— Giuseppe Sollazzo (@puntofisso) March 2, 2017
was an interesting thought piece. Could we even identify them, let alone publish them? Here follows a very quick rapid reflection on it…
Caveat 1: What I’ve described as ‘data sets’ are kind of a mix between system and broad subjects covered through complex relationships often between multiple databases and specific, easily defined and well documented data tables.
Caveat 2: This was done as a quick, reactive exercise – so naturally a huge weight on my own subjective judgement as to the ‘importance’ of a given service, with some consideration of:
- Cost/Organisational Risk
- Public interest (i.e a volume of people care about it, as opposed the legal public interest)
- Existence as a dataset. E.g. some of the data that might be most interesting (holistic decision registers, say) simply don’t exist.
- Short term political exigency
- So, then – in no particular order (and there’s more than 20):
- Children’s Social Care: (Caseload, status activity and outcomes)*
- Adult Social Care & Health: (packages of support, safeguarding and outcomes)*
- Education status and outcomes (e.g. progress, attainment)*
- Owned Property assets, income and arrears against same(!)
- Council tax base, collections and arrears*
- Staff lists*
- Budget outturn
- Income and Savings profiled against budgets
- Customer contacts (via contact centre)*
- Capital programme (what are we going to build)
- Council meetings, formal decision registers
- Commissioning intentions (what are we going to buy)
- Public Protection Service requests*
- Specific asset management & repair
- Public realm assets (characteristics) (It’s actually deeply disingenuous to count this as one dataset, because it’s hundreds – from allotments to zoos.)(!)
- National/ government produced statistics subset to local authority (and below)
- Local Land and Property Gazateer(!)
- Waste collection and recycling volume
- Pension fund assets and liabilities
- Library use*
- Transport network monitoring (counters etc.)
- Car park occupancy
- Local development (Planning) applications and decisions
- Licensing applications and decisions
- Air quality monitor outputs
- Electoral Register*
For Open Data interest, I’ve tagged (*) those datasets that are wholly derived from personal, or sensitive personal data so from the basic perspective of open data and (!) for those which are, or might wholly be subject to Ordnance Survey licensing restriction.
Other data could be determined as commercially sensitive (particularly that which relates to commercial market activity, such as property management or pensions), but that would need much further debate.
Finally, I’ve explicitly not included population/demographic/needs based data or performance monitoring (which given my day job was a struggle) as in most instances that would itself be derived from the above.