/Management

https://opengeoscales.github.io/Management/

Welcome to OpenGeoScales 👋

Unlocking Climate Change Data & Knowledge

License: MIT

Short presentation

OpenGeoScales is a collaborative open data platform providing free access to qualified, harmonized and normalized geospatial open data sources and analytics on various scales. OpenGeoScales adress environmental topics and it aims at providing certified data and accesible knowledge in climate change issues: GHG emissions, energy, natural hazards, pollution, deforastation, waste...

Why?

  • Environmental issues: Increasing interest in environmental issues --> Need for reliable environmental open data, aggregated indicators and open source analytics reports.
  • Open data & collaborative analytics: Increasing open data providers, platforms and portals --> Lack of platforms providing clean and normalized geospatial data with transparent access to implemented treatments
  • City/community scale: Increasing interest of local policymakers in climate impacts in city/community scale --> Rare data is provided in small scale

Goal

Empower citizens, governments, NGOs, academia, companies and investors with reliable open geo-spatial data and open source analytics to address city-level climate change impacts.

Key concepts:

  • Environmental issues: climate change, natural hazards, air quality, GHG emissions, energy, pollution
  • Openness: open data, open source
  • Community: collaborative work, open source community
  • Geospatial data
  • Geographical scales: country, city, grid

How?

1 - Identify climate change related topics with potential interested persons/users/organizations in accruate and relevant data and analytics (e.g. GHG emissions)

2 - List a set of questions to answer by synthesizing various source of knwoledge (e.g. What are GHG emissions? How ghg emissions are measured? How GHG emissions data are collected? By whom? Why is it inmportant to reduce our emissions? What are the more impactful sectors?...)

3 - Implement adhoc analytics: identifying data sources, analyzing data sources, defining normalized data models, defining data processing to clean/normalize raw data...

4 - Industrialize data pipelines: data collection, ingestion, processing, cleaned data storage

5 - Implement analytics reports based on the cleaned and harmonized database in order to answer the defined questions

6 - Develop interactive dashboards to visualize the aggeragted data

7 - Develop APIs to expose cleaned from built databases

8 - Get users feedbacks to identify improvements and further analysis

Topics

  • GHG emissions: City GHG emissions (evolution, comparative study, emissions by sector…)
  • climate hazards: City exposure to climate hazards impact, vulnerability index, climate hazards events
  • Air quality: Air quality index in city level
  • Mobility: Transportation related emissions, transportation modes...
  • Energy: Energy mix, percent of renewable energy
  • Land use: Urban development, deforestation...
  • Society: Demographics, urban population...

target users

  • Citizens
  • Governments: policy makers, local authorities
  • NGOs: World Resources Institute, Carbon Disclosure Project, The Shift Project, C40 cities, Our world in data…
  • Academia: Researchers, students
  • Journalists: Data journalism
  • Data professionals

Inspired by

  • Open data
    • Our world in Data
    • World Resources Institute: Climate Watch
    • Open Data Institute
  • Collaborative data tools:
  • Made with ML

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License

Acknowledgements