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While stakeholder-driven approaches have been increasingly used in scenario modeling, previous studies have mostly focused on the qualitative elements, e.g., narratives and policy documents, from the stakeholders, but lack engagement of stakeholders with quantitative inputs. In this study, we conducted workshops with a stakeholder group to integrate the participatory mapping of future policies in the simulation, and to compare the environmental impacts after including the participatory mapping. A land system change model named CLUMondo was used to simulate four scenarios, i.e., Business-As-Usual (BAU), Destroying Resources in Owyhee (DRO), Ecological Conservation (EC), and Managed Recreation (MR), in Owyhee County, Idaho, United States. The InVEST models were used to assess water yield, soil erosion, and wildlife habitat under the four scenarios. The results show that the DRO scenario would decrease shrubland and increased grassland, thus leading to less water yield, more soil erosion, and deteriorated wildlife habitat anticipated through to 2050. On the contrary, the EC and MR scenarios reverse the trend and would improve these ecosystem services over the same time horizon. The stakeholder-driven policies appear to influence the spatial distribution of the land system and ecosystem services. The results help to reach a nuanced understanding of the stakeholder-driven scenarios and highlight the importance of engaging stakeholders in scenario modeling and environmental impact analysis.
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This content will become publicly available on June 22, 2026
ONION: A Multi-Layered Framework for Participatory ER Design
We present ONION, a multi-layered framework for participatory Entity-Relationship (ER) modeling that integrates insights from design justice, participatory AI, and conceptual modeling. ONION introduces a five-stage methodology: Observe, Nurture, Integrate, Optimize, Normalize. It supports progressive abstraction from unstructured stakeholder input to structured ER diagrams. Our approach aims to reduce designer bias, promote inclusive participation, and increase transparency through the modeling process. We evaluate ONION through real-world workshops focused on sociotechnical systems in Ukraine, highlighting how diverse stakeholder engagement leads to richer data models and deeper mutual understanding. Early results demonstrate ONION ’s potential to host diversity in early-stage data modeling. We conclude with lessons learned, limitations and challenges involved in scaling and refining the framework for broader adoption.
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- PAR ID:
- 10614530
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400719592
- Page Range / eLocation ID:
- 1 to 7
- Format(s):
- Medium: X
- Location:
- Berlin, Germany
- Sponsoring Org:
- National Science Foundation
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