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Mapping Knowledge and Gaps in Data, Transparency, and Capacity Building Practices in the Mekong Region
USAID Mekong for the Future (MFF) commissioned the East-West Management Institute’s Open Development Initiative (ODI) to map the data ecosystem in Cambodia, Lao People’s Democratic Republic (Lao PDR), Myanmar, and Thailand—collectively referred to here as the Mekong region—with the purpose of making recommendations to support CSOs in the region to engage with environmental governance and environmental data. Research was conducted from December 2021 – May 2022.
This process revealed three broad themes and several cross-cutting issues that impact the environmental data ecosystem in the Mekong Region: • Persistent knowledge gaps related to what data are available, where to find it, and how to use it; • A lack of diversity and inclusion in the data ecosystem, including the exclusion of Indigenous and other marginalized communities’ knowledge in existing datasets; and • Limited access to data due to gate-keeping, infrastructure and tool limitations, and safety and security challenges.
Additional Information
| Field | Value |
|---|---|
| Last updated | 2023၊ 27 ဇွန် |
| Created | 2023၊ 27 ဇွန် |
| ပုံစံ | |
| လိုင်စင် | Creative Commons Attribution Share-Alike |
| အမည် | Mapping Knowledge and Gaps in Data, Transparency, and Capacity Building Practices in the Mekong Region |
| ဖော်ပြချက် |
USAID Mekong for the Future (MFF) commissioned the East-West Management Institute’s Open Development Initiative (ODI) to map the data ecosystem in Cambodia, Lao People’s Democratic Republic (Lao PDR), Myanmar, and Thailand—collectively referred to here as the Mekong region—with the purpose of making recommendations to support CSOs in the region to engage with environmental governance and environmental data. Research was conducted from December 2021 – May 2022. This process revealed three broad themes and several cross-cutting issues that impact the environmental data ecosystem in the Mekong Region: • Persistent knowledge gaps related to what data are available, where to find it, and how to use it; • A lack of diversity and inclusion in the data ecosystem, including the exclusion of Indigenous and other marginalized communities’ knowledge in existing datasets; and • Limited access to data due to gate-keeping, infrastructure and tool limitations, and safety and security challenges. |
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