Dissecting the still-breathing body of "Open Data"

Benjamin Welby has a great 5-part series on Open Data, summarising a lot of the current state in local government, and raising some good questions about how local government can lead on a lot of this. His first article picks up on my "Open Data must die!" post, and got me thinking about the term itself again.

Why is this an interesting thought exercise? Maybe the names don't matter, and function is everything. But at the same time, names crystallise our shared understanding of why we're doing something.

So why do we use the term "Open"?

Partly legacy - open source, open access, open-not-closed. All good stuff.

But in the context of governance, what role does the term "open" play? In fact, if we look at the two aspects of a) service delivery and b) democratic engagement, why is openness important? Answering this question, I believe, is key to moving open data forward - by clarifying new purposes other than openness in its own right. By setting an agenda other than "being open" we can start to look at being smarter and more productive, but within a context of accountability and shared decision-making.


Service Delivery

Let's take a break for a moment and consider the commercial world of "open data" - the Flickrs and the Googles and the like. A lot of the push for open government data came from a shift in the web paradigm from "data-as-a-website" to "data-as-an-API". Suddenly control of the data opened up - an essential inevitability as websites moved to a social model of importing data from users more and more. The website became a store, rather than a presence in itself.

Openness in this commercial world meant (or means) that developers were no longer restricted to the path to access this data that the website builders had pre-determined. You could suddenly write your own slideshow script based on your (or someone else's) Flickr photo stream, for example. Or print it out. Or turn it into text.

To return to government services, we have two types of user though, and two types of data.

First, we need to differentiate between data used by individuals and data used by policy-makers.

Second, we need to compare data about individuals with data about systems. By systems, I mean any organisation or structure that can be seen as a "whole" - such as transport systems, finance systems, demographic systems and geographic areas, etc.

This gives us a basic 2-way matrix on to which we can position "data" (which, after all, is ubiquitous):

Box 3 is greyed out because it doesn't count, imho. Ignore it?

The commercial data mentioned above falls into box 1 - a user accessing their own data. This is largely ignored (or discussed in fairly esoteric circles) under the governmental "Open Data" banner because it's hard. It's probably also the most useful, but maybe one to come back to. People tend to think of health data and benefit information, but one could also include library data (reading histories, current books, etc) and so forth in here.

Box 2 - systemic data used by individuals - is where a lot of people would like to position Open Data, whether it fits or not. The idea of the "individual" accessing data appeals to our consumerist lifestyle, like governments fulfilling their public-good role for the ultimate satisfaction of the private citizen.

(The "Armchair Auditor" idea falls into this precise trap of supposing that individuals will hold Government to account. There is nothing more romantic than a single person overcoming Universal Might.)

Some of this data is actually really, really useful. Transport data, opening times, prices, etc - this is the realm of information that we all use on a day-to-day basis. But that kind of data is "small" information - we consume something very specific in very short bursts, such as "next bus from stop X", or "who is my councillor?". These could almost be considered "facts" about the world.

Other data is also relevant to individuals, but from more of a research perspective. Being able to present data differently, such as with TheyWorkForYou, or aggregating data up to make travel-time-vs-house-price maps, starts to address the notion of how we can interact with the data in a user-experience kind of way. But to engage, users must not only interact with the data, but also with the democratic process (see box 4). The boundary between these two seems relatively unexplored so far.

Box 3 - policy-makers accessing data about individuals. I'm actually going to call this a void box, because I think at this point we transmogrify into anecdotal evidence, rather than data. Policy-makers love using stories about individuals, far more than comparing their stats in a Top-Trumps-esque kind of way. Comment if you feel differently.

Box 4 - systemic data used by policy-makers - really leads us into the idea of "democratic engagement", because it's where the overarching power lies. This is the data/evidence used to make decisions at a higher level. It needs to be aggregated to resolve complexity (and gain understandability), but be reliable and resilient enough for decisions to be made confidently.

This box includes data about government activities, such as spending data, as well as data about geographical areas, such as the IMD and National Indicators and demographics and so on.


Opening up Box 4

Box 4 is the most interesting, because it hasn't really been done before. Or rather, not in an open sense. Plenty of companies use "systemic" data - or "big data" if you like - to explore trends and make decisions. But all that data is valuable and therefore closed.

This is where and why Open Data hits challenges: the systemic data in this box is fundamentally tied to how administrations work and think. That is, it represents a worldview upon which certain types of decision can be made - accountable ones, justifiable ones, trackable ones. Data here, whether it's financial, organisational, demographic statistics or what-have-you, has gone through a long history of hammering out. To be usable, it must be comparable, and to be comparable it must be rigourously defined, in terms of what's collected and what it means.

It's why we have National Indicators and the ESD and consultations on standards within government.

And this leads to a bit of a paradox, which the Open Data world is currently trying to grapple with:

First, the data needs to be understood, because it's so well defined.

Second, the data - even after being understood - is only useful to its original context (the policy-making hierarchy), even after being understood.

Both of these together form an interlocking puzzle: If people don't understand the data, how can they use it? And if not's useful to them in their context, why would they want to understand it?

(Additionally, this paradox is semi-locked inside a Japanese puzzle box. Even if you get both, do you necessarily have the power to influence decisions?)


Democratic Engagement

This gives us effectively a 3-way combo lock on Open Data, which immediately answers our second purpose - that of democratic engagement. There is a philosophical argument for democracy, and indeed a philosophical argument for "openness". But I would say we have that already - people want to engage, even if out of a sense of ownership ("I pay my taxes and vote, therefore I should have a say.").

But people are also busy and/or lazy - there's no philosophical drive to see how government works any more than I have a philosophical drive to see how my computer works while I'm using it. Rather, I look at source code when I want to change it or write my own. The philosophy of "openness" rapidly transforms into a reality of "effect". And it's this sense of being able to "effect" that the idea Open Data comes down to.

Next time you see a dataset being opened up, ask ye 3 questions of it:

1. Can I understand it?
2. Is it useful to me in my life?
3. Who's listening for answers that might lie within it?

Too often "Open" data ignores all 3 of these questions. "Raw data now" ignores these questions. You cannot separate data from policy and expect engagement.

"Open" is a mindset, not a piece of content.

"Open" cannot be an end in its own right. 

Supporting a System of Spaces

I can only describe CityCampBrighton last weekend as an organised maelstrom of ideation. I don't know what that means, but it sounds great, kind of sums up just how much stuff was going on, and at the same avoids any real definition. Bingo.

So there are a few thoughts I'm hoping to blog shortly. But to begin with, why not talk about space?

Stuff Has To Happen Somewhere

There is a notion that says the Universe exists so that everything that happens can happen somewhere. In our virtual, post-Universe model of the world, we often assume that things can happen in a zero-size, flatworld-like dimension which doesn't really exist. From bricks-n-mortar to clicks-n-, um, whatever, the physical idea of "space" is something that has been done. Physicality is expensive, and all that.

But "virtual" or "real", spaces are where things happen. People gather, drink coffee, discuss ideas, make stuff, drink beer, and learn. People dance, have rubber band fights, listen to music, watch their babies, play board games, race cars. Everything happens somewhere but not everything happens everywhere and not everything can be done anywhere. Everything has its own idea of what space it needs.

Stuff happening in space. Source: Hubblesite.org

The CityCamp Space

CityCamp itself follows an open-space meeting style space, with its own rules - namely that a) the sessions are set at the start, and b) you can attend/leave whichever session you want, even halfway through. You are not allowed to be offended if someone walks out on you. (Although I never worked out if I was allowed, theoretically, to walk out of my own session.)

CityCampBrighton obviously discusses a larger "space" - Brighton and Hove - with an aim of setting out the existing "participants" (population) and "rules" (local regulation, etc.) and working out how new ideas can take these forward. In the process, the multitude of "local" spaces (shops, galleries, public facilities, tourist attractions, homes, etc.) come into play. All of these, I believe, are massively important to Things Being Done - to bring people together absolutely requires that idea of a space, set aside from everything else and with its own specific sense of purpose.

Reconstructing these kind of spaces is what geeks like doing. We come up with forums and MUDs and social media so that we can talk to people a) across the world, and/or b) when it's too wet to go out. So there has to be an intrinsic link between "real" space, and these simulations of space. They have to encourage the same kind of interaction and sense of environmental purpose that allows people to talk, and to support Things Happening somewhere.

CityCamp discussion in full swing. Source: Adam Oxford

In her 20 CityCamp Things, Catherine Howe picks this up at point #19:

19. I want to spend a lot more time looking at the intersections of offline and online networks and spaces.

And in his reflections on the day, Toby Blume (one of the judges) also makes the bridge between within-CityCamp space and without-CityCamp space, and the purpose of the former:

Using technology to develop social innovation has huge potential but I still feel it’s an invited space which non-techies are welcomed in to, to a greater or lesser extent. I can’t help feeling there’s more we can do to establish and support social spaces that put technology second to community action

There were so many good ideas at the weekend, but as Toby points out, not all of them were necessarily "right" for the funding prize on offer. Some were fresh ideas and needed more direction. Some were too large. Some might even be too small. In a way, there's perhaps a dilemma over whether CityCamp is there to award funding Dragon's Den style, or to foster networking and new ideas. (Personally, I think this dilemma adds to the creative tension. Don't change it.)

Grow the System

But the whole point of this piece is to highlight that a space isn't just a space - it's one space in an integrated system of spaces. The original purpose of open-space meetings and the Law of Two Feet is that ideas shouldn't be constrained or killed by the space (or conversation) they were born in.

A new idea often requires a new space. Sometimes that's 2 people standing around a different table. Sometimes it's a cafe instead of an office. Sometimes it's a mailing list or a wiki instead of a cafe. Sometimes it's a meeting involving dozens of stakeholders. The idea moves and proliferates from one space to another (or even to many others) depending on who's taking it forward, and what needs to be done about it.

An open space. With an obstacle. Source: Andrew Middleton

What can really kill an idea, then, is throttling this ability to jump from space to space. Either the space that someone would like to use isn't there, isn't quite right for the idea, or the person can't get to it. Taking each of these in turn, how can we support a system of spaces that means any idea has a better chance of survival?

1. Turn private spaces into available spaces. I almost put "make more spaces" here, but I'm not sure that's useful. We have enough space, but more often than not it's parcelled off as "private". The commercial mindset has shifted us to a world in which it's more acceptable to have adverts plastered over everything than it is to have public notices, or even art. This needs changing.

In the physical world, this can mean more negotiation to get more/cheaper/longer access agreements. Or it can mean taking space without permission (think flashmobs, or graffiti).

In the virtual world, gathering has tended towards "private" spaces - i.e. commercially-owned ones - more recently, with the onset of Twitter, Facebook, Google Docs, etc. If the rules bother you, then remember that there is always an option. Learn to code. Use open-source. Host your own service. People do this all the time.

2. Make spaces flexible. Sometimes a space is good, but not quite good enough. It needs tweaking. Physical spaces might need to be rearranged, or items might need to be brought in from outside (projectors, flipboards, power sockets, wifi, kettles). Virtual spaces are actually often harder to change - but should have enough options available to be adapted to the need.

In other words, don't be stingy with what people can do to a space. Too many seminar rooms still have tables all facing the front, and all bolted to the floor. You probably don't know - or shouldn't know, even - what people want to do - trying to predict this can limit the flexibility, or influence the purpose of the space. Be open to change. Ask people to put things back if you like. But don't just put the space before the idea.

3. Allow Ideas to get out, even if People can't (yet). OK, a slightly odd/different one this. But it's fundamentally important to realise the creation and value of an idea, even if nothing can be done about it right now. And to that end, any space that wants to be part of the system of spaces needs to allow/encourage a) somewhere for ideas to be "put on hold" - whether it's someone taking notes for themselves, post-it notes on a window, or an alternative to-do list - and b) a way to connect the people interested in that idea outside of the current space. For instance, attendee lists, Twitter lists, and feedback forms all allow sub-groups to re-connect, form and potentially move elsewhere.


That's 3 starters, anyway. The aim is really just to let ideas - and the people interested in them - to be able to do what they want, where they want to. It's to unlock all that potential currently caged up through middle-scale, short-term management. It's to turn missed opportunities into a framework that can nurture the next generation of ideas, rather than try to control them.

Data Engagement as a Healthy Ecosystem

Writing up the "Data Engagement (Everyday Data)" session from #ukgc12 is tricky, because it opened up a whole set of new questions and thoughts for me. I'm still trying to tie these thoughts together, and might break it down into a series of posts. This one starts out by looking at the many uses and users of data, and how this fits in with the Data Engagement Charter (see Tim's post) that others started to put together in the Saturday session.

Data as an Ecosystem

A year ago, I asked some questions around the relativity of data. It feels like I have some vague answers now, even if they're shifting about still.

The BBC are currently showing an awesome series about the history of plants on Earth, called "How to Grow a Planet" - but it's not just about plants, it's about how plants developed alongside rocks and Sunlight, and then how they developed alongside animals. It's a story of opportunity and of symbiotic relationships - in other words, of how co-dependence can lead to vitality and huge, thriving ecosystems.

The idea of data as an ecosystem isn't a new one. But it is one that's easy to forget, especially when we're staring at technical formats or CSV files, or when we're on a crusade for a much larger philosophy. However, understanding how different data users interact is key to a data itself thriving. During the session, I drew something like this:

At the time, I wanted to capture the important thing - the links from one group to another. In other words, data flows from user to user, from group to group, and gets transformed as it does so. This is the fundamental reason why data is good - not because it is easily automate-able, or easily packageable into binary, but because it can and does mean different things to different people. And yet we are also intrinsically linked through that flow of data at the same time. All different, yet all the same.

Each group has different needs and different backgrounds, and so each link in the diagram, at a data-level, will involve different...

• Access needs
• Numerical understanding
• Contextual, real-world understanding
• Quality needs
• Reliability needs
• etc.

A systemic/network view of data moving around means we can move from a "one size fits all" perspective to a narrower, more specific viewpoint. This means we can ask questions such as:

1. What is our role and our position in the system?
2. Who are our audiences (current and potential) and what do they want?

This gives us a less scary starting point than the idea that every data-handling party needs to cater to every other data-wanting party. Not everyone needs to do everything. We've come to grapple with this the last few years, with the shift from central authorities specifically providing data to an "end user" (if such a user exists) to providing "raw" data for a different audience. But the debate is still murky and needs to be made more explicit.

Data Engagement Charter - A Star Map?

Which is where a Charter can really help, I think. Although not just in terms of giving people an easy-to-follow guide, but also as a way to really map out the different uses and users of data. Si Whitehouse's blogpost on the subject has a 4-way use-case diagram positing 4 different types of people who want to find data:

Can we use this to start working out what the most important needs of each are, and more importantly, who could be filling those needs? And vice versa - if you have an existing audience who are struggling to engage with your data, what can you do to make it meet their needs?

I wanted to use this image to illustrate this post, for some reason:

At some level it represents an opening up of barriers, which can summarise the ongoing efforts to open up data. But at another level it's a great image because it mirrors both the links in the first image above, and the two dimensional axis sitting nonchalantly in the Use Cases diagram. It not-so-neatly sums up the way in which data flow changes according to what the data is being used for right now. Sometimes cars need to flow. Sometimes trains need to flow. With the right barriers and the right flexibility, we can have both. Or all, depending on how many users we're talking about.

So there's no "right" answer to how data should be opened up, any more than there's a "right" answer to which programming language I should use. There is what's most appropriate, perhaps, and certainly what's most fun. Linked data and SPARQL are good in some cases. Excel and Word reports are fine in other cases.

How to Have a Healthy Data Ecosystem

Having said that, it's not quite true. To keep an ecosystem alive means sticking to some rules, otherwise we end up with fragmentation, infestation, and/or the possible collapse of large parts of that ecosystem.

The 2 main components of a healthy system are, for me, openness and feedback.

Openness allows for flexibility and the ability to rapidly make new connections - vital when the environment changes (climate-wise, but also economically, politically, and technologically). Without openness, things can exist for a while, sure, but there is little resilience as time goes on.

Which standard gets used for data doesn't matter as much as whether we can interface with it in the future. We need to avoid data lock-in (or lock-out, depending on where you're standing) - whether that comes from legal, technical or economic aspects. There may be reasons for certain barriers (such as privacy), but these shouldn't translate into a general attitude of making data difficult to obtain. Legal barriers should not prevent technical access from being as easy as possible, for example.

Feedback is also vital, as it provides a way to negotiate the value of data without resorting to a "survival of the fittest" regime. Feedback in a data sense means that the fruits of Data Engagement benefit both parties involved - and that the link between parties gets stronger as a result of it being used.

In other words, we need to consistently and continually make sure that data is useful, otherwise the disadvantages of providing it and acquiring it will outweigh the benefits.

A Data Engagement Charter is an awesome first step to understanding and realising this. Such a Charter, alongside technical prowess and legal openness (another post), can be a very real call-to-arms for this recipe for an ecosystem. To make data successful, we have to understand that we are co-dependent on each other, and that it cannot be a one-way flow, even if we try to make it one.

"Open Data" Needs to Die

Amongst all the UK GovCamp 2012 buzz, point #18 from Tom Sprints' write-up caught me as being one of the more curious:

18. A lot of “open data” sessions just seemed to me to be variations on a theme, and didn’t sell themselves to me at all. I am therefore worried that some of those discussions are either very esoteric, or insufficiently informed by people who understand the issues rather than the tech.

Where have we come from?

As a data geek (I like the word "mechanic" myself), it's been intriguing to see the conversation around "open data" change over successive GovCamps. A few years back, the question was heartily "How can we get hold of data?" - Tim Berners-Lee was starting out on his comeback tour, and mySociety were beginning to show that data could be made useful with some clever tools.

As I remember it (likely in a fairly biased narrative way), the conversation then switched fairly rapidly into "What's the best way to open up data?" - in terms of what data and what platforms were most useful to developers. Suddenly data stores had (experimental) APIs, and the public realm had massive amounts of spending data. There was some loose rhetoric about transparency and accountability, while developers picked things apart with fine Excel toothcombs.

Then things got more interesting, as it turned out everything that had happened so far didn't automagically lead to Amazing Stuff Happening. The question became a necessary "So what?" - as if transparency and accountability weren't enough by themselves! The topic turned to users and reasons and (more often) to interesting examples. Surely, somebody was clamouring for this stuff after all this?

I'm kind of hoping this explains something about why "open data" sessions are a bit fumbly-jumbly now.

Open data got complicated, quickly. Because data is complicated. Jump to the present, and conversations rapidly flit between all of the above either because everybody is involved at the same time, or the people who should be involved, aren't.

"Open Data" is harmful

Or both. The paradox is that it's become difficult to talk about open data firstly because those who were talking about it from one point of view are now talking about it from many points of view. And secondly because those who weren't talking about it before aren't talking about it now. Data silos still exist. Most people still use Excel. Statisticians still output reports.

The term "open data" is meaningless now. Not just meaningless - actively harmful. If you're used to talking about it, then the conversation has begun to fragment and coalesce around more subtle outcrops. And if you're not used to talking about it, then you're put off because nobody can explain what it means - and more importantly, what it means to you. So you carry on as normal.

My session at GovCamp on Data Engagement was, in retrospect, an attempt to get back to the previous question of "So what?". What I really want to do is fence the conversation off from the technical, economic and political aspects of data (although I'm still into all these things) and focus on the why. I desperately tried not to use the term "open data" because I think it would have distracted the discussion. (To be honest, I wanted to find something better than "data engagement" too, hence the phrase "Everyday data".)

And I'm really glad that some of the idea got taken up on day 2 by Tim Davies and others. A "Charter" for engaging with data really starts to delve into how we think about how to make data useful.

I admit I'm a little afraid that the term "Open Data Engagement" just makes the discussion even more vague. What does that mean to you if you have no idea what it is, or what Open Data is supposed to be? Is it all at risk of becoming another buzzword? What about "Data Usability", or "Public Data Engagement"? I'm still aware just how much I hate the terms "Public Understanding of Science" and "Public Engagement with Science". Are we going round in circles?

Should we call a Stats Spade a Stats Spade?

Many people with useful, everyday data and databases really don't think in terms of data. Because the data is about stuff they know, they think of it as "information". Maybe even a "resource". But ask them what "data" they have and they'll probably give you a back-up of their website.

One of the interesting points coming out of the Data Engagement session was that people deal with data all the time - think football, Formula 1, house prices, etc. But do people even refer to this as "data"? Or - more likely - do they call them "stats"? Mention "stats" and people think of tables, averages, and counts.

In a way, "stats" makes sense where "data" doesn't. "Information" makes sense where "data" doesn't. "Data" is tricky because it's all of this and more. It's figures, it's formats, it's visualisations. No wonder even those who understand this get confused when talking to each other. The more you try to take "Data" into the real world, the less the term applies.

Should the "open data" moniker be scrapped instead of more "useful" terms like these? Would this make talking about implementing it more difficult, or easier? After all, any conversation on how to make data useful quickly turns away from talk of even databases and on to other issues (standards, protocols, best practice, comprehension).

Maybe if we talk about our bus times as "public information", and spending figures as "spending figures" then people will be interested in it, and we can stop trying to work out what "open" means.

Maybe.

UKGovCamp 2012 - 5x5 (plus one)

So Friday and Saturday were host to the indispensable UKGovCamp 2012 - a huge gathering of people interested in making public stuff better with technology, roughly speaking. I got along to the Friday day all about talking (rather than Saturday's doing), and gorged myself on thoughtmeat. Seriously, I was feeling dizzy by lunchtime.

Somehow I think I managed to carry on talking sensibly enough to feel useful. I also took notes and recordings of the sessions I was in, but here are 5 points from each that struck some kind of chord with me. They're a mix of things people said, and stuff I thought, but I think I can remember which was which.

I've put up audio from each session here.

Session 1: Data Viz + maps issues + challenges
- Vicky Sargent

This seemed to focus largely on data quality.

• Poor quality data can be exposed through openness.
• Different users/uses want different levels of quality/reliability. 
• Bringing together those who want reliability with those who want usability is hard.
• Getting useful "infoporn" is hard.
• Start by knowing what you're trying to achieve.

Session 2: Open Data as a Business Model
- John Sheridan

This went into how to sustainably fund both open data, and businesses based on it.

• It's not just a choice between "open"/public and "closed"/private.
• Perceptions of data reliability (including being up-to-date) are inherently linked to data management and its economics.
• i.e. Some people think you need a tightly controlled team / contract / business model to maintain data quality... Whereas others think openness is a viable form of reliability. (Cf. Wikipedia "vs" Encyclopedia Brittanica)
• Licensing offers multiple funding models depending on end-user, a la open source software. Chris Taggart doing a lot of this with openlylocal.com
• Does the data business model depend on the size/resources of the dataset/audience?

Session 3: LinkedGov tool to clean up & link data!
- Dan Paul Smith

This was a demonstration of the really impressive work being put together by @LinkedGov (http://www.linkedgov.org).

• Software that extends Google Refine to let you easily link data structures and tidy data.
• If letting people edit data ("cleaning", "linking", etc), you have to be careful not to introduce "new" data such as assumed defaults for new values. 
• Suddenly linked/semantic data is starting to look really powerful. I'm almost converted :-)
• The ability to "modularise" links to other external data lists has huge implications for data as a Distributed Ecosystem.
• Metadata for what's been edited needs to be accessible and clear, to understand who's done what over the lifetime of a dataset.

Session 4: Data Engagement / Everyday Data
-  me

This was an attempt to think about how to get data into something everyday and, not perceived as a "technical" thing. "Slides" and audio available.

• People love data if it's about something they love - e.g. football, F1, sales...
• Language used is massively important - often 2 groups will talk about the same thing, but in totally different ways.
• A range of "necessary" precision was brought up again - how can you transform the complexity of data into simplicity without misleading?
• Does data visualisation have to be 'comprehensively accurate', or can it just be enough to get people to ask more questions?
• Give data context and it's easier to turn data into feedback and so learn from it.

There were some great examples, and some amazing ideas coming out of this for me, which I'll blogpost properly soon.

Session 5: Network society engagement
- Catherine Howe

This wasn't to do with data at all... This was about the advantages offered by moving to a more networked, more engaging approach to decision-making.

• Catherine claims that the current system of engagement/consultation is actually a method to mitigate our own ongoing disappointment in political participation.
• If done better, political participation can be enlightening, rewarding, and fun.
• Bringing people together as part of the consultation process can mean they understand it/others more, and are less disappointed if they don't get what they want.
• Feedback as part of the consultation is vital to success. In effect, consultation moves towards conversation rather than just gathering views. (Does this that changing people's views is an objective of a networked approach? Does this raise questions around the accuracy of the final result, or does a more involved process and more post-process feedback negate this?)
• While I generally agree, I wasn't sure how much success from trials was down to using a networked approach, and how much was down to just using a different approach (i.e. novelty can often be fun in itself) - more consultation iterations needed?

I'm running out of time so won't go over Mike Bracken's speech or the Closing Note. Here are 5 random, general points instead:

• The data landscape is slowly coming together in my head. I know I know something important about it, but I don't know what it is yet. Like Cooper in Twin Peaks. You know, when he has that dream. I need to mull it over and chuck some rocks at a bottle.
• It feels weird not having twitter usernames on name tags.
• GovCampers are a bunch of (mostly beardless) ale-swillers. Much to the surprise of the pub.
• The engineering/development going into the new gov.uk single domain is seriously good.
• The medium T-shirts this year are definitely smaller than the medium T-shirts last year. Or did I get a ladies' one?

Pintless Debate

[In which the debate for/against the regulation of pub companies is ultimately broken down into the futility of arguments.]

The Parliamentary debate on the future of pub licenses has me hooked. Living in Brighton, it's difficult to describe, or even imagine, just what effect local pubs have on every day life - from evening entertainment, to decent food, to convenient meeting and organising places, to Damned Good Beer.

So it was great to see my MP Caroline Lucas weighing in with views from the Landlord of the Greys in Hanover - in fact, this was why I clicked through to the rest of the debate.

Two Pints, Please

In a nutshell, the debate is a classic "is market self-regulation enough?" argument. Most voices in this one argue that large pub companies ("pubco's") have too much power when it comes to setting a) rents for licensees, and b) rules and rates for "guest beers" and other things that help make pubs "interesting" (or affordable).

The motion moves for regulation to free up licensees from this "beer tie" and to review the self-regulatory nature pubs by an independent body.

But as you read through, it becomes clear that the debate is really about:

1. BIS' response to CAMRA's complaint appearing to be taken fairly word-for-word from a BBPA (British Beer & Pub Association) submission without much further input - recently discovered through an FOI request.

2. The Government's apparently "weak" action of apparently rubber-stamping the self-regulatory guidelines as what should constitute the statutory code. (See Adrian Bailey's comment.)

3. What seem to be otherwise fairly "liquid" but one-sided negotiations between tenants/licensees and the pubco's (see here for example).

Brian Binley makes a very interesting point about the unsustainable debt model used by pubco's basically being passed on to landlords - and hence on to consumers, who unsurprisingly either go to a cheaper local pub (if one exists) or the supermarket. Andrew Bridgen goes on to call it "almost feudal".

How [the] debate rages

But over time, the debate threatens to emerge from its pretence of being about the pub model, and into an attack on the political process that is driving it (or being driven by it). At this point, the debate breaks down into 3 types of discourse:

1. Anecdotal/qualitative rhetoric: Stories from constituents, traders, etc. I suggest that the Select Committees' evidence also falls under this as they adopt an "interview" style approach. (Also, here's a good SC report from 2009 on the matter.)

2. Statistical evidence for/against intervention: Ed Davey seems to use stats more than others, for example.

3. Attacks against process and character: With the nature of the BIS response and its apparent "close ties" to the BBPA being thrown open by the FoI request above, this is a third line of argument which seeks to undermine both of the above, on matters of personal principle.

There are also appeals to "external" authority. The OFT, for instance, seem keen not to be involved, which leads some to say they're not relevant, but others to say this merely means regulation has no place in an apparently successful market.

Welcome to politics. What's interesting is how - or if - each of these types of argument "trump" each other. In other words, should we give pubs more choice over beer because 

a) a lot of people say it's a problem?

b) data suggests there is a link between lack of freedom, and pubs closing?

c) the people behind the non-choice have too much economic and political power?

In my mind, this is a bit of a paper-scissors-stone situation. Can any of these really be more important than the others, or do they just lead to a cycle of disagreement? How much do each of these - or all of them combined - duly influence any voting on the matter? And should I really have bought that four-pack of Speckled Hen from Sainsbury's today?

Exit, Stage Left

I also liked the general response to Ed Davey's comment which reads a little like the script for a bad school comedy play:

Brian Binley: Will the hon. Gentleman give way?
Edward Davey: No, I want to make some progress. 
[Hon. Members: “Oh!”]

Also:

Martin Horwood: Will my hon. Friend give way?
Edward Davey: No, but I will in a second.
Brian Binley: Will the Minister give way now?

Occupy is not equality, it is Equality.

Read Occupy London is a nursery for the mind by Madeleine Bunting at the Guardian. Think this through. 

Let's be clear. The Occupy movement is not about equality. Sure, they talk of "the 99%", but this is more a description of the world around them, rather than who should act. 

It is not about forcing a one-size-fits-all, globally-empowering solution, but about the personal ability to build a better world where you are. The most important message coming out of the Occupy movement is that there is no global solution. There is only what you can do.

Those striving for equality rely on some kind of Universal Right - but such Rights always require a centralised and authoritative power to maintain that equality. Capitalism "fought" against communism with this very tenet in mind - that the network is more sustainable and more adaptable than a single viewpoint.

Now maybe history is being repeated - the New Network is flexing its strength around an old one that has crystallised. The old market has laid out its flaws for all to see (imbalance, resource exploitation, workforce exploitation, future exploitation), and challenges the centralised authorities (the State) to fix them. The enemy and the saviour are on the same side.

The Occupy movement is not about equality as we understand it because requires effort, and responsibility, and right now, the motivation to employ this effort scattered between individuals. Instead, t is about inspiration. The idea of "equality" is shifted fundamentally, from a notion of identicality - in terms of living arrangements, in terms of spending power, in terms of life expectancy - to a notion of potential.

The difference is huge. It almost seems to speak more to traditional market values than those who defend the markets as they stand. The idea that you get out what you put in, and that if you create true value then you will be valued. Be smart. Be authentic. Be happy. Be hard-working. Be connected. Be helpful. All of these are network values.

And all of these are values inherent to each and every one of us, not "skills" that we "choose" to get "taught".

Commonality is the new equality. Everything else - how you live, how you die - is just what you do with it.