Resources
Manual
Open Data Manual
The "Open Data Manual" serves as a comprehensive guide to enhance data literacy among Nepal’s youth, civil society, and private sector. It introduces open data concepts, its history in Nepal, and practical steps for working with data, including cleaning, extraction, analysis, visualization, and publishing. The manual highlights Nepal’s emerging open data ecosystem, supported by government initiatives like the Right to Information Act and civil society projects, despite challenges like non-machine-readable formats (e.g., PDFs) and the absence of formal open data policies. It emphasizes the potential of open data to drive transparency, innovation, and sustainable development, offering tools, resources, and case studies to empower users.
Key Insights
- Open Data Definition and Benefits: Open data is freely accessible, machine-readable, and reusable, promoting transparency, accountability, innovation, and civic participation. In Nepal, it supports governance, education, and development but is often restricted by non-open formats like PDFs.
- Nepal’s Open Data Ecosystem: Since 2013, Nepal's open data movement has included government, civil society, and the private sector. Initiatives like the National Action Plan on Open Government Data (2017), NepalMap, and QuakeMap demonstrate progress despite ongoing challenges.
- Policy Gaps: Nepal lacks an official open data law or centralized portal. While the Right to Information Act (2007) supports access, it does not require proactive disclosure, limiting data availability.
- Data Sources and Formats: Government data often comes from institutions like the Central Bureau of Statistics and Ministry of Finance, but in closed formats. Civil society and international portals (e.g., Open Nepal, World Bank) offer more accessible alternatives.
- Practical Workflow: The manual outlines an 8-step data workflow: brainstorming, searching, extracting, cleaning, analyzing, visualizing, storytelling, and publishing under open licenses. Tools like Python, OpenRefine, and Datawrapper are recommended.
- Data Cleaning and Quality: High-quality data must be valid, accurate, complete, consistent, and uniform. Common issues like human error and format inconsistency can be addressed using spreadsheets and OpenRefine.
- Visualization and Storytelling: Data visualization makes complex data understandable and engaging. Tools like Datawrapper and Tableau Public are essential for crafting visual narratives that aid development planning and decision-making.
- Publishing and Licensing: Open data should be shared in machine-readable formats (e.g., CSV, JSON) under open licenses like Creative Commons. In the absence of a national portal, data is distributed via websites, cloud platforms, or civil society portals such as Open Nepal Data Portal.
