we run a simple ego filter, we can see the photos that a user has uploaded or commented on/favourited:

If we increase the depth to 2, we can see who else a particular user is connected to by virtue of a shared interest in the same photographs (I’m not sure what edge size relates to here…?):

Here, user ba49 is outsize because they uploaded a lot of the images that are shown. (The above graph shows linkage between ba49 and other users who either commented on/favourited one of ba49′s images, or who commented/favourited photo that ba49 also commented on/favourited.)

Doh – it appears I’ve crashed Gephi, so as it’s late, I’m going to stop for now! In the next post, I’ll show how we can further elaborate the nodes using extended user identifiers that designate the role a person is acting in (eg as a commenter, favouriter or photo uploader) to see what sorts of view this lets us take over the network.

Earlier today, I spent an hour or so Telling outside a poll station on behalf of a friend who’s standing in a local election. Tellers are those party reps (though not strictly so, in my case…) who grab the poll card numbers of folk who’ve voted so that when evening strikes, any folk who promised to vote for you who haven’t turned out can be bundled into the back of a car and driven to the polling station. Or something like that.

The Telling process itself is paper based, scribbling down numbers of voters (or a line to show a vote from an unknown person) as they enter or leave the polling station. (I asked the other Tellers whether the form was to wait until the voter left the polling station, so as not to be seen as attempting to unfairly influence voters on the way into the station. One said he had been originally “trained” to do just that, but the retired Conservative lady tellers seemed to prefer grabbing the number on the way in…)

So I stood there for an hour, writing down numbers on a piece of paper… (I also annotated some of the marks with a simple clock face showing the approximate o’clock of when the vote was cast, just because…; (the Telling sheet instructions advised starting collections from each new hour on a fresh sheet, to give an idea of hourly turnout)).

Just before I went out, I spent all of 2 mins creating a Google form that would capture the voter number information (plus optional info – I’ve no idea what that might be? Maybe definite knowledge of how the voter claimed to be voting or have voted?):

Grabbing the shortcode link for the form meant it was on my phone and available for recording numbers in electronic form… (It also struck me that it should be quite easy to let folk submit numbers to somewhere via a text message; so for anyone with unlimited free texts, there’d be no reason not to send in voter numbers to either a local or national collection point, maybe with sender number reconciled back to a particular ward or polling station?) I didn’t use this “app” in the end, (are there data collection/protection issues with regard to shoving this info into a Google Spreadsheet, for example?), but there was no technical reason why it couldn’t have been used to collect this data in real time.

So what else came to mind? Gaining access to the electoral roll allows (I think) the domicile of voters to be identified by poll number, at least to the street level; which means that it would be possible to generate a crude heat map, in real time, of where votes had been cast from.

Another part of the jigsaw: when canvassing, I believe the theory is that candidates capture the details of voters who might vote their way, so that they can be knocked up (or whatever the phrase is!) if it turns out that by a particular time they don’t appear to have voted (as recorded by the Tellers). Again, this seems to be a paper based activity, although it would be trivial to capture this information, along with exact address or lat/long details, with an app, and feed that info back to a local or national data collection point.

When I mentioned in chatting to the other Tellers that it would be trivial to put tells onto a rough map, the response was: “but why?” My first thought was: well why not, it’s not hard….?! Then followed by the thought: why not “demap” markers? If you have built up a map of possible friendly votes in pre-poll canvassing through a 2 minute to create app, every time one of your voters turns out you could remove their marker from the map (or change the shade of their marker). That way you’d have an at a glance view of where you needed to go encouraging voters out.

So… would the be a Good Thing to do or not? Or would it be a bit creepy? Is capturing this sort of data in this sort of way legal? Does it infringe on areas governed by the Data Protection Act, or electoral regulations?

PS Hmmm… what would be really handy would be a DIFF spredsheet formula that would generate a list of items that appear in one column that donlt appear in another column. If you know of one, or an easy way of achieving this in a spreadsheet, please post a comment below letting me know how ;-)

Over the last few weeks and months, I’ve had several opportunities to try and peddle my own peculiar take on the sorts of skills that I think someone – possibly “the librarians” – needs to be developing if we’re going to have the go-to people we need to help us keep tabs on world of digital information, and put some of those digital bits to work effectively; for example: Digital Librarian presentation, Imaginings Around Emerging Infoskills for Digital Librarians, CILIP Talk – Skills of the Future, Time For a Library Shist – Arcadia Brown Bag Lunch presentation, and so on…

Quite by chance, I came across a couple of posts yesterday that illustrate some of the skills that actual librarians need…

First up was Ed Chamberlain’s “Resignation Letter to CILIP” describing his reasons for leaving that professional body. Part of Ed ‘s role is to keep the OPAC ticking over for the Cambridge University Libraries, so his take comes from a technical stance, but many of the issues he raises reach wider than that. For example, on the relevance of the training CILIP provides, Ed writes: “[I]n the near future, a modern information service could involve data curation and storage, online communication services and data manipulation, database design and potentially web application construction on behalf of users. Yet CILIP does not appear to be skilling a workforce to do this.

He also touches on the role of CILIP as an advocate for Libraries, as threats come in from the defection of users to competing online technologies, as well as stresses brought on by financial woes within institutions.

The second post that caught my eye came from @katy_bird, a librarian working for the Guardian newspaper – “Week in the life: Wednesday 25 May 2010“. So what did Katy do over the last week? Daily tasks included corrections and updating the Afghanistan war casualty count, before a handful of Datastore tasks uploading content to the Guardian’s public data spreadsheets. There were also queries from journalists about statistics of one sort or another. I appreciate that these may not be the everyday tasks of an HE Librarian (read the post yourself to see the full range of duties performed), but I wonder what Katy’s week would have looked like 5 years ago compared today? Are there trends there that might indicate a natural path for the evolution of the academic librarian?

Which reminds me… Here’s the OU VC’s take on where the future may lay for librarians, taken from his keynote at the JISC2010 conference:

Sensemaking, that’s what…

PS here’s another related post I came across yesterday: Librarians Have Skills That Pay The Bills. And here’s one that got me thinking about the role public librarians might have to play in opening up and liberating content at a local/civic level: Data scraping using Google Docs spreadsheets (after all, public libraries are one of the places you go to pick up flyers and see posters about what’s going on locally, right?!) Related to this: Programming, Not Coding: Infoskills for Journalists (and Librarians..?!;-) I’m thinking I really need to take a long, long walk to mull over the blurring relationship (as I see it) between the roles of journalists, librarians and academics/educators…

PPS @daveyp pointed out to me there is actually a tradition of librarians blogging about what they get up to, which several others then reiterated;-)

Find out more here: Library: Day in the Life (I will be…).

PS for what it’s worth, I’d be interested in running “Future Librarian” sessions at other libraries, especially in HE sector, to see how local experiences vary… email me… ;-)

PPS Related, picked up via a tweet from @boycetrus: Libraries and Journalism: Same, Same but Different?; and just now, via @niamhpage: Librarians as Teachers

…and another, this time from @librgoddess/@theUL (“Is your library a library or a book storage facility … ?”): Where do we go from here?

The last few weeks have just seemed crazy to me – lots of events, new folk to meet, some incredibly stimulating conversations and a seemingly incessant flow of announcements that might actually mean something coming in over the interwebs. Picking up email as I was leaving the OU last night, I spotted an invite to today’s launch of a reversioned BBC iPLayer. I couldn’t make it down/up to London today, but the press release, #iplayer twitter coverage, live blogs and BBC blogs [UPDATE: another here], as well as the thing itself – http://beta.bbc.co.uk/iplayer/ (or in mobile form, http://beta.bbc.co.uk/mobile/iplayer/) kept me more than entertained.

One thing that’s kept coming to mind over this period has been the changing nature of TV viewing. Considering my own TV viewing through the main “living room screen”, it’s now split pretty much into thirds:

• one third live TV from the four analogue terrestrial channels we can receive (BBC1, BBC2, ITV1, Channel4);
• one third DVD box sets;
• one third iPLayer on Nintendo Wii, (which personally is to say: BBC1, BBC2, BBC3, BBC4 and BBC Parliament). NB my iPlayer on the Wii viewing tends not to be between 8pm and 9.15pm when for whatever reason buffering and dropouts disrupt viewing to such an extent that programmes are pretty much unwatchable. maybe it’s a local bandwidth problem, or maybe it’s a BBC problem…?

[Source: BBC iStats]

(Thinking back a couple of years, the split used to be split 2/5 live TV, 2/5 HDD recordings, 1/5 video; but then the HDD broke and I replaced it with a cheap one with such an unusable interface we never bother with it anymore, except as a DVD player.)

I think it would be safe to say that if 4oD or the ITV Player were available on the Wii, we’d watch ITV and Channel 4 content on it… Same for Channel 5 (maybe?!).

The new iPlayer, whilst not providing a place to watch content from other providers, will apparently start providing a discovery service over content from other channels. As the press release puts it:

Later in the summer, audiences will also be able to find links to programmes from ITV Player, 4oD, Clic, Demand Five and SeeSaw – as a result of partnership deals with public service broadcasters ITV, Channel 4, S4C and Five, and communications infrastructure and media services company Arqiva.

These “metadata partnerships” mean that audiences looking for long-form programmes from other TV services will be directed to their websites: BBC iPlayer will link and drive traffic to them, without any sharing of technology or syndication of content.

But that’s for later? What’s for now…?

First up is a revamp of the iPlayer website:

If you sign in with a BBC ID, you can get a range of personalisation options, including personal recommendations based on your previous viewing habits (I wonder if they use the Google Prediction API?!;-) and the ability to share recommendations with your friends from Facebook and/or Twitter who have also linked their social network account to their BBC ID:

Unlike Recomendations, Favourites are private (though it could be handy to at least get hold of a private feed/one with an obfuscated URL, so that you could transport favourites elsewhere? Hmmm… I wonder if we’re going to start seeing personalised BBC iPlayer iGoogle gadgets, or wordpress widgets?!;-)

I assume that Personal Recommendations are based on Favourites and watched programmes? Linking iPlayer state to a BBC ID means that you can watch the content through any browser and link it back to your account, though I’m not sure how (if) the desktop iPlayer client also picks up BBC log in details? (Hmm, could it do this through a Flash cookie I wonder?)

One problem for me is that a lot of my iPlayer viewing is done through the Wii, so unless that has been updated with personalisation features (I’ll check later today;-), the most useful data for making recommendations to me will be lost. (That said, the whole family watches iPlayer on the Wii, so the recommendations could go all over the place, cf. disrputed Amazon recommendations just after Christmas! (You’d think they’d be able to make the recommendations based on views between different windows of time?!) However, from the figures, it looks as though the WIi channel isn’t widely used…

[Data: BBC iStats]

(Hmmm, which reminds me… looking at the the Wii Shop last night, Nintendo we’re pushing a scheme giving out free Nintendo points if you could persuade someone else to hook their Wii up to the net. So maybe there are a lot of Wiis out there that aren’t networked, although they could be….?)

There look to be further personalisation options available in the Categories area (“My Categories”), although I’m not sure how this works…?

A second future announcement related to a tie-up with Windows Instant Messenger. Again from the press release:

A partnership with Microsoft allows Windows Live Messenger users to log in to their messaging service through BBC iPlayer, enabling them to invite other contacts to watch programmes at the same time and chat live. This is an experimental feature, which will be available in beta later in the Summer; if it proves successful, the BBC plans to extend it to other instant messaging services.

That is, users will be able to watch content on-demand, but synched with their remote friends, so they can chat along to it at the same time…. To me, this shouts out a great opportunity to capture programme synched tweets that can be fed into an evolving status updates caption feed (e.g. other Martin’s Twitter powered subtitles for BBC iPlayer, JISC10 Conference Keynotes with Twitter Subtitles or most recently Google I/O 2010 – Keynote Day 2 Android Demo with Twitter Subtitles).

(As to the deal with Microsoft, I can understand why the BBC feels it needs to partner with different corporates in a fair way, but from local experience in my household, most of the chat that used to be relayed by Instant Messenger now runs via Facebook chat…)

I’m not sure I fully grok what being able to watch content in synch with remotes friends actually means. YouTube piloted a feature like this several years ago (Youtube Streams?), where groups could gather around a video and chat around it, but I think they have since dropped it? (Maybe the timing wasn’t right a couple of years ago?) What this does mean, of course, is that small groups can start to reintroduce concurrent (“locally scheduled”) programming, that we have been moving away from through consumption of personal recordings and on-demand content?

Chatting to OU PR guru Paula Feery last week, it struck me that a lot of TV related PR activity (which we go in for at the OU because of our co-pro arrangement with the BBC) is aimed at getting previews of programmes into the press. But from my own viewing habits, a large part of my viewing (particularly over iPlayer content) is guided by post hoc reviews appearing in the weekend press of programmes broadcast over the previous seven days, as well as “last week’s” Radio Times, and (occasionally) social media comments from people I follow relating to programmes they have recently watched themselves. From a PR point of view, there may be an increasing benefit in considering “after-TX” PR opportunities to exploit the fact that content remains viewable over a 7 or 28 day period (or even longer for series linked content or content that is rebroadcast on other BBC channels).

The social features of iPlayer also means there are improved opportunities for promoting content though social media channels (so for example: maybe @open2 needs lots of Facebook and Twitter friends, a BBC ID, and someone tasked with recommending all the OU’s BBC output ;-)

PS I still can’t find an easy way of grabbing a list of OU/BBC programmes for a 7 day watch again service (which I have to admit, I haven’t maintained for over a year, so I’d be very surprised if it still works?! Same with the mobile version). I don’t think it’s possible to get a feed of recommendations or favorites out of iPlayer, but if it was possible, it would be handy to have one with a list of content in that list that was currently available on iPlayer ;-)

PPS So much for personalisation…. BBC ID registration requires an age; I set mine to well over 16 but still get this?

I can appreciate why, but if this is supposed to be a personalised service….?

PPPS Reminds me, I still haven’t looked at the Google TV announcement yet… Here’s Liam’s take on it: Google TV: Your TV may never be the same again

PPPPS for more of my disconnected thoughts about status update captions, see eg:

- Twitter Powered Subtitles for BBC iPlayer Content c/o the MASHe Blog;

- Searching the Backchannel – Martin Bean, OU VC, Twitter Captioned at JISC10 (since implemented by @mhawksey).

For Martin’s development timeline, see MASHe tt-tweets category.

PPPPPS A comprehensive run down of the new features, plus commentary on the design philosophy, can be found in this blog post from Anthony Rose: Introducing the all new BBC iPlayer (This time it’s personal)

Slides from a presentation earlier today:

Doug blogged it here: CALRG Conf: Learning in Public

This made me think…:

[I]f your every utterance, regardless of the privacy of the setting, is potentially subject to external scrutiny, you are living if not in a surveillance state, then in a state of surveillance.

“Whose interests are being served by this squalid tale of entrapment?” Andrew Anthony, The Observer, Sunday 23 May 2010