Artificial Intelligence as a Catalyzer for Open Government Data Ecosystems: A Typological Theory Approach

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F25%3A50022421" target="_blank" >RIV/62690094:18450/25:50022421 - isvavai.cz</a>

Výsledek na webu

<a href="https://scholarspace.manoa.hawaii.edu/server/api/core/bitstreams/8ebfe9f6-65c6-4673-88b2-094bde970bb2/content" target="_blank" >https://scholarspace.manoa.hawaii.edu/server/api/core/bitstreams/8ebfe9f6-65c6-4673-88b2-094bde970bb2/content</a>

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Artificial Intelligence as a Catalyzer for Open Government Data Ecosystems: A Typological Theory Approach

Popis výsledku v původním jazyce

Artificial Intelligence (AI) within digital government has witnessed growing interest as it can improve governance processes and stimulate citizen engagement. Despite the rise of Generative AI, discussions on AI fusion with Open Government Data (OGD) remain limited to specific implementations and scattered across disciplines. Drawing from the synthesis of the literature through a systematic review, this study examines and structures how AI can enrich OGD initiatives. Employing a typological approach, ideal profiles of AI application within the OGD lifecycle are formalized, capturing varied roles across the portal and ecosystems perspectives. The resulting conceptual framework identifies eight ideal types of AI applications for OGD: AI as Portal Curator, Explorer, Linker, and Monitor, and AI as Ecosystem Data Retriever, Connecter, Value Developer and Engager. This theoretical foundation shows the under-investigation of some types and will inform policymakers, practitioners, and researchers in leveraging AI to cultivate OGD ecosystems.

Název v anglickém jazyce

Artificial Intelligence as a Catalyzer for Open Government Data Ecosystems: A Typological Theory Approach

Popis výsledku anglicky

Artificial Intelligence (AI) within digital government has witnessed growing interest as it can improve governance processes and stimulate citizen engagement. Despite the rise of Generative AI, discussions on AI fusion with Open Government Data (OGD) remain limited to specific implementations and scattered across disciplines. Drawing from the synthesis of the literature through a systematic review, this study examines and structures how AI can enrich OGD initiatives. Employing a typological approach, ideal profiles of AI application within the OGD lifecycle are formalized, capturing varied roles across the portal and ecosystems perspectives. The resulting conceptual framework identifies eight ideal types of AI applications for OGD: AI as Portal Curator, Explorer, Linker, and Monitor, and AI as Ecosystem Data Retriever, Connecter, Value Developer and Engager. This theoretical foundation shows the under-investigation of some types and will inform policymakers, practitioners, and researchers in leveraging AI to cultivate OGD ecosystems.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 58th Hawaii International Conference on System Sciences

ISBN

978-0-9981331-8-8

ISSN

1530-1605

e-ISSN

—

Počet stran výsledku

10

Strana od-do

2176-2185

Název nakladatele

University of Hawaii Press

Místo vydání

Honolulu

Místo konání akce

Waikoloa

Datum konání akce

7. 1. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001443246900260