Extraction of knowledge from open government data

Abstract

Purpose The purpose of this paper is to establish a new conceptual iterative framework for extracting knowledge from open government data (OGD). OGD is becoming a major source for knowledge and innovation to generate economic value, if properly used. However, currently there are no standards or frameworks for applying knowledge continuum tactics, techniques and procedures (TTPs) to improve elicit knowledge extraction from OGD in a consistent manner. Design/methodology/approach This paper is based on a comprehensive review of literature on both OGD and knowledge management (KM) frameworks. It provides insights into the extraction of knowledge from OGD by using a vast array of phased KM TTPs into the OGD lifecycle phases. Findings The paper proposes a knowledge iterative value network (KIVN) as a new conceptual model that applies the principles of KM on OGD. KIVN operates through applying KM TTPs to transfer and transform discrete data into valuable knowledge. Research limitations/implications This model covers the most important knowledge elicitation steps; however, users who are interested in using KIVN phases may need to slightly customize it based on their environment and OGD policy and procedure. Practical implications After its validation, the model allows facilitating systemic manipulation of OGD for both data-consuming industries and data-producing governments to establish new business models and governance schemes to better make use of OGD. Originality/value This paper offers new perspectives on eliciting knowledge from OGD and discussing crucial, but overlooked area of the OGD arena, namely, knowledge extraction through KM principles.

Persuasion of tacit knowledge in teaching information technology and information systems

“…The author stated that the nonspatial distance between data and knowledge can collectively be described as the knowledge continuum. The existence of data, information and knowledge in continuum has been reported by Saba (2019), Mohamed et al (2020), O’grady (2012), Masud et al (2010), Senatore et al (2019), Randles et al (2012), Zins (2007), Faucher et al (2008) and Shim and Roth (2008). Nonaka and Krogh (2009) stated that “TK and EK can be conceptually distinguished along a continuum.” The begetting of information from data using IS aligned with Nonaka’s idea of knowledge creation in the SECI model.…”

ENEA PAES: A Web Platform for Supporting Italian Municipalities in Sustainable Energy Action Plan

“…Public administration (PA) shares authoritative open data (Mohamed et al 2020) by the guidelines proposed for data sharing (AGID 2022; Colpaert et al 2013). These heterogeneous data are available in different machine-readable formats.…”

“…In this context, the PAES platform provides digital support to municipal operators to draft a BEI, taking advantage even of valuable open data (Mohamed et al 2020) shared by Italian PA. Particularly, the BEI provides a preliminary estimate of CO 2 emissions divided by sector (residential, transportation, tertiary) and energy carrier.…”

New challenges for public value and accountability in the age of big data: a bibliometric analysis

“…As Andrews (2019) argues, public value theory (Moore, 1995;Bozeman, 2007) has rarely been used to support regulatory action on data governance. The excessive emphasis on open government models (Dawes et al, 2016;Mohamed et al, 2020) has delayed political and scientific reflection on the conceptual and empirical link between private data and public value, with a few recent exceptions (Ingrams, 2018).…”