Unlocking Government Open Data: Harnessing Open-Source LLMs for Rapid Insights and Beyond
<p>This chapter explores how large language models (LLMs) can systematically enhance the value creation cycle of open government data (OGD). Building on three established taxonomies and evaluation frameworks for open data, we map key OGD dimensions, research areas, and lifecycle stages to concrete L...
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| Autores principales: | , , , |
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| Formato: | Capítulo de libro |
| Lenguaje: | inglés |
| Publicado: |
IntechOpen
2026
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| Materias: | |
| Acceso en línea: | https://www.intechopen.com/chapters/1237279 |
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| _version_ | 1879164877226901504 |
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| author | Ali, Mohsan Lachana, Zoi Charalabidis, Yannis Alexopoulos, Charalampos |
| author_browse | Alexopoulos, Charalampos Ali, Mohsan Charalabidis, Yannis Lachana, Zoi |
| author_facet | Ali, Mohsan Lachana, Zoi Charalabidis, Yannis Alexopoulos, Charalampos |
| author_sort | Ali, Mohsan |
| building | IntechOpen |
| collection | Acceso abierto |
| description | <p>This chapter explores how large language models (LLMs) can systematically enhance the value creation cycle of open government data (OGD). Building on three established taxonomies and evaluation frameworks for open data, we map key OGD dimensions, research areas, and lifecycle stages to concrete LLMs capabilities. Through this conceptual mapping, we identify seven functional roles for LLMs in the OGD ecosystem: (1) text summarization and comparison, (2) metadata and ontology generation and alignment, (3) multilingual translation and accessibility, (4) user interaction and personalization, (5) quality assessment and evaluation reporting, (6) data cleansing and annotation, and (7) impact and innovation analysis. The chapter synthesizes recent literature and emerging case studies (e.g., conversational interfaces to open data portals, LLM-based data exploration agents) to illustrate how these roles can support policy design, portal architectures, data quality management, and impact measurement. We argue that, when properly governed, LLMs can act as intelligent intermediaries between heterogeneous open data infrastructures and diverse user groups, turning static datasets into dynamic, dialog-driven insight generation environments. At the same time, we highlight risks related to hallucinations, bias, privacy, reproducibility, and over-reliance on proprietary AI infrastructure. The research resulted in seven key functional roles that structure and synthesize the potential contribution of LLMs across the OGD value chain. The chapter concludes with practical guidance for public organizations and researchers seeking to apply LLMs thoughtfully within national and regional open data strategies.</p> |
| doi_str_mv | 10.5772/intechopen.1014744 |
| first_indexed | 2026-10-15T21:41:19Z |
| format | Book Chapter |
| fullrecord | <oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><identifier>intech-1237279</identifier><datestamp>2026-07-28</datestamp>
<dc:title>Unlocking Government Open Data: Harnessing Open-Source LLMs for Rapid Insights and Beyond</dc:title>
<dc:creator>Mohsan Ali</dc:creator>
<dc:creator>Zoi Lachana</dc:creator>
<dc:creator>Yannis Charalabidis</dc:creator>
<dc:creator>Charalampos Alexopoulos</dc:creator>
<dc:subject>Social Sciences and Humanities</dc:subject>
<dc:description><p>This chapter explores how large language models (LLMs) can systematically enhance the value creation cycle of open government data (OGD). Building on three established taxonomies and evaluation frameworks for open data, we map key OGD dimensions, research areas, and lifecycle stages to concrete LLMs capabilities. Through this conceptual mapping, we identify seven functional roles for LLMs in the OGD ecosystem: (1) text summarization and comparison, (2) metadata and ontology generation and alignment, (3) multilingual translation and accessibility, (4) user interaction and personalization, (5) quality assessment and evaluation reporting, (6) data cleansing and annotation, and (7) impact and innovation analysis. The chapter synthesizes recent literature and emerging case studies (e.g., conversational interfaces to open data portals, LLM-based data exploration agents) to illustrate how these roles can support policy design, portal architectures, data quality management, and impact measurement. We argue that, when properly governed, LLMs can act as intelligent intermediaries between heterogeneous open data infrastructures and diverse user groups, turning static datasets into dynamic, dialog-driven insight generation environments. At the same time, we highlight risks related to hallucinations, bias, privacy, reproducibility, and over-reliance on proprietary AI infrastructure. The research resulted in seven key functional roles that structure and synthesize the potential contribution of LLMs across the OGD value chain. The chapter concludes with practical guidance for public organizations and researchers seeking to apply LLMs thoughtfully within national and regional open data strategies.</p></dc:description>
<dc:publisher>IntechOpen</dc:publisher>
<dc:date>2026-07-28</dc:date>
<dc:type>Chapter, Part Of Book</dc:type>
<dc:identifier>https://www.intechopen.com/chapters/1237279</dc:identifier>
<dc:identifier>doi:10.5772/intechopen.1014744</dc:identifier>
<dc:language>en</dc:language>
<dc:relation>ISBN:978-1-83635-536-6</dc:relation>
<dc:rights>https://creativecommons.org/licenses/by/3.0/</dc:rights>
<dc:source>https://www.intechopen.com/books/1004507 ; Open Knowledge Ecosystems: Governance, Standards, AI and Ethics - Critical Perspectives, Infrastructure, and Domain Applications</dc:source>
</oai_dc:dc> |
| id | intech-1237279 |
| institution | IntechOpen |
| isbn | 978-1-83635-536-6 |
| language | English |
| last_indexed | 2026-10-15T21:41:19Z |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| publisher | IntechOpen |
| publisherStr | IntechOpen |
| record_format | oai_dc |
| spelling | intech-12372792026-07-28 Unlocking Government Open Data: Harnessing Open-Source LLMs for Rapid Insights and Beyond Mohsan Ali Zoi Lachana Yannis Charalabidis Charalampos Alexopoulos Social Sciences and Humanities <p>This chapter explores how large language models (LLMs) can systematically enhance the value creation cycle of open government data (OGD). Building on three established taxonomies and evaluation frameworks for open data, we map key OGD dimensions, research areas, and lifecycle stages to concrete LLMs capabilities. Through this conceptual mapping, we identify seven functional roles for LLMs in the OGD ecosystem: (1) text summarization and comparison, (2) metadata and ontology generation and alignment, (3) multilingual translation and accessibility, (4) user interaction and personalization, (5) quality assessment and evaluation reporting, (6) data cleansing and annotation, and (7) impact and innovation analysis. The chapter synthesizes recent literature and emerging case studies (e.g., conversational interfaces to open data portals, LLM-based data exploration agents) to illustrate how these roles can support policy design, portal architectures, data quality management, and impact measurement. We argue that, when properly governed, LLMs can act as intelligent intermediaries between heterogeneous open data infrastructures and diverse user groups, turning static datasets into dynamic, dialog-driven insight generation environments. At the same time, we highlight risks related to hallucinations, bias, privacy, reproducibility, and over-reliance on proprietary AI infrastructure. The research resulted in seven key functional roles that structure and synthesize the potential contribution of LLMs across the OGD value chain. The chapter concludes with practical guidance for public organizations and researchers seeking to apply LLMs thoughtfully within national and regional open data strategies.</p> IntechOpen 2026-07-28 Chapter, Part Of Book https://www.intechopen.com/chapters/1237279 doi:10.5772/intechopen.1014744 en ISBN:978-1-83635-536-6 https://creativecommons.org/licenses/by/3.0/ https://www.intechopen.com/books/1004507 ; Open Knowledge Ecosystems: Governance, Standards, AI and Ethics - Critical Perspectives, Infrastructure, and Domain Applications |
| spellingShingle | Social Sciences and Humanities Ali, Mohsan Lachana, Zoi Charalabidis, Yannis Alexopoulos, Charalampos Unlocking Government Open Data: Harnessing Open-Source LLMs for Rapid Insights and Beyond |
| title | Unlocking Government Open Data: Harnessing Open-Source LLMs for Rapid Insights and Beyond |
| title_full | Unlocking Government Open Data: Harnessing Open-Source LLMs for Rapid Insights and Beyond |
| title_fullStr | Unlocking Government Open Data: Harnessing Open-Source LLMs for Rapid Insights and Beyond |
| title_full_unstemmed | Unlocking Government Open Data: Harnessing Open-Source LLMs for Rapid Insights and Beyond |
| title_short | Unlocking Government Open Data: Harnessing Open-Source LLMs for Rapid Insights and Beyond |
| title_sort | unlocking government open data harnessing open source llms for rapid insights and beyond |
| topic | Social Sciences and Humanities |
| url | https://www.intechopen.com/chapters/1237279 |
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