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  "author": "",
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  "author": "",
            
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  "author_email": "Amin Kiaghadi",
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  "author_email": "Amin Kiaghadi",
            
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  "creator_user_id": "a21a024c-343c-4b53-a214-49d6fe62a720",
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  "creator_user_id": "a21a024c-343c-4b53-a214-49d6fe62a720",
            
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  "groups": [],
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  "groups": [
            
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    {
            
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      "description": "The Smart & Connected Communities project 
            
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focuses on improving resilience in communities facing extreme weather 
            
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events and chronic stressors. \r\n\r\nIt aims to create a secure 
            
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online portal where residents can share their local knowledge about 
            
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these challenges. Researchers will work with the community to 
            
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integrate this local knowledge with existing data sets used for 
            
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planning and disaster preparation. The project not only enhances 
            
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community resilience but also contributes to the national interest by 
            
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providing a model that other communities can adapt. It involves 
            
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creating innovative tools, data privacy processes, and knowledge 
            
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integration frameworks, promoting local expertise in decision-making, 
            
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and enhancing computer-based modeling for better resilience and 
            
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preparedness.\r\n\r\nPrinciple Funder: National Science Foundation 
            
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Smart & Connected Communities (Award No. 2127353)",
            
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      "display_name": "Texas: Central Region",
            
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      "id": "bf53a48a-8ca5-4a0f-9772-daf4bf460f16",
            
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      "image_display_url": 
            
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      "name": "central-texas-region",
            
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      "title": "Texas: Central Region"
            
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    },
            
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    {
            
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      "description": "The Smart & Connected Communities project 
            
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focuses on improving resilience in communities facing extreme weather 
            
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events and chronic stressors. It aims to create a secure online portal 
            
32
where residents can share their local knowledge about these 
            
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challenges. Researchers will work with the community to integrate this 
            
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local knowledge with existing data sets used for planning and disaster 
            
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preparation. The project not only enhances community resilience but 
            
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also contributes to the national interest by providing a model that 
            
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other communities can adapt. It involves creating innovative tools, 
            
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data privacy processes, and knowledge integration frameworks, 
            
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promoting local expertise in decision-making, and enhancing 
            
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computer-based modeling for better resilience and 
            
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preparedness.\r\n\r\nPrinciple Funder: National Science Foundation 
            
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Smart & Connected Communities (Award No. 2127353)",
            
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      "display_name": "Texas: Rio Grande Valley Region",
            
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      "id": "06257bd5-3ba2-47dd-ba84-ad3a83092297",
            
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      "image_display_url": 
            
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exas.edu/uploads/group/2025-06-27-031854.161623BeulahModelScreen.png",
            
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      "name": "rgv",
            
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      "title": "Texas: Rio Grande Valley Region"
            
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    },
            
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    {
            
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      "description": "Core infrastructure for a reusable Knowledge 
            
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Management Platform. Research and develop scalable decision support 
            
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and deep uncertainty cybertools. How: Collaborate with research team 
            
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to design and implement services that support data and model 
            
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management and extend CI and DSS approaches that will be sustained via 
            
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leveraged efforts with other initiatives, like TDIS, DOLCE, MINT, etc. 
            
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Research Focus (RF's) to develop advanced decision support tools that 
            
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address: * RF1 - knowledge capture for sensed and unstructured 
            
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information,  * RF2 \u2013 develop reusable analytical methods that 
            
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use natural language processing to computationally deconstruct problem 
            
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formulations and link data/models with decision problems. * RF3 \u2013 
            
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explore and design methods and utilities that support a standardized 
            
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use of methods for decision making under deep uncertainty. 
            
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Implementation Science to support stakeholder community needs and act 
            
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as a learning laboratory for Intelligent Systems and IFL 
            
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researchers\r\n\r\nPrinciple Funder: Planet Texas 2050",
            
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      "display_name": "Texas: Southeast Region",
            
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      "id": "fc1a600d-1f56-421b-9f8a-8deca201ff03",
            
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      "image_display_url": 
            
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oup/2025-02-21-163737.483713Screenshot-2025-02-21-at-10.37.15-AM.png",
            
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      "name": "setx",
            
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      "title": "Texas: Southeast Region"
            
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    },
            
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    {
            
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      "description": "",
            
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      "display_name": "Texas: Statewide Subsidence Data",
            
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      "id": "92969cee-3dfc-4a30-8b77-a551b06c5ddf",
            
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      "image_display_url": 
            
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texas.edu/uploads/group/2025-06-27-032017.037656SUBSIDEthumbnail.png",
            
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      "name": "subsidence",
            
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      "title": "Texas: Statewide Subsidence Data"
            
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    },
            
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    {
            
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      "description": "",
            
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      "display_name": "Texas: Western Region",
            
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      "id": "219f08ff-2d96-4239-b3ec-57d5ffee87e9",
            
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      "image_display_url": 
            
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tacc.utexas.edu/uploads/group/2025-02-21-162954.184423PrudeRanch.png",
            
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      "name": "west-texas",
            
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      "title": "Texas: Western Region"
            
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    }
            
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  "maintainer": "",
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  "maintainer": "",
            
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  "maintainer_email": "spierce@tacc.utexas.edu",
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  "name": "tiff-links-go-look",
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  "name": "tiff-links-go-look",
            
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  "notes": "Links shared during TIFF presentation by Amin Kiaghadi in 
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  "notes": "Links shared during TIFF presentation by Amin Kiaghadi in 
            
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September 2025. ",
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September 2025. ",
            
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  "organization": {
            
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    "approval_status": "approved",
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    "created": "2024-12-13T20:42:00.734799",
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    "created": "2025-09-10T20:59:33.489696",
            
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    "description": "Planet Texas 2050's interdisciplinary research 
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    "description": "",
            
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teams work on designing solutions for stronger, more resilient 
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    "id": "673b95fc-4c5a-4d9a-88c7-ed7cf35bb48c",
            
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communities. The initiative combines expertise from architects, 
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archaeologists, city planners, public health experts, geologists, 
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engineers, biologists, computer scientists, artists and 

            
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community-based partners in an eight-year research program.",

            
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    "image_url": "2025-01-01-201726.957849Planet-Texas-Logo.png",

            
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    "title": "Planet Texas 2050",
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      "name": "Mapped Data Resources for TIFF Coastal Science ",
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