ASC Conference

1
IQML A Software Suite and Extended Mark-Up
Language (XML) for Intelligent Questionnaires

• Joanne Lamb
• Joan Fairgrieve
• CES, University of Edinburgh

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Overview

• What is IQML
• Aims and Objectives
• Standards
• Questionnaire Design

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What is IQML

• EU project funded by IST programme
• CPA4 - Statistical Tools
• Seven partners
• Five modules
• Common back bone
• http//www.cordis.lu/ist/projects/99-10338.htm
• http//www.epros.ed.ac.uk/iqml (end of the month)

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The Partners

• University of Edinburgh, UK
• Statistisk sentralbyraa, Norway
• Central Statistics Office, Ireland
• National Technical University of Athens, Greece
• Desan Marktonderzoek BV, Netherlands
• Dimension EDI Ltd, UK
• Comfact AB, Sweden

5
The modules

• Metadata maintenance and repository (MMR)
• support the definition of metadata objects, such
  as codes, tables, questions etc.
• APIs will be developed to store and access these
  metadata objects
• The Questionnaire Designer (QD)
• enable the user to design and manage
  questionnaires
• allow the user to define questionnaires at a
  number of levels conceptual, logical, and formal
• interface for other questionnaire depositories
• to re-render the questionnaires into the XML
  format
• capture all relevant metadata and store it in the
  metadata repository

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The modules

• The Questionnaire Presentation Tool (QP)
• render the questionnaire for use with PCs and in
  particular with web browsers
• XML support for the presentation, validation,
  navigation and calculation
• The Database Interrogation Tool (DI)
• support the extraction of data from popular
  databases
• allow data to be extracted from XML and loaded
  into a database
• The Survey Administration Package (SA)
• questionnaires integrated with registers and
  sample frames
• track the despatch and receipts of questionnaires
  and software to individuals and organisations

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The modules and their users
Survey
Response
QD
QP
Questionnaire Designer
Individual or corporate
MMR
SA
DI
Survey Manager
Corporate
Co. DB
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Aims and Objectives

• To improve the accuracy and timeliness of
  statistical data collection
• from enterprises and individuals
• To reduce the burden of statistical reporting on
  enterprises
• How?
• By developing these tools
• By contributing to standards

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Standards

• Contribution to the Common Warehouse Metadata
  Interchange (CWMI) of the OMG
• Participating in a number of accompanying
  measures activities around the FP5 project
• Focusing on metadata in and from data collection
• XML is used for a realisation of the model

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What is CWMI

• GoalsEstablish an industry standard
  specification for common warehouse metadata
  interchangeProvide a generic mechanism that can
  be used to transfer a variety of warehouse
  metadata

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CWM Joint Submission Team

• IBM (Dan Chang, J. J. Daudenarde, Debra LaVergne)
• Unisys (Don Baisley, Sridhar Iyengar, Doug
  Tolbert)
• NCR (Bruce McLean, Vihelm Rosenqvist)
• Hyperion (John Poole)
• Oracle (David Last, David Mellor)
• UBS (Hans-Peter Hoidn, Jeffrey Peckham)
• Genesis (David Frankel, Phil Longden)
• Dimension EDI (Chris Nelson, Anders Tornqvist)
• IQML partners

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Data Warehouse Lifecycle
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The Questionnaire Design module

• CES is developing the Questionnaire Design Module
• What automation can we achieve?
• Intelligent Questionnaires? How?
• Use existing question banks
• Use prior knowledge of samples
• Define routing
• Perform calculations on responses

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General Advantages

• For the Survey Manager
• standard set of items relevant for further action
  in the statistical process
• standardised way of exchanging
• possibility of specifying background
  information to be captured during the QD process
• storage facilities for re-use and archiving
• interface with Survey Administration
• For the analyst
• access to the original questionnaire
• explanations of coding and routing assumptions
• background information

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Advantages for the designer

• a GUI front end
• remembers all information supplied
• interfaces with several media - CAPI, CATI,
  paper, internet
• access to questions banks

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Capturing metadata

• As much metadata as possible will be created
  automatically by the system (e.g. question type
  and format can be used to generate data
  definitions)
• Metadata that cannot be created automatically
  will be collected in a user-friendly way at the
  appropriate time in the survey process from the
  appropriate user

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Implications for designers

• XML, standards etc. will be invisible to users
• The Questionnaire designer will not be expected
  to act as a programmer
• The metadata for repository captured as part of
  flow through survey process

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Conclusions

• Metadata has been under discussion for many years
• But capturing it is a problem!!
• Two changes bring it back to the foreground
• XML eases the exchange mechanism
• and tools are available to interface between XML
  and databases
• Dissemination issues make it more visible
• of datasets for re-use
• via the Web
• Other application areas are interested
• But we still need work on metadata for surveys
  and statistics