MODULE 2 - NPSI

1 Capacity to implement natural resources information management 2: data management PrinciplesMODULE 2 Promoting Best Practice in Spatial data and Information management MODULE 2: data management principles Page i Table of Contents Guide for managers .. ii Context ..ii Actions .. ii Acknowledgements .. iii Guide to symbols .. iv Introduction 1 What is data management ?.. 1 principles .. 1 Why do we need to manage data ? 2 File naming conventions and directory structure .. 2 Key drivers for improved data 4 Statutory requirements for data and information management .. 4 Benefits of good data management .. 5 principles of good data management 6 data policy.

2 6 data 6 data documentation and metadata compilation .. 7 data quality, standardisation, harmonisation and audit .. 7 data life-cycle control .. 8 data 8 data access and 9 Establishing a data policy 9 data acquisition .. 9 Fitness for purpose and point of 10 data care (custodial duties) .. 10 data use and exchange .. 11 Implementing data management key roles and responsibilities 11 data management champion .. 11 data policy manager .. 12 data 12 Additional support 13 Glossary 14 Attachment 2 1 data cleansing approach of Glenorchy City Council 15 What is data cleansing? .. 16 Product Number: PN21205 ISBN: 978-0-642-37155-3 Promoting Best Practice in Spatial data and Information management MODULE 2: data management principles Page ii Guide for managers Context All agencies, departments and resource centres collect, create, store and utilise data in some form most of which has been obtained at considerable cost.

3 It has been estimated that 90 per cent of the costs of establishing a GIS can be attributed to the development of the thematic datasets, and that in excess of 80 per cent of all data have some geographical components and can therefore be referenced to geographical locations such as points, lines or areas. Experience reveals that treating data as long-term assets and managing them within a coordinated framework produces considerable savings and ongoing value. Most jurisdictions throughout Australia have established policies governing access and use of data and information, along with custodianship guidelines and information management strategies. Proper processes and procedures for data and information management are the foundation of an efficient management system.

4 This guide provides background information on best practice for managing data as assets and valued resources. The primary audience is those responsible for managing spatial data and information, although the principles described are equally applicable to other types of data . Policies and procedures are required to guide the transition from tactical, project-based data collection and management to a strategic information infrastructure that will inform decision making on a wide range of issues. In many situations data are incomplete, not easily accessible, not up-to-date, and often lack any documentation on accuracy and reliability. As such, utilising the data outside of the immediate discipline or agency that collected them can be difficult.

5 MODULE 2: data management principles provides a framework within which the activities of data collectors, managers and information providers can be integrated. If organisational management is convinced that the tangible benefits from investing in data management outweigh the costs, then it will be given the priority it requires. Actions Managers should focus on the need to achieve an integrated information management solution. Such a solution would successfully combine leadership, people, computer hardware and software applications and data into a framework ensuring the appropriate tools and rules are in place to maintain the data and turn them into useful information products in support of operations and decision making.

6 The goal will be achieved through the formalisation of an infrastructure, production of guidelines, and the development of standards and procedures to support data management and processing. Managers should facilitate the development and implementation of a data policy which addresses the following key elements: Promoting Best Practice in Spatial data and Information management MODULE 2: data management principles Page iii creation of an easily accessible data system which can efficiently disseminate data collected as part of project activities to the widest range of users development of core datasets as baseline products provision of best practice quality assurance mechanisms and procedures to produce validated.

7 Well-documented datasets that meet priority information requirements archiving of all data collected to ensure their availability for multiple use and to safeguard the investment for future use improvement of the effectiveness and efficiencies of policy and program development through the coordination of data and information activities provision of timely and up-to-date data and information products to support a wide range of activities. Acknowledgements This MODULE draws heavily on material produced by the UK Intra-governmental Group on Geographic Information working group on principles and Practice of Geographic Information data management . The source of this material is duly acknowledged.

8 Promoting Best Practice in Spatial data and Information management MODULE 2: data management principles Page iv Guide to symbols The following symbols are used throughout the Toolkit as a guide to users, and draw attention to important issues and information. Information which readers should take particular note of Best practice information Tips for readers based on experience and aimed at saving time and resources Caution readers are advised that particular care should be taken or that the subject issue may be complex Additional information Capability raising used to show a signpost to a higher capability level Bold Text Used to highlight a particular issue Boxed Text Highlighting of issues specifically related to ANZLIC or the Audit Promoting Best Practice in Spatial data and Information management MODULE 2: data management principles Page 1 Introduction What is data management ?

9 This document addresses the key aspects of data management giving consideration to the following guiding principles : Don t re-invent the information management wheel. Where possible capture data once for multiple/generic use. Avoid duplication in data acquisition share and co-operate wherever possible. Use existing systems/facilities wherever possible. Manage data to maximise their value both during and after the project that they were collected for. Give priority to the broadest value data of benefit to multiple processes. Develop and implement metadata standards and documentation procedures. Where possible develop and implement (or adopt existing) data publishing standards. Contribute to long-term strategic goals for data and information management Select the most robust organisation with the broadest span of interest as the most appropriate custodian of high-value general use information.

10 Reinforce and support data custodians and where possible negotiate access. Guiding principles The term data management embraces the full spectrum of activities involved in handling data , including: data policy data ownership data documentation and metadata compilation data quality, standardisation, harmonisation and audit data life-cycle control data custodianship data security and access constraints data access, data sharing and dissemination/licensing arrangements data publishing. 1 2 Individual people or departments have documented data management processes, policies and procedures. Use the sections in MODULE 2 as a guide to link the documentation of processes, policies and procedures to actual business processes within an NRM region.