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This study proposes a generative scenario-based methodology to improve planning and decision support systems that help policymakers in a given urban context, to imagine futures, to advance towards integrating government functions, and to identify pathways to get there. To demonstrate the same, we developed a scenario-based simulation platform, named ‘Simulogue’. The tool is set in Chennai, India, and is designed as a platform for integrated governance through a facilitated dialogue between various stakeholders involved with governing Chennai. The dialogue is based on various future scenarios that each stakeholder develops and is able to negotiate with their peers. A futures-based approach helps to improve decision-making by (i) facilitating the integration of diverse public institutions and collaboration between stakeholders by defining specific goals and evaluation parameters by stakeholders themselves and (ii) incorporating intangible data with regards their interaction and decision-making into the decision support system. Scenario-based planning enables stakeholders to explore different situations they would like to plan for. It enables them to articulate their goals and constraints with respect to the functions they perform. As a result, planning outcomes can be designed that stem from policymakers themselves. To be able to do so accurately, we must capture all relevant data such as data on resource-access, control, regulation and use as well as qualitative data on interaction amongst stakeholders. Through a combination of stakeholder-led workshops and developing an agent-based simulation tool, we bring together data, people, processes and constraints, presented in the form of future scenarios that policymakers must identify and work towards.
", "publication_date": "2019-05-20", "publisher": "Zenodo", "resource_type": { "id": "publication-conferencepaper", "title": { "de": "Konferenzbeitrag", "en": "Conference paper" } }, "rights": [ { "description": { "en": "The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited." }, "icon": "cc-by-icon", "id": "cc-by-4.0", "props": { "scheme": "spdx", "url": "https://creativecommons.org/licenses/by/4.0/legalcode" }, "title": { "en": "Creative Commons Attribution 4.0 International" } } ], "subjects": [ { "subject": "Decision-support" }, { "subject": "Scenario-based" }, { "subject": "Integrated-governance" }, { "subject": "Simulation-platform" }, { "subject": "Generative" } ], "title": "Imagining Futures \u2013 A generative scenario-based methodology to improve planning and decision-support systems for policymakers" }, "parent": { "access": { "owned_by": { "user": 67811 } }, "communities": { "default": "daa9c7bc-7c9e-49e6-9b5f-8032586c6a55", "entries": [ { "access": { "member_policy": "open", "members_visibility": "public", "record_policy": "open", "review_policy": "open", "visibility": "public" }, "children": { "allow": false }, "created": "2017-04-11T13:44:03.516801+00:00", "custom_fields": {}, "deletion_status": { "is_deleted": false, "status": "P" }, "id": "daa9c7bc-7c9e-49e6-9b5f-8032586c6a55", "links": {}, "metadata": { "curation_policy": "This page publishes discussion papers and other materials which have been presented at Data for Policy conferences. Only members of the Data for Policy team may upload materials pertaining to the conference series at any time.
\r\n", "page": "A community for sharing discussion papers presented at Data for Policy conferences. Data for Policy is an international conference series dedicated to exploring the interface between Data Science and Government Policy with input from top academic institutions, government departments, international organisations and other key stakeholders in the non-profit and commercial sectors.
\r\n\r\nWebsite: http://dataforpolicy.org/
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