Amt für Statistik Berlin-Brandenburg Dr. Peter LohaußState Statistical Institute Berlin-Brandenburg Q 2010 Helsinki 5. May 2010 Managing Processes in Data

Q 2010 Helsinki

5. May 2010

Amt für Statistik Berlin-Brandenburg

Dr. Peter Lohauß State Statistical Institute Berlin-Brandenburg

Managing Processes in Data Dissemination


1 Quality principles

Relevance: European Statistics must meet the needs of users.

Timeliness and punctuality: European statistics must be disseminates in an timely and punctual manner.

Accessibility and clarity: European statistics should be presented in a clear and understandable form, disseminated in a suitable and convenient manner, available and accessible on an impartial basis with supporting metadata and guidance.


2 Types of users


3 Internet as dissemination platform

Public: Basic online tables, charts, maps, publication download

Experts/Knowledge worker: online access to databases or data cubes for extensive analyses and download

Researchers: online microdata access with automatic disclosure control to be developed

User satisfaction surveys: easier internet access, more small area data


4. Statistical Information: Product or Service?

Producer User Producer User


2.1 Design outputs

5. The Generic Statistical Business Process Model dissemination sub-processes

1 Specify

2 Design

3 Build

4 Collect

5 Process

6 Analyse

7 Disseminate

8 Archive

9 Evaluate

3.3. Configure workflows

1.1. Determine needs for information

1.2 Consult and confirm needs

1.3 Establish output objectives

2.5 Design workflow

3.6 Finalize production systems

5.8 Finalize outputs

7.3 Release7.2 Produce

products7.1 Update output

system7.4 Promote

7.5 ManageUser

Support

6.5 Finalize output

6.4.Disclosure control

6.1Prepare draftoutput


PublicationCustom made

tables

6 Conventional users and dissemination

Experts/Knowledge Workers Government analysts, researchers

business institutes,

Product Custom made selection and

analyses

Public General public, journalists,

libraries, business, students

Product Basis tables, statistical reports,

yearbooks


6.1 Dissemination up to now

5 Process 6 Analyse 7 Disseminate


7.3 Release

7.2 Produce products

7.1 Update output system

7.4 Promote

7.5 Manage usersupport

6.5 Finalize output



Experts:tailored tables

Public:Publications


Reports, Evaluation

Microdata access

7 Additional new types of users and dissemination

Researcher Research projects, Universities

and scientific institutes, students, government agencies

Service Professional use of microdata for

research and analyses, use of statistic software and models

Experts/Knowledge Workers Government analysts, planner,

Institutes, associations

Service regularly updated large datasets

to support decision making, reports and analyses, database access


7.1 New processes of dissemination

5 Process 6 Analyse 7 Disseminate


7.3 Release

7.2 Produce products


7.4 Promote

7.5 Manage usersupport

6.5 Finalize output



Researchers:Access to microdata

Public:Online tables Publications

Experts:Reports online tables


7.2 Statistical Information Servicefor experts/knowledge workers

Microdatabase Automatic disclosure control of microdata Or data cubes Selection of databases/data cubes and variables Web-Interface Effective online retrieval Availability of small area statistics Display of Metadata Download in common formats Charts / maps for visualising


8 Case study: Coordinated Data Pool Berlin

5.8 Finalize data files


6.4 Apply disclosure control

5.5 Derive new variables and statistical units

Update Geographical Information System

Determine output

Subject Matter Unit Regional Statistics unit Local Authorities

State/Community Planers

Useoutput


Expert Knowledge Base: Superstar

Documents

Amt für Statistik Berlin-Brandenburg Dr. Peter LohaußState Statistical Institute Berlin-Brandenburg Q 2010 Helsinki 5. May 2010 Managing Processes in Data