Tag Archive for 'wikipedia'

Explaining APML: what it is & why you want it

Published on October 10, 2007 in DataPortability, with 26 Comments. Tags: , , , , , , , , , , , , , , , , , , , , , , , .

Lately there has been a lot of chatter about APML. As a member of the workgroup advocating this standard, I thought I might help answer some of the questions on people’s minds. Primarily – “what is an APML file”, and “why do I want one”. I suggest you read the excellent article by Marjolein Hoekstra on attention profiling that she recently wrote, if you haven’t already done so, as an introduction to attention profiling. This article will focus on explaining what the technical side of an APML file is and what can be done with it. Hopefully by understanding what APML actually is, you’ll understand how it can benefit you as a user.

APML – the specification
APML stands for Attention Profile Markup Language. It’s an attention economy concept, based on the XML technical standard. I am going to assume you don’t know what attention means, nor what XML is, so here is a quick explanation to get you on board.

Attention
There is this concept floating around on the web about the attention economy. It means as a consumer, you consume web services – e-mail, rss readers, social networking sites – and you generate value through your attention. For example, if I am on a Myspace band page for Sneaky Sound System, I am giving attention to that band. Newscorp (the company that owns MySpace) is capturing that implicit data about me (ie, it knows I like Electro/Pop/House music). By giving my attention, Newscorp has collected information about me. Implicit data are things you give away about yourself without saying it, like how people can determine what type of person you are purely off the clothes you wear. It’s like explicit data – information you give up about yourself (like your gender when you signed up to MySpace).

Attention camera

I know what you did last Summer

XML
XML is one of the core standards on the web. The web pages you access, are probably using a form of XML to provide the content to you (xHTML). If you use an RSS reader, it pulls a version of XML to deliver that content to you. I am not going to get into a discussion about XML because there are plenty of other places that can do that. However I just want to make sure you understand, that XML is a very flexible way of structuring data. Think of it like a street directory. It’s useless if you have a map with no street names if you are trying to find a house. But by having a map with the street names, it suddenly becomes a lot more useful because you can make sense of the houses (the content). It’s a way of describing a piece of content.

APML – the specification
So all APML is, is a way of converting your attention into a structured format. The way APML does this, is that it stores your implicit and explicit data – and scores it. Lost? Keep reading.

Continuing with my example about Sneaky Sound System. If MySpace supported APML, they would identify that I like pop music. But just because someone gives attention to something, that doesn’t mean they really like it; the thing about implicit data is that companies are guessing because you haven’t actually said it. So MySpace might say I like pop music but with a score of 0.2 or 20% positive – meaning they’re not too confident. Now lets say directly after that, I go onto the Britney Spears music space. Okay, there’s no doubting now: I definitely do like pop music. So my score against “pop” is now 0.5 (50%). And if I visited the Christina Aguilera page: forget about it – my APML rank just blew to 1.0! (Note that the scoring system is a percentage, with a range from -1.0 to +1.0 or -100% to +100%).

APML ranks things, but the concepts are not just things: it will also rank authors. In the case of Marjolein Hoekstra, who wrote that post I mention in my intro, because I read other things from her it means I have a high regard for her writing. Therefore, my APML file gives her a high score. On the other hand, I have an allergic reaction whenever I read something from Valleywag because they have cooties. So Marjolein’s rank would be 1.0 but Valleywag’s -1.0.

Aside from the ranking of concepts (which is the core of what APML is), there are other things in an APML file that might confuse you when reviewing the spec. “From” means ‘from the place you gave your attention’. So with the Sneaky Sound System concept, it would be ‘from: MySpace’. It’s simply describing the name of the application that added the implicit node. Another thing you may notice in an APML file is that you can create “profiles”. For example, the concepts about me in my “work” profile is not something I want to mix with my “personal” profile. This allows you to segment the ranked concepts in your APML into different groups, allowing applications access to only a particilar profile.

Another thing to take note of is ‘implicit’ and ‘explicit’ which I touched on above – implicit being things you give attention to (ie, the clothes you wear – people guess because of what you wear, you are a certain personality type); explicit being things you gave away (the words you said – when you say “I’m a moron” it’s quite obvious, you are). APML categorises concepts based on whether you explicitly said it, or it was implicitly determined by an application.

Okay, big whoop – why can an APML do for me?
In my eyes, there are five main benefits of APML: filtering, accountability, privacy, shared data, and you being boss.

1) Filtering
If a company supports APML, they are using a smart standard that other companies use to profile you. By ranking concepts and authors for example, they can use your APML file in the future to filter things that might interest you. As I have such a high ranking for Marjolein, when Bloglines implements APML, they will be able to use this information to start prioritising content in my RSS reader. Meaning, of the 1000 items in my bloglines reader, all the blog postings from her will have more emphasis for me to read whilst all the ones about Valleywag will sit at the bottom (with last nights trash).

2) Accountability
If a company is collecting implicit data about me and trying to profile me, I would like to see that infomation thank you very much. It’s a bit like me wearing a pink shirt at a party. You meet me at a party, and think “Pink – the dude must be gay”. Now I am actually as straight as a doornail, and wearing that pink shirt is me trying to be trendy. However what you have done is that by observation, you have profiled me. Now imagine if that was a web application, where this happens all the time. By letting them access your data – your APML file – you can change that. I’ve actually done this with Particls before, which supports APML. It had ranked a concept as high based on things I had read, which was wrong. So what I did, was changed the score to -1.0 for one of them, because that way, Particls would never show me content on things it thought I would like.

3) Privacy
I joined the APML workgroup for this reason: it was to me a smart away to deal with the growing privacy issue on the web. It fits my requirements about being privacy compliant:

  • who can see information about you
  • when can people see information about you:
  • what information they can see about you

The way APML does that is by allowing me to create ‘profiles’ within my APML file; allowing me to export my APML file from a company; and by allowing me to access my APML file so I can see what profile I have.

drivers

Here is my APML, now let me in. Biatch.

4) Shared data
An APML file can, with your permission, share information between your web-services. My concepts ranking books on Amazon.com, can sit alongside my RSS feed rankings. What’s powerful about that, is the unintended consequences of sharing that data. For example, if Amazon ranked what my favourite genres were about books – this could be useful information to help me filter my RSS feeds about blog topics. The data generated in Amazon’s ecosystem, can benefit me and enjoy a product in another ecosystem, in a mutually beneficial way.

5) You’re the boss!
By being able to generate APML for the things you give attention to, you are recognising the value your attention has – something companies already place a lot of value on. Your browsing habits can reveal useful information about your personality, and the ability to control your profile is a very powerful concept. It’s like controlling the image people have of you: you don’t want the wrong things being said about you. :-)

Want to know more?
Check the APML FAQ. Othersise, post a comment if you still have no idea what APML is. Myself or one of the other APML workgroup members would be more than happy to answer your queries.

Don’t get the Semantic Web? You will after this

Published on September 12, 2007 in semantic web, with 9 Comments. Tags: , , , , , , , , , , , , , , , , , , , .

Prior to 2006, I had sort of heard of the Semantic Web. To be honest, I didn’t know much – it was just another buzzword. I’ve been hearing about Microformats for years, and cool but useless initiatives like XFN. However to me it was simply just another web thing being thrown around.

Then in August 2006, I came across Adrian Holovaty’s article where he argues journalism needs to move from a story-centric world to a data-centric world. And that’s when it dawned on me: the Semantic web is some serious business.

I have since done a lot of reading, listening, and thinking. I don’t profess to be a Semantic Web expert – but I know more than the average person as I have (painfully) put myself through videos and audios of academic types who confuse the crap out of me. I’ve also read through a myriad of academic papers from the W3C, which are like the times when you read a novel and keep re-reading the same page and still can’t remember what you just read.

Hell – I still don’t get things. But I get the vision, so that’s what I am going to share with you now. Hopefully, my understanding will benefit the clueless and the skeptical alike, because it’s a powerful vision which is entirely possible

1) The current web is great for humans; useless for machines
When you search for ambiguous terms, at best, search engines can algorithmically predict some sort of answer that partially answers your query. Sometimes not. But the complexity of language, is not something engineers can engineer to deal with. After all, without ambiguity of natural languages, the existence of poetry is impossible.

Fine.

What did you think when you read that? As in: “I’ve had it – fine!” which is like another way of saying ok or agreeing with something. Perhaps you thought about that parking ticket I just got – illegal parking gets you fined. Maybe you thought I am applauding myself by saying that was one fine piece of wordcraftship I just wrote, or said in another context, like a fine wine.

Language is ambiguous, and depending on the context with other words, we can determine what the meaning of the word is. Search start-up company Powerset, which is hoping to kill Google and rule the world, is employing exactly this technique to improve search: intelligent processing of words depending on context. So by me putting in “it’s a fine”, it understands the context that it’s a parking ticket, because you wouldn’t say “it’s a” in front of ‘fine’ when you use it to agree with something (the ‘ok’ meaning above).

But let’s use another example: “Hilton Paris” in Google – the worlds most ‘advanced’ search engine. Obviously, as a human reading that sentence, you understand because of the context of those words I would like to find information about the Hilton in Paris. Well maybe.

Let’s see what Google comes up with: Of the ten search results (as of when I wrote this blog posting), one was a news item on the celebrity; six were on the celebrity describing her in some shape or form, and three results were on the actual Hotel. Google, at 30/70 – is a little unsure.

Why is Paris Hilton, that blonde haired thingy of a celebrity, coming up in the search results?

Technologies like Powerset apparently produce a better result because it understands the order of the words and context of the search query. But the problem with these searches, isn’t the interpretation of what the searcher wants – but also the ability to understand the actual search results. Powerset can only interpret so much of the gazilions of words out there. There is the whole problem of the source data, no just the query. Don’t get what I mean? Keep reading. But for now, learn this lesson

Computers have no idea about the data they are reading. In fact, Google pumping out those search results is based on people linking. Google is a machine, and reads 1s and 0s – machine language. It doesn’t get human language

2) The Semantic web is about making what human’s read, machine readable
Tim Berner’s Lee, the guy that invented the World Wide Web and the visionary behind the Semantic Web, prefers to call it the ‘data web’. The current web is a web of documents – by adding this extra data to content – machines will be able to understand it. Metadata, is data about data.

A practical outcome of having a semantic web, is that Google would know that when it pulls up a web page regardless of the context of the words – it will understand what the content is. Think of every word on the web, being linked to a master dictionary.

The benefit of the semantic web is not for humans – at least immediately. The Semantic Web is actually pretty boring with what it does – what is exciting, is what it will enable. Keep reading.

3) The Semantic web is for machines to interpret, not people
A lot of the skeptics of the semantic web, usually don’t see the value of it. Who cares about adding all this extra meta data? I mean heck – Google still was able to get the website I needed – the Hilton in Paris. Sure, the other 60% of the results on that page were irrelevant, but I’m happy.

I once came across a Google employee and he asked “what’s the point of a semantic web; don’t we already enough metadata?” To some extent, he’s right – there are some websites out there that have metadata. But the point of the semantic web is so that machines once they read the information, can start thinking like how a human would and connecting it to other information. There needs to be across the board metadata.

For example, my friend Michael was recently looking to buy a car. A painful process, because there are so many variables. So many different models, different makes, different dealers, different packages. We have websites, with cars for sale neatly categorised into profile pages saying what model it is, what colour it is, and how much. (Which may I add, are hosted on multiple car sites with different types of profiles). A human painfully reads through these profiles, and computes as fast as a human can. But a machine can’t read these profiles.

Instead of wasting his (and my) weekends driving around Sydney to find his car, a machine could find it for him. So, Mike would enter his profile in – what he requires in a car, what his credit limit is, what his prior history with cars are – everything that would affect his judgement of a car. And then, the computer can query every online website with cars to match the criteria. Because the computer can interpret these websites across the board, it can evaluate and it can go back to Michael and say “this is the car for you, at this dealer – click yes to buy”.

The semantic web is about giving computers the information to be able to interpret data, so that it can do what they do really well – compute.

4) A worldwide database
What essentially Berner’s Lee envisions, is turning the entire world wide web into a database that can be queried. Currently, the web looks like Microsoft Word – one swab of text. However, if that swab of text was neatly categorised in an Excel spreadsheet, you could manipulate that data and do what you please – create reports, reorder them, filter, and do whatever until your heart is content.

At university, I was forced to do an Information Systems subject which was essentially about the theory of databases. Damn painful. I learned only two things from that course. The first thing was that my lecturer, tutor, and classmates spoke less intelligible English than a caterpillar. But the second thing was that I learned what information is and how it differs from data. I am now going to share with you that lesson, and save you three months of your life.

You see, data is meaningless. For example, 23 degrees is data. On its own, it’s useless. Another piece of data in Sydney. Again, Рuseless. I mean, you can think all sorts of things when you think of Sydney, but it doesn’t have any meaning.

Now put together 23 degrees and Sydney, and you have just created information. Information is about creating relationships between data. By creating a relationship, an association, between these two different pieces of data – you can determine it’s going to be a warm day in Sydney. And that is what information is: Relationship building; connecting the dots; linking the islands of data together to generate something meaningful.

The semantic web is about allowing computers to be able to query the sum of human knowledge like one big database to generate information

Concluding thoughts
You are probably now starting to freak out and think “Terminator” images with computers suddenly erupting form under your computer desk, and smashing you against the wall as a battle between humans and computers begins. But I don’t see it like that.

I think about the thousands of hours humans spend trying to compute things. I think of the cancer research, whereby all this experimentation occurring in labs, is trying to connect new pieces of data with old data to create new information. I think about computers being about to query the entire taxation legislation to make sure I don’t pay any tax, because it knows how it all fits together (having studied tax, I can assure you – it takes a lifetime to only understand a portion of tax law). In short, I understand the vision of the Semantic web as a way of linking things together, to enable computers to compute – so that I can sit on my hammock drinking my beer, as I can delegate the duties of my life to the machines.

All the semantic web is trying to do, is making sure everything is structured in a consistent manner, with a consistent dictionary behind the content, so that a machine can draw connections. As Berner’s Lee said on one of the videos I saw: “it’s all about creating links”.

The process to a Semantic Web is boring. But once we have those links, we can then start talking about those hammocks. And that’s when the power of the internet – the global network – will really take off.

Facebook is doing what Google did: enabling

Published on September 9, 2007 in social computing, with 1 Comment. Tags: , , , , , , , , , , , , , , , , , , , , , , , , , , .

The hype surrounding the Facebook platform has created a frenzy of hype – on it being a closed wall, on privacy and the right to users having control of their data, and of course the monetisation opportunities of the applications themselves (which on the whole, appear futile but that will change).

We’ve heard of applications becoming targeted, with one (rumoured) for $3 million – and it has proved applications are an excellent way to acquire users and generate leads to your off-Facebook website & products. We’ve also seen applications desperately trying to monetise their products, by putting Google Ads on the homepage of the application, which are probably just as effective as giving a steak to a vegetarian. The other day however was the first instance where I have seen a monetisation strategy by an application that genuinely looked possible.

It’s this application called Compare Friends, where you essentially compare two friends on a question (who’s nicer, who has better hair, who would you rather sleep with…). The aggregate of responses from your friends who have compared you, can indicate how a person sits in a social network. For example, I am most dateable in my network, and one of the people with prettiest eyes (oh shucks guys!).

The other day, I was given an option to access the premium service – which essentially analyses your friends’ responses.

compare sub

It occurred to me that monetisation strategies for the Facebook platform are possible beyond whacking Google Adsense on the application homepage. Valuable data can be collected by an application, such as what your friends think of you, and that can be turned into a useful service. Like above, they offer to tell you who is most likely to give you a good reference – that could be a useful thing. In the applications current iteration, I have no plans to pay 10 bucks for that data – but it does make you wonder that with time, more sophisticated services can be offered.

Facebook as the bastion of consumer insight

On a similar theme, I did an experiment a few months ago whereby I purchased a facebook poll, asking a certain demographic a serious question. The poll itself revealed some valuable data, as it gave me some more insight into the type of users of Facebook (following up from my original posting). However what it also revealed was the power of tapping into the crowd for a response so quickly.
clustered yes
Seeing the data come in by the minute as up to 200 people took the poll, as a marketer you could quickly gauge how people think about something in a statistically valid sample, in literally hours. You should read this posting discussing what I learned from the poll if you are interested.

It’s difficult to predict the trends I am seeing, and what will become of Facebook because a lot could happen. However one thing is certain, is that right now, it is a highly effective vehicle for individuals to gain insight about themselves – and generating this information is something I think people will pay for if it proves useful. Furthermore, it is an excellent way for organisations to organise quick and effective market research to test a hypothesis.

The power of Facebook, for external entities, is that it gives access to controlled populations whereby valuable data can be gained. As the WSJ notes, the platform has now started to see some clever applications that realise this. Expect a lot more to come.

Facebook is doing what Google did for the industry

When Google listed, a commentator said this could launch a new golden age that would bring optimism not seen since the bubble days to this badly shaken industry. I reflected on that point he made to see if his prophesy would come true one day. In case you hadn’t noticed, he was spot on!

When Google came, it did two big things for the industry

1) AdSense. Companies now had a revenue model – put some Google ads on your website in minutes. It was a cheap, effective advertising network that created an ecosystem. As of 30 June 2007, Google makes about 36% of their revenue from members in the Google network – meaning, non-Google websites. That’s about $2.7 billion. Although we can’t quantify how much their partners received – which could be anything from 20% to 70% (the $2.7 billion of course is Google’s share) – it would be safe to say Google helped the web ecosystem generate an extra $1 billion. That’s a lot of money!

2) Acquisitions. Google’s cash meant that buyouts where an option, rather than IPO, as is what most start-ups aimed for in the bubble days. In fact, I would argue the whole web2.0 strategy for startups is to get acquired by Google. This has encouraged innovation, as all parties from entrepreneurs to VC’s can make money from simply building features rather than actual businesses that have a positive cashflow. This innovation has a cumulative effect, as somewhere along the line, someone discovers an easy way to make money in ways others hadn’t thought possible.

Google’s starting to get stale now – but here comes Facebook to further add to the ecosystem. Their acquisition of a ‘web-operating system‘ built by a guy considered to be the next Bill Gates shows that Facebook’s growth is beyond a one hit wonder. The potential for the company to shake the industry is huge – for example, in advertising alone, they could roll out an advertising network that takes it a step further than contextual advertising as they actually have a full profile of 40 million people. This would make it the most efficient advertising system in the world. They could become the default login and identity system for people – no longer will you need to create an account for that pesky new site asking you to create an account. And as we are seeing currently, they enable a platform the helps other businesses generate business.

I’ve often heard people say that history will repeat itself – usually pointing to how 12 months ago Myspace was all the rage: Facebook is a fad, they will be replaced one day. I don’t think so – Facebook is evolving, and more importantly is that it is improving the entire web ecosystem. Facebook, like Google, is a company that strengthens the web economy. I am probably going to hate them one day, just like how my once loved Google is starting to annoy me now. But thank God it exists – because it’s enabling another generation of commerce that sees the sophistication of the web.