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WALIS Data Management Workshop

29th May, 2001

Olive Farm Function Centre, South Guildford

Over 70 participants, from State Government and local government agencies, attended the one day WALIS Data Management. The workshop consisted of a number of presentations and group sessions that were designed to explore a series of data management issues including: the life cycle of data, project planning and user needs, standards, legislative requirements, custodianship, data documentation (metadata), quality assurance and data auditing.

The key theme of the workshop was that the costs of data acquisition are often the most significant costs incurred by an organisation and a well-managed dataset is significantly more valuable than a poorly managed one. This makes data management critically important for any organisation; and the challenge of how to manage data is a formidable one. This challenge must be met, as sound decisions can only be made on the basis of current, correct and complete knowledge. Good data management provides the foundation for an effective information system. An effective information system capitalises on the advantages offered by information technologies. The research that has been performed to-date indicates that formal (written) data management plans are becoming a popular means of encouraging good data management practice.

OUTCOMES

The workshop and future seminars are designed to assist in the development of WALIS Data Management Guidelines to be used by WALIS agencies to maximise the benefit of their information resources.

A number of specific issues were identified at the workshop warranting further discussion at future seminars. Various helpful hints were also identified and which will be included in the WALIS Data Management Guidelines.

The output from the workshop will now be reviewed by the WALIS Access Group to assist in the development of the Guidelines and example processes of data management techniques.

WORKSHOP ISSUES AND HELPFUL HINTS

Managing the Data Life Cycle

1. Setting Objectives

Choose parts of dataset where there is strong demand

Start with your budget resources in mind but don't limit important objectives

Break a dataset down to its parts and work on each part (eg vegetation - flora)

Have a long term development plan but focus on aspects that can achieve short term results, acceptance and help longer term

Specify data and your major users

Close link to strategic objectives

2. Communication

Focus on your major users and communicate with them

Liaise with the people who already collect the data (data management is a tool for the whole organisation, not just the manager)

Liaise with users to monitor current processes and identify opportunities for processes and results

Liaise with those interpreting data to ensure correct outputs

3. Documentation

Review processes, record current practices and capture points for possible improvements

Go once quickly through whole life cycle then repeat review in detail

Aim for a planning process not just a plan

Detail names of people who have skills in areas in addition to key processes (ie include knowledge management - personalise and codify)

Specify data so it meets its objectives

Fit your language to domain language

4. Process

Cycle back to test feasibility of meeting objectives

Validate data close to its source

Ensure quality control is managed by someone other than the author

Make sure classification systems work (ie use comprehensive and agreed classifications)

5. Metadata

To ensure improved metadata documentation practices, agencies should consider

Give the user what they require and will use

Use standards that exist, don't reinvent

Develop a workable plan to collect the metadata (ie Metadata Monday)

Capture as you create, don't wait till the data is being stored to document all metadata

Educate and train users on capturing effective metadata

Audit metadata to ensure consistency

NEXT STEPS

Maintain WALIS website with updated progress in development of data management guidelines and examples

Coordinate briefings for WALIS Agencies on new State Records legislation

Track new technologies (ie ISO, OpenGIS, XML)

Review other planning strategies (ie asset management techniques) to assist development of data management guidelines

Investigate users requirements and common specifications for potential development of WALIS metadata management tool (including assessment of current MET use)

Regulate WALIS metadata transfer format (ie XML)