Opening the information floodgates

An unexpectedly quick return to the Royal Society was again caused by the word "information".

This time it was bundled up in the phrase "Opening the information floodgates: the technologies and challenges of a web of linked data", which is enough to get any geek moist with anticipation.

Rising to that challenge was Professor Nigel Shadbolt of the University of Southampton (which is where I learnt all the maths that I have now forgotten) who gave us a view of how the web is evolving to encompass structured data.

Along the way he gave us this illuminating star system for assessing connectivity:

1. Put your data on the web (any format)
2. Make it available as structured data, e.g. csv
3. Use open, standard data formats
4. Use URLs to point to your data (so that people and machines can get to it)
5. Link your data to other people's data

This is the essence of the semantic web where the content has meaning allowing new deeper connections to be exploited. Some examples were given, such as the ASBOrometer iPhone app, but these were the familiar mash-ups of geographical data against one other set of data that have been around for years.

So far so good, but there is a big problem. And that's quality.

The example Professor Shadbolt gave us was the official data on the location of bus stops which has 5% error records in it.

This problem, while admitted, was rather glossed over with the enthusiastic claim that the crowd will fix the problem, as it has with matter-of-fact issues in Wikipedia.

But that is to gloss over the examples that go against this.

For example, if you Google "Slovak Currency" you are still told that "1 Slovak koruna = 0.0280875591 British pounds", almost two years after the Slovaks upgraded to the Euro.

And I've pointed out problems with map data previously.

Data interpretation, or Information Literacy if you prefer, is another big issue that has yet to be addressed too. Sharing data makes lots of assumptions about what it means, as anybody who has tried benchmarking knows.

For examples, to compare data about hospitals you need to know about any specialities that they have (more people die of cancer in hospitals that specialise in cancer simply because they take proportionally more cancer patients) and the catchment areas they serve (proportionally more people die in hospitals that serve unhealthy regions).

These concerns were obvious to the audience and most of the questions that were asked at the end were about quality or interpretation of data.

The semantic web sounds a good idea in principle but there is an awfully long way to go from PowerPoint to implementation.

Information theory meets writing

Somehow the Royal Society's programme of talks fails to inspire me and so my recent visit there was only my second. The last was two years ago to hear a discussion on Telling stories with numbers, telling stories with words.

The carrot this time was Information Theory laced with Writing, which last combined at a Gurteen event early last year.

Professor David MacKay's talk was well structured, content-rich and well delivered, revealing the speaker to be very comfortable with his subject area.

He opened with some basics of Information Theory which more-or-less comes to effective versus efficient. To make information efficient we reduce redundancy, e.g. "Mry hd a litl lmb", but to make it effective we add redundancy (check digits and the like) to improve its readability over poor quality communications.

The talk then went on to describe some of the obvious weaknesses with keyboards where we use our very flexible fingers to press keys that are either on or off.

This led us in to a demonstration of Dasher, which Professor MacKay described as a walk through a library containing every conceivable book.

Dasher guides the writer through text showing, at each stage, the letter (or punctuation mark) that is most likely to follow what has gone before.

Here we can see that "writ" has been selected and the most likely options are "e", "ing" and "ten". In this case the finger has scrolled down to select "ten".

The idea is simple and has its obvious attractions, particularly for those of us used to writing with one finger while standing up on the train or tube.

And it's a free iPhone App so it's easy to try for yourself.

I did so and found it harder than I expected (not that I tried it for that long, to be honest). Part of this is that I am not very comfortable with the alphabet and I found letters whizzing past me before I could find them. A touch of Dyslexia perhaps.

But my biggest problem with Dasher is it does not address the problem that we talked about at the start of the talk, the inherent redundancy in the English language. A (possibly) better input system does nothing to solve the issues of inconsistent spelling and words inflated in length well beyond their phonetic requirement.

The problem it does help to solve is to help people who do not have the flexible fingers that I mentioned earlier and the talk gave several examples of where new technologies have enabled even the very immobile to communicate.

The talk did not quite do what I expected but I did learn a lot and I am grateful for that.

Telling stories with numbers, telling stories with words

As a mathematician by training, and inclination, who is employed to exploit words, a talk entitled "Telling stories with numbers, telling stories with words" was always going to interesting.

I was also interested in the possible Knowledge Management (KM) connections as story telling has been a hot topic there for some years.

But let's start with the geeky stuff first. The map shown here is taken from my iPod touch. When at home and on the wi-fi network I can use the maps application to find out where I am going and then save that map as a photograph so that I can access it later when offline. Simple, but very useful.

The talk was hosted by the Royal Society and was in the form of a conversation between Mark Haddon (author of The Curious Incident of the Dog in the Night Time) and Marcus du Sautoy (ubiquitous maths guy) on the similarities and differences between their two practices.

I am not sure that I agree with all of their observations but it was interesting to hear how they see things.

The main difference between the two was that story telling with words was seen as a open world where gaps are left deliberately for the reader's imagination to fill and where the story never really ends whereas as mathematics has to be precise so that all readers get the same message and the story ends with a firm statement, e.g. a proof.

The point was also well made that the mathematics invented (or discovered, perhaps) by the Ancient Greeks is still used today, and always will be, whereas their stories are mostly forgotten.

From a KM perspective, the aim of literature seemed almost to be the antithesis of KM in that the aim is to have uncertainty but in maths it was interesting to hear Marcus du Sautoy describe how he goes from having his original ideas, to sharing them with a small number of people who can understand what he is on about (the arm waving stage) and then writing them down in an academic paper that any mathematician can understand.

Like all good conversations it was inconclusive but it was well worth listening to for an hour and it gave the 200 or so eavesdroppers a few things to think about.