The only extra I can think of is similar comparisons and metadata for geographic changes. As OA's are not constant, i.e. some will be split or merged (< 5%) information to identify these will be required. Indeed being able to select these, may even be required as they will potentially be the areas of greatest change.

There are prerequisites for the supply of boundaries for other geographies as detailed on the ONS Geography website.

Is this true, will COA boundaries be charged for?

I would sugest the addition of SARS as a topic and to split the geography section into statistical and administrative. Not sure what you intend to include under "special data products"

The section on SDC is welcome, but the implications of it may need to be included in the "understanding" section as well.

In 2011 this is worth remembering when whatever arrangements are put into place, otherwise a useful dataset may lose it's value if access is unduely restricted.

The origin destination tables, especially at low geographies, will be greatly affected.

The method itself should be unbiased, so that a total of 50 people travelling from OA1 to OA2 would have an expected value of 50, but there is significant variation between the published total (which is a sum of protected counts) either above or below the unperturbed total.

The variation can be seen for OA to OA counts broken down by different variables. For example, using a breakdown by age and sex could give a total of 25, a breakdown by economic activity could give a total of 33. By taking all the different published breakdowns and averaging the totals, one gets a still unbiased estimate and with far less variability from the unprotected count.

For the 2011 Census, we have already proposed that origin destination tables at low geographies are protected not by SDC methods, but by licensing and access arrangements. The precise details of this approach have not yet been finalised.

We try to use the detailed OA to OA origin :destination tables to estimate 'self containment ' patterns for migrations and travel to work patterns, to help in identifying funcitonal housing market areas. At this scale pretty well every cell is '3', which potentialy causes a lot of distortion. Common sense would suggest that longer distance moves/commutes are likely to be smaller numbers.

But if changing the disclosure rules looks like an unwinnable battle, what would help is some work to show how much distortion it actually does cause. I've experimented by changing all '3' cells to 1 or 2, to see the effect, and it is noticeable. But a check against the real numbers at different distances could perhaps give an average variation that could be applied.

The past graphs should also be replaced gradually with traditional flat versions

That extra 'don't know' option is there now - if it does not appear then just refresh the page and it should be OK.

My guess is that for most people in a home \ school based role that a NeSS like website will provide what is required. For greater access of data a NOMIS approach for users who want more data and less analysis \ mapping. Over this will be those who want the census output in bulk and little extra.

Whether you agree with my conclusion about groupings and requirements, there does require a clarity when researching the requirements, of who the answer is aimed at, in order that the question can be properly asked of and targeted at the appropriate responder

There is also a desperate need to tweak Output Area boundaries so that they are recognisable on the ground: that they run along the centre of roads and streams, face of fences and walls, between boundary stones, etc. This is for the most part technically achievable: the anomalous parts of OAs generally contain no residential properties; anomalous OA boundaries rarely pass through them. Snapping to physical features in this way would be worth the effort (if not the spurious expense of commercial charges by Ordnance Survey and the Royal Mail) and would greatly increase the acceptability of census data to general users.