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On 8. septembra 2025, 20:09:22 UTC,
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Updated description of resource Slides for TWDB Discussion August 2025 in Sites & Stories Application to
This is a presentation slide deck that summarizes the state of features and capabilities developed as decision support systems. The slides walkthrough a demo and description of analyzing qualitative data using natural language processing and large language modeling tools on the science gateways portals. Additionally, features for an interactive annotation interface that allows users to label and describe text tracebacks to interviews or corpora on an interactive 3D terrain data representation built on lidar point datasets.
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15 | "name": "interactive-sites-stories", | 15 | "name": "interactive-sites-stories", | ||
16 | "notes": "Based on the annual report, here are the significant | 16 | "notes": "Based on the annual report, here are the significant | ||
17 | results for the Sites & Stories Application and AI approaches that | 17 | results for the Sites & Stories Application and AI approaches that | ||
18 | Suzanne Pierce and Texas Advanced Computing Center contributed | 18 | Suzanne Pierce and Texas Advanced Computing Center contributed | ||
19 | to:\r\n\r\n## 1. Deployed Scalable AI-Enabled Analytical | 19 | to:\r\n\r\n## 1. Deployed Scalable AI-Enabled Analytical | ||
20 | Infrastructure\r\n\r\nThe Sites & Stories (S&S) application advanced | 20 | Infrastructure\r\n\r\nThe Sites & Stories (S&S) application advanced | ||
21 | 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 | ||
22 | 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 | ||
24 | Language Model capabilities through a science gateway data portal that | 24 | Language Model capabilities through a science gateway data portal that | ||
25 | 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 | ||
26 | 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 | ||
28 | Field-Ready Data Collection and Analysis Capabilities \r\n\r\nThe | 28 | Field-Ready Data Collection and Analysis Capabilities \r\n\r\nThe | ||
29 | 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 | ||
31 | 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 | ||
35 | 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 | ||
37 | 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 | ||
39 | identification of relevant data collections and models for locally | 39 | identification of relevant data collections and models for locally | ||
40 | identified stakeholder problems. The system now enables semantic | 40 | identified stakeholder problems. The system now enables semantic | ||
41 | linking of stakeholder interview information with digital terrain | 41 | linking of stakeholder interview information with digital terrain | ||
42 | 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 | ||
44 | with scientific models and observational data.\r\n\r\n## 4. | 44 | with scientific models and observational data.\r\n\r\n## 4. | ||
45 | Demonstrated Transferability and Scalability Across | 45 | Demonstrated Transferability and Scalability Across | ||
46 | Contexts\r\n\r\nThe capabilities were successfully replicated and | 46 | Contexts\r\n\r\nThe capabilities were successfully replicated and | ||
47 | tested for transferability in the Rio Grande Valley of Texas, proving | 47 | tested for transferability in the Rio Grande Valley of Texas, proving | ||
48 | the system's applicability beyond Arctic contexts. The S&S application | 48 | the system's applicability beyond Arctic contexts. The S&S application | ||
49 | was deployed for broad use by researchers with training provided to | 49 | was deployed for broad use by researchers with training provided to | ||
50 | large research teams and community partners. The system is now fully | 50 | large research teams and community partners. The system is now fully | ||
51 | scalable, reusable, and easily modified across different settings and | 51 | scalable, reusable, and easily modified across different settings and | ||
52 | use cases.\r\n\r\n## 5. Established Reusable Computational Cookbook | 52 | use cases.\r\n\r\n## 5. Established Reusable Computational Cookbook | ||
53 | Framework \r\n\r\nAI-enabled analytical workflows are now available | 53 | Framework \r\n\r\nAI-enabled analytical workflows are now available | ||
54 | across multiple scales, from individual narrative analysis through | 54 | across multiple scales, from individual narrative analysis through | ||
55 | Natural Language Processing computational cookbooks to topical | 55 | Natural Language Processing computational cookbooks to topical | ||
56 | analysis using BERTtopic cookbook, plus open-ended analysis tools | 56 | analysis using BERTtopic cookbook, plus open-ended analysis tools | ||
57 | using four Large Language Foundation Model options on TACC systems. | 57 | using four Large Language Foundation Model options on TACC systems. | ||
58 | These workflows provide mechanisms for linking lived experience | 58 | These workflows provide mechanisms for linking lived experience | ||
59 | information with observational data and physics-based models in | 59 | information with observational data and physics-based models in | ||
60 | convergent applications, with the full code base and reusable products | 60 | convergent applications, with the full code base and reusable products | ||
61 | available via Science Gateway applications and GitHub.", | 61 | available via Science Gateway applications and GitHub.", | ||
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68 | teams work on designing solutions for stronger, more resilient | 68 | teams work on designing solutions for stronger, more resilient | ||
69 | communities. The initiative combines expertise from architects, | 69 | communities. The initiative combines expertise from architects, | ||
70 | archaeologists, city planners, public health experts, geologists, | 70 | archaeologists, city planners, public health experts, geologists, | ||
71 | engineers, biologists, computer scientists, artists and | 71 | engineers, biologists, computer scientists, artists and | ||
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162 | summarizes the state of features and capabilities developed as | ||||
163 | decision support systems. The slides walkthrough a demo and | ||||
164 | description of analyzing qualitative data using natural language | ||||
165 | processing and large language modeling tools on the science gateways | ||||
166 | portals. Additionally, features for an interactive annotation | ||||
167 | interface that allows users to label and describe text tracebacks to | ||||
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