Table 2 Requirements for a successful implementation of a national/regional/global geo-information infrastructure. Summary of the recipes and main recommendations provided by various specialist groups and researchers from around the world for a successful implementation of a national/regional/global geo-information infrastructure that can also support real-time GIS public health applications.

• Vision and leadership at the highest levels (e.g., departments of health)

• Official/governmental support

• Fostering a culture of data sharing and joined-up working at all levels (local to global) that considers spatial information an asset

• Raising awareness activities and campaigns; reaching out to policy and strategy makers in the health and other sectors

• Policies and practices actively promoting the exchange and reuse of geo-information, and greater public access to it

• Education, training, and capacity building

Resources and ICT infrastructures

• Appropriate human, financial and technical resources

• Providing support to organisations lacking the necessary resources to join in common, coherent national/regional/global initiatives

• Adequate information telecommunications technology infrastructures and bandwidth

• Moving to the Web and building all necessary critical connectivity/geospatial infrastructure that should not be independently recreated by all

Data security and confidentiality issues

• Developing unambiguous legal frameworks and policies, as well as suitable technical solutions to address the crucial issues of individual privacy, national security, and data confidentiality

• Adequate protection measures of networked geo-information assets against cyber terrorism

Data and standards issues

• Up-to-date and accurate core digital geo-datasets

• National data utilities/services (industry standard services that are independent of any particular user interface)

• Standardised metadata in centralised catalogues or clearinghouses

• Adopting common standards to address integration and interoperability issues (GML and other technologies; health-related standards)

• Automated geocoding

• Automated conflation of geospatial databases

Data use and applications issues

• Do not just focus on data; develop applications

• Adopting common semantics, data models (ontologies) and health indicators; the latter should also cover population demographics and socio-economic factors

• A deep understanding of data and industry; reaching a consensus on the inputs and outputs in different health and healthcare applications

• Developing increased sensitivity to and awareness of data problems and errors, as well as competency in techniques for recognising and reducing their negative impact on conclusions drawn from spatial analysis

• Appropriate and robust statistical and epidemiological methods must be used to avoid the consequences of visual bias and various data problems in GIS processes

• Seamless integration into routine workflows of intelligent software tools that are easy-to-use by mainstream public health practitioners, and which allow only valid visualisations and analyses of data from a variety of sources across space and time

• User interface accessibility requirements

Interdisciplinary collaboration and partnerships

• Development of effective partnerships (including community/academia collaboration), and involvement of and coordination between all stakeholders and users

• Community data sharing must be systematic, uniform and regular, and governed by adequate data-sharing agreements

• Building interdisciplinary teams with expertise in public health and epidemiology, medical informatics, medical statistics, health economics, computer science, law, and engineering

• Other important points: joint ownership of projects by their respective stakeholders; shared commitment; having realistic expectations

General approaches

• A combined top-down and bottom-up incremental implementation approach

• Assessing current state of geospatial readiness to respond to normal and emergency community health needs, and identifying beacon sites as examples to follow

• Fault tolerance at all levels (hardware and software)

• Full systems redundancy, and standardised database replication measures and off-site backups (these are also important aspects of data security)