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  "name": "interactive-sites-stories",
            
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  "notes": "Based on the annual report, here are the significant 
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  "notes": "Based on the annual report, here are the significant 
            
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results for the Sites & Stories Application and AI approaches that 
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results for the Sites & Stories Application and AI approaches that 
            
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Suzanne Pierce and Texas Advanced Computing Center contributed 
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Suzanne Pierce and Texas Advanced Computing Center contributed 
            
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to:\r\n\r\n## 1. Deployed Scalable AI-Enabled Analytical 
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to:\r\n\r\n## 1. Deployed Scalable AI-Enabled Analytical 
            
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Infrastructure\r\n\r\nThe Sites & Stories (S&S) application advanced 
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Infrastructure\r\n\r\nThe Sites & Stories (S&S) application advanced 
            
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from testing to full deployment as a reusable tool on Texas Advanced 
21
from testing to full deployment as a reusable tool on Texas Advanced 
            
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Computing Center Resources. The system now provides cross-scale 
22
Computing Center Resources. The system now provides cross-scale 
            
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applications of Natural Language Processing, topic modeling, and Large 
23
applications of Natural Language Processing, topic modeling, and Large 
            
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Language Model capabilities through a science gateway data portal that 
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Language Model capabilities through a science gateway data portal that 
            
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enables analyses at scale with HPC and GPU compute. LLM tools were 
25
enables analyses at scale with HPC and GPU compute. LLM tools were 
            
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successfully incorporated into the S&S application suite with open and 
26
successfully incorporated into the S&S application suite with open and 
            
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reproducible access as of June 2024.\r\n\r\n## 2. Validated 
27
reproducible access as of June 2024.\r\n\r\n## 2. Validated 
            
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Field-Ready Data Collection and Analysis Capabilities  \r\n\r\nThe 
28
Field-Ready Data Collection and Analysis Capabilities  \r\n\r\nThe 
            
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team completed 25 performance field tests in Nunapitchuk to evaluate 
29
team completed 25 performance field tests in Nunapitchuk to evaluate 
            
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the Sites & Stories data collection and ingest services using 
30
the Sites & Stories data collection and ingest services using 
            
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variations in hardware, software, and data catalog capabilities. These 
31
variations in hardware, software, and data catalog capabilities. These 
            
32
tests demonstrated the system's ability to function in remote Arctic 
32
tests demonstrated the system's ability to function in remote Arctic 
            
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environments while supporting both interview data collection and drone 
33
environments while supporting both interview data collection and drone 
            
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terrain data processing. The application successfully automated 
34
terrain data processing. The application successfully automated 
            
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analytical approaches with AI to connect qualitative and quantitative 
35
analytical approaches with AI to connect qualitative and quantitative 
            
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knowledge in well-defined workflows.\r\n\r\n## 3. Advanced Semantic 
36
knowledge in well-defined workflows.\r\n\r\n## 3. Advanced Semantic 
            
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Linking and Automated Knowledge Integration\r\n\r\nThe S&S application 
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Linking and Automated Knowledge Integration\r\n\r\nThe S&S application 
            
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was enhanced with semantic linking mechanisms to automate 
38
was enhanced with semantic linking mechanisms to automate 
            
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identification of relevant data collections and models for locally 
39
identification of relevant data collections and models for locally 
            
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identified stakeholder problems. The system now enables semantic 
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identified stakeholder problems. The system now enables semantic 
            
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linking of stakeholder interview information with digital terrain 
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linking of stakeholder interview information with digital terrain 
            
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models, creating culturally-informed technical resources. This 
42
models, creating culturally-informed technical resources. This 
            
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advancement allows for automated connection of community knowledge 
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advancement allows for automated connection of community knowledge 
            
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with scientific models and observational data.\r\n\r\n## 4. 
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with scientific models and observational data.\r\n\r\n## 4. 
            
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Demonstrated Transferability and Scalability Across 
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Demonstrated Transferability and Scalability Across 
            
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Contexts\r\n\r\nThe capabilities were successfully replicated and 
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Contexts\r\n\r\nThe capabilities were successfully replicated and 
            
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tested for transferability in the Rio Grande Valley of Texas, proving 
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tested for transferability in the Rio Grande Valley of Texas, proving 
            
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the system's applicability beyond Arctic contexts. The S&S application 
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the system's applicability beyond Arctic contexts. The S&S application 
            
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was deployed for broad use by researchers with training provided to 
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was deployed for broad use by researchers with training provided to 
            
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large research teams and community partners. The system is now fully 
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large research teams and community partners. The system is now fully 
            
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scalable, reusable, and easily modified across different settings and 
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scalable, reusable, and easily modified across different settings and 
            
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use cases.\r\n\r\n## 5. Established Reusable Computational Cookbook 
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use cases.\r\n\r\n## 5. Established Reusable Computational Cookbook 
            
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Framework  \r\n\r\nAI-enabled analytical workflows are now available 
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Framework  \r\n\r\nAI-enabled analytical workflows are now available 
            
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across multiple scales, from individual narrative analysis through 
54
across multiple scales, from individual narrative analysis through 
            
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Natural Language Processing computational cookbooks to topical 
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Natural Language Processing computational cookbooks to topical 
            
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analysis using BERTtopic cookbook, plus open-ended analysis tools 
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analysis using BERTtopic cookbook, plus open-ended analysis tools 
            
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using four Large Language Foundation Model options on TACC systems. 
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using four Large Language Foundation Model options on TACC systems. 
            
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These workflows provide mechanisms for linking lived experience 
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These workflows provide mechanisms for linking lived experience 
            
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information with observational data and physics-based models in 
59
information with observational data and physics-based models in 
            
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convergent applications, with the full code base and reusable products 
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convergent applications, with the full code base and reusable products 
            
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available via Science Gateway applications and GitHub.",
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summarizes the state of features and capabilities developed as 
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decision support systems. The slides walkthrough a demo and 
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decision support systems. The slides walkthrough a demo and 
            
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description of analyzing qualitative data using natural language 
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description of analyzing qualitative data using natural language 
            
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processing and large language modeling tools on the science gateways 
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processing and large language modeling tools on the science gateways 
            
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portals. Additionally, features for an interactive annotation 
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portals. Additionally, features for an interactive annotation 
            
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interface that allows users to label and describe text tracebacks to 
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interface that allows users to label and describe text tracebacks to 
            
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interviews or corpora on an interactive 3D terrain data representation 
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interviews or corpora on an interactive 3D terrain data representation 
            
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built on lidar point datasets.",
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