UNESCWA-政府开放数据工具包（英文）-2021.4-50页_1006kb

Summary of the Open Government Open Data Toolkit

Core Content

The Open Government Open Data Toolkit is a comprehensive guide designed to support the planning, implementation, and sustainability of open data initiatives in the Arab region. It is developed by ESCWA (Economic and Social Commission for Western Asia) with the aim of aligning with the 2030 Agenda for Sustainable Development. The toolkit is informed by global best practices and references, including the United Nations Development Programme (UNDP), the Partnership for Open Data, the European Data Portal, and successful open data programmes from the UK, Australia, and other countries.

The toolkit outlines a structured approach to open data management, consisting of four main phases: Preliminary, Development, Roll-out, and Standard Practice. Each phase includes specific key tasks that organizations should undertake to ensure the successful launch and long-term maintenance of open data programmes.

Main Phases and Key Tasks

1. Preliminary Phase

• Conduct a baseline data maturity assessment.
• Develop the open data strategy, which should be:
  • Open and collaborative, involving all stakeholders.
  • Engaging, allowing public input.
  • Aligned with national and organizational goals.
• Define the strategic vision, objectives, stakeholders, and principles.
• Establish metrics to measure progress.

2. Development Phase

• Develop the open data policy, which should:
  • Outline the organization's commitment to open data.
  • Define the scope, purpose, and governance of the open data initiative.
  • Include data selection, licensing, privacy, and quality standards.
• Create a central open data team with roles such as:
  • Programme Sponsor
  • Chief Data Officer
  • Legal Advisor
  • Portal/IT Manager
  • Subject Matter Expert
  • Coordinator
  • Data Publisher
• Develop a training programme to build capacity and ensure a culture of open data.

3. Roll-out Phase

• Publish more high-value datasets.
• Improve internal and external organizational capacity.
• Promote the use of open data through:
  • Improved prioritization and release processes.
  • Handling complex cases like privacy and anonymization.
  • Enhancing the open data portal with new features.
  • Organizing developer events such as hackathons.
  • Conducting data innovation challenges and competitions.

4. Standard Practice Phase

• Ensure open data publication and updates are part of standard government procedures.
• Maintain a smaller but effective open data team to monitor and update standards and processes.
• Continue publishing datasets in line with priorities and user needs.
• Regularly evaluate the programme to identify progress and areas for improvement.
• Sustain engagement with both internal and external data users.

Open Data Inventories and Catalogues

The toolkit provides a four-phase approach for creating and maintaining open data inventories and catalogues:

Phase 1: Prepare a Master List of High-Value Datasets

• Identify datasets that are likely to have a significant impact when released.
• Examples of high-value datasets include:
  • Education: Provider performance, locations, sanitation data.
  • Health Care: Provider locations, services offered, quality and performance.
  • Transport: Timetables, locations, traffic flow data.
  • Environment: Weather, pollution, soil data, cadastral maps.
  • Sanitation and Waste: Disposal sites, toilet facilities.
  • Governance: Election locations, results, financial transactions.
  • Economy and Business: Budget data, company registers.

Phase 2: Classify Datasets in the Master List

• Classify datasets according to their relevance, value, and readiness for release.
• Aim for openness by default, with clear criteria for classification.

Phase 3: Release Datasets to the Open Data Catalogue

• Publish datasets from the inventory to the open data catalogue.
• Ensure the data is released in accordance with the policy and standards.

Phase 4: Update the Inventory and Catalogue

• Maintain and update the inventory and catalogue regularly based on feedback and changing needs.

Key Features of Open Data Platforms

The toolkit recommends three main options for open data platforms:

• Online Download: Direct access to datasets.
• Data Portal: A centralized platform for data publication and access.
• Application Programming Interfaces (APIs): Enable programmatic access to data.

Key features of open data platforms include:

• User-friendly interfaces.
• Search and tagging capabilities.
• Metadata support.
• Accessibility and interoperability.
• Scalability and sustainability.

Evaluation of Open Data Programmes

The evaluation process is structured into five steps:

1. Initiation: Launch the programme and secure support.
2. Evaluation of Readiness: Assess the organization's preparedness.
3. Evaluation of Publishing: Review the quality and consistency of published data.
4. Evaluation of Impact: Measure the effect of open data on society and governance.
5. Gaps and Action Plan Report: Identify gaps and outline a plan for improvement.

Open Data Quality

Open data quality is evaluated through four criteria:

• Legal: Compliance with licensing and privacy laws.
• Practical: Feasibility of data release and management.
• Technical: Use of open formats and metadata standards.
• Social: Engagement with users and impact on public participation.

A quality assurance process is recommended to ensure all these criteria are met.

Conclusion

The toolkit emphasizes the importance of a structured, phased approach to open data management, starting with strategic planning and ending with the establishment of standard practices. It also highlights the need for collaboration, transparency, and continuous improvement. By following these guidelines, governments can enhance public engagement, improve service delivery, and promote innovation through the effective use of open data.