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  "name": "interactive-sites-stories",
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  "name": "interactive-sites-stories",
            
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  "notes": "Based on the annual report, here are the significant 
16
  "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 
18
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 
20
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 
            
23
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 
24
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 
            
27
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 
            
30
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 
            
33
environments while supporting both interview data collection and drone 
33
environments while supporting both interview data collection and drone 
            
34
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 
            
36
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 
37
Linking and Automated Knowledge Integration\r\n\r\nThe S&S application 
            
38
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 
40
identified stakeholder problems. The system now enables semantic 
            
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linking of stakeholder interview information with digital terrain 
41
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 
            
43
advancement allows for automated connection of community knowledge 
43
advancement allows for automated connection of community knowledge 
            
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with scientific models and observational data.\r\n\r\n## 4. 
44
with scientific models and observational data.\r\n\r\n## 4. 
            
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Demonstrated Transferability and Scalability Across 
45
Demonstrated Transferability and Scalability Across 
            
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Contexts\r\n\r\nThe capabilities were successfully replicated and 
46
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 
47
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 
48
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 
49
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 
50
large research teams and community partners. The system is now fully 
            
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scalable, reusable, and easily modified across different settings and 
51
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 
53
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 
55
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. 
57
using four Large Language Foundation Model options on TACC systems. 
            
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These workflows provide mechanisms for linking lived experience 
58
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 
60
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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available via Science Gateway applications and GitHub.",
            
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teams work on designing solutions for stronger, more resilient 
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teams work on designing solutions for stronger, more resilient 
            
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communities. The initiative combines expertise from architects, 
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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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archaeologists, city planners, public health experts, geologists, 
            
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engineers, biologists, computer scientists, artists and 
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engineers, biologists, computer scientists, artists and 
            
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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 
164
description of analyzing qualitative data using natural language 
            
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processing and large language modeling tools on the science gateways 
165
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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