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Enabling GOV 3.0 through Semantic Web, Natural Language Processing and Text Analytics


Islam A. Hassan, Adegboyega Ojo

Publication Type: 
Refereed Conference Meeting Proceeding
The notion of “Government 3.0” (Gov3.0) is gradually emerging among policymakers as a label for next generation ICT-enabled technology innovation in government and successor to “Government 2.0” (social media or web 2.0 based) initiatives. The Gov3.0 phenomenon has been largely associated with all forms desirable attributes for future government institutions such as increased agility and innovation capacity. However, only few scholarly works have attempted to provide conceptualizations or analysis of this emerging phenomenon. This paper offers such conceptualization, by describing Government 3.0 as Semantic Web (SWEB) or Web 3.0 enabled innovation in government. While there are existing SWEB-based applications in the government domain, the diffusion of this family of applications in the government has been slow if not stagnated. We argue that the reason for this problem is largely due to the lack of tools and domain specific resources for automatic semantic annotation of existing government-related resources and contents on the web and social web. To address this challenge, we describe how text-analytics and Natural Language Processing tools could be used for information extraction and annotation of existing government resources on the web. In addition, we describe how the semantic resources generated from our web-scale automated annotation approach could be used to build two exemplar Gov 3.0 applications. Finally we discuss the challenges in developing this Gov3.0 infrastructure.
Conference Name: 
Transforming Government (t-Gov) Workshop 2014
t-Gov Workshop ’14 (t-Gov 14)
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Publication Date: 
Conference Location: 
United Kingdom (excluding Northern Ireland)
Research Group: 
National University of Ireland, Galway (NUIG)
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