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From community data to global action: strengthening the use of Citizen Science data for sustainable development

Sponsoring Organization

Citizen Science Global Partnership (CSGP)

Organization

Global Network of Citizen Science Networks

Supporting Organization(s)

CSGP’s national and regional CS associations and collaborating partners

Data Type
Citizen data Monitoring and evaluation Data for SDG monitoring
Region

Global

Objective

CSGP commits to strengthening the recognition and responsible use of Citizen Science data in sustainability monitoring and decision making. A global network-of-networks, CSGP will connect community producing data with national, regional and international data users, including public authorities, statistical institutions and international organisations. It will identify and communicate examples showing where Citizen Science data can address evidence gaps, complement established data sources and provide insights into local conditions. CSGP will also promote practical exchange on data quality, openness, accessibility and responsible governance, while supporting organisations from underrepresented regions to participate in these discussions. The objective is to create clearer and more equitable pathways through which community-generated evidence can inform policy and contribute to progress towards the SDGs.

Description:
What problem is this commitment aiming to solve?

Citizen Science communities worldwide collect valuable data on air quality, biodiversity, climate, health and other sustainability challenges. Yet these data often remain confined to individual projects and are not sufficiently visible, understood or used by public authorities and international organisations. Data producers may lack opportunities to demonstrate their value, while policymakers may be uncertain about their quality, relevance and appropriate use. These barriers are particularly significant for grassroots initiatives and organisations in underrepresented regions, which often have limited access to technical support, partnerships and global policy processes. As a result, Citizen Science data that could fill evidence gaps, complement official sources and reveal local inequalities are frequently overlooked. Stronger connections are needed between communities that produce data and the institutions that can use them for sustainable-development monitoring, environmental action and public decision-making. 

Briefly describe the commitment including key activities, strategies and intended outcomes.

The intended outcomes are greater visibility and use of Citizen Science data, stronger partnerships between data producers and users, improved capacity to produce policy-relevant data, and more inclusive data systems that recognise communities as active contributors.

CSGP will:

  • identify and document Citizen Science initiatives addressing sustainability challenges across different regions;
  • develop a portfolio of cases demonstrating how Citizen Science data fill gaps, complement other sources or support policy action;
  • convene exchanges between Citizen Science organisations, public authorities, statistical institutions and international organisations;
  • support thematic communities working with data on areas such as air quality and climate action;
  • share practical lessons on data quality, accessibility, openness, responsible use and community participation;
  • enable organisations from underrepresented regions to present their data, needs and experience in international forums; and
  • advocate for appropriate recognition of Citizen Science data in sustainability monitoring and policy processes.
Describe how you will monitor progress and evaluate the success of this commitment?

Progress could be monitored through:

  • Number, regional distribution and SDG areas of initiatives and case studies documented (e.g. featured on the website);
  • dialogues or collaborations established with statistical institutions, public authorities and international organisations;
  • examples of Citizen Science data being accessed, assessed, combined with other sources or used in decisions-making;
  • guidance, recommendations and learning resources produced
Timeline
The commitment would run from 2027 to 2030, aligning with the timeframe recommended by Commit to Data and the SDGs.
Contact Person
Maria Rosa Mondardini maria.mondardini@uzh.ch