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Alan Lewis - SASPAC Project Officer with Hugh Neffendorf on the Crystal Ball 2011 Census Data Distributor Workshop – 20th March 2007

2011 Ons Data Workshop (20.3.07)

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2011 Data Distributors Workshop

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Page 1: 2011 Ons Data Workshop (20.3.07)

Alan Lewis - SASPAC Project Officer

with

Hugh Neffendorf on the Crystal Ball

2011 Census Data Distributor Workshop – 20th March 2007

Page 2: 2011 Ons Data Workshop (20.3.07)

Presentation structure:

• What is SASPAC?

• SASPAC’s uses and users

• SASPAC in 2001

• 2011 preparation and vision

• Our wishes

• Crystal Ball

Page 3: 2011 Ons Data Workshop (20.3.07)

What is SASPAC?

• mall rea tatistics kage

• Conceived in 1978 to access 1981 Census (Mainframe to Windows-based PC environment). 1991 and 2001 versions.

• IDeA (local gov’t) owns the Intellectual Property Rights (IPR)

• Managed/developed on behalf of IDeA and its users by GLA

• Owned and managed by the Public Sector and is “Not for Profit”

• Funded purely through user annual subscriptions

Page 4: 2011 Ons Data Workshop (20.3.07)

SASPAC, its Uses and its Users

• Data Searching – Querying – Analysis – Manipulation – Export - Presentation

• All 2001 datasets for the UK (inc. SMS/SWS/TVS), 1991/81 Census, Specially Commissioned Tables, other non-Census data e.g. NeSS/OAC/user’s local data

• Users oversee and inform development through SASPAC Advisory Panel (SAP), helpdesk, website, roadshows and training

• Currently approx. 300 member organisations in the scheme (inc. local, central and regional gov’t, health sector, academia, Census Offices, private sector)

Page 5: 2011 Ons Data Workshop (20.3.07)

SASPAC in 2001:

• Windows-based software distributed on CD and updates via Web

• Designed to run on users’ local PCs, networks and thin clients

• Data distributed to our users by CD/DVD/Web

• Strengths:

Page 6: 2011 Ons Data Workshop (20.3.07)

SASPAC in 2001:Strengths:

Access to 1981/1991/2001 + SCT

- datasets

Page 7: 2011 Ons Data Workshop (20.3.07)

SASPAC in 2001:Strengths:

All datasets are searchable

- datasets

- searchable

Page 8: 2011 Ons Data Workshop (20.3.07)

SASPAC in 2001:Strengths:

- datasets

- searchable

- metadata

Table row/column headings with footnotes

Page 9: 2011 Ons Data Workshop (20.3.07)

SASPAC in 2001:Strengths:

- datasets

- searchable

- metadata

- new zone creation

Build new areas using text listings or maps

Page 10: 2011 Ons Data Workshop (20.3.07)

SASPAC in 2001:Strengths:

- datasets

- searchable

- metadata

- new zone creation

- export

Export files in a variety of formats for analysis in other packages

Page 11: 2011 Ons Data Workshop (20.3.07)

SASPAC in 2001:Strengths:

- datasets

- searchable

- metadata

- new zone creation

- export

- GIS

Mapshore – integrated GIS

Page 12: 2011 Ons Data Workshop (20.3.07)

SASPAC in 2001:Strengths:

- datasets

- searchable

- metadata

- new zone creation

- export

- GIS

- Web Publisher

Publish interactive SVG Web pages

Page 13: 2011 Ons Data Workshop (20.3.07)

SASPAC in 2001:Strengths:

- datasets

- searchable

- metadata

- new zone creation

- export

- GIS

- Web Publisher

- flexible

Output Area Classification

Page 14: 2011 Ons Data Workshop (20.3.07)

User Type Super Table

NeSS SCROL NOMIS SAS-PAC

CAS-WEB

Data Brokers

GIS Kits

Market Analysis

Consul-tants

Public R R RProfessional

--Casual use R R R R R--In depth use R R R R--Use others R R--Consultants R R RAcademic R R R

SASPAC in 2001:• On the whole we think we got things about right, met our user needs

for 2001 and continue to do so

• SASPAC represents a large and important user group

• SASPAC’s user spectrum:

• SASPAC keeps changing to reflect the needs of this major user group

Page 15: 2011 Ons Data Workshop (20.3.07)

Preparing for 2011:

• Early days but started thinking and planning for 2011 already

• Programme of consultation and planning between now and 2011

includes: - consulting with SASPAC Advisory Panel (SAP)

- user questionnaires

- roadshows/conferences (with Census Offices)

- funding plan

• More Web-based but retain the strengths/power of desktop version

• Understanding the balance of roles between Census and Intermediaries

Page 16: 2011 Ons Data Workshop (20.3.07)

Vision for 2011:

• Build a culture of trust and partnership between Intermediaries and Census Offices

• Work with Census Offices to help improve delivery of the Census data to user spectrum through an appropriate output strategy

• Working closer with Academic Sector (who are also SASPAC Users),

possible joint development but definitely collaboration and sharing of experience

• Deliver accurate data to our users on time

Page 17: 2011 Ons Data Workshop (20.3.07)

SASPAC’s 4 wishes:

1. Bulk delivery in popular formats (CSV/SASPAC) – Web is unlikely to meet all re-suppliers demands

2. Controlled early release of data to re-suppliers for pre-processing and to trusted/experienced users for QA (rehearsal of 2011 output streams using 2001 data)

3. Agreement in advance of nationally comparable standard tables

4. Improved error tracking/management systems

Page 18: 2011 Ons Data Workshop (20.3.07)

SASPAC’s Crystal Ball…

Page 19: 2011 Ons Data Workshop (20.3.07)

Crystal Ball 1

• We need to think about 2013, not 2011

• We can’t really imagine all the technology yet

• The Web won’t be quite like today (e.g. Web 2.0)

• There will be no (significant) bandwidth, speed or size constraints

• Web and desktop will be indistinguishable

• More use of online data – data filter tool

Page 20: 2011 Ons Data Workshop (20.3.07)

Crystal Ball 2

• Probably .NET base. Search engine style

• We will avoid proprietary approaches

• Very new look and feel but still portable, open, efficient

• More user features – e.g. publishing, analysis, help, wizards

• Work programme established, including consultation and academic liaison

• We will produce first release in 2011 with 2001 data

Page 21: 2011 Ons Data Workshop (20.3.07)

Hugh’s 4 wishes:1. There should be NO differences between E, S, W, NI censuses

except in cases where the need is overwhelmingly clear.

2. OS data embedded in boundaries should be available on consistent terms to ONS data.

3. Imputation should involve modelling where data is sparse, rather than donor records (e.g. matrix data). Similarly, disclosure control should be clever instead of just adjusting numbers. Tables about the same things should add up to the same numbers.

4. Output planning should be weighted toward real, serious Census users and not to casual ones that just want a number.

Page 22: 2011 Ons Data Workshop (20.3.07)

Alan Lewis - SASPAC Project Officer

with

Hugh Neffendorf on the Crystal Ball