The maturity of open government data maturity: a multivocal literature review

Author:

Çaldağ Murat TahirORCID,Gökalp EbruORCID

Abstract

PurposeThe aim of this study is to provide administrators in government institutions a roadmap to achieve benefits of open government data (OGD) by reviewing and classifying studies with assessment or maturity models (MMs) in the OGD domain with a Multivocal Literature Review (MLR).Design/methodology/approachTo achieve this goal, the authors conducted an MLR that includes data from not only the formal literature but also the grey literature (e.g. white papers and online documents).FindingsOut of 3,569 sources, 81 studies were selected by following the elimination scheme and assessing sources by relevance and methodology. As a result of the quality assessment of the identified MMs based on predefined criteria, unambiguity, comparability, repeatability, completeness, clearness and objectivity, it was observed that there are a limited number of MMs in this domain and none of them fully satisfies the requirements.Originality/valueThis study is likely the first MLR on OGD domain. This MLR serves as a first step for future research on OGD assessment and MMs by presenting the need to establish a holistic approach covering all OGD dimensions, creation of an objective assessment method, prescriptive properties, and empirical evaluation demonstrating the applicability and usefulness at different scope levels.

Publisher

Emerald

Subject

Library and Information Sciences,Information Systems

Reference63 articles.

1. A systematic literature review of open government data research: challenges, opportunities and gaps,2018

2. Motivations for open data adoption: an institutional theory perspective;Government Information Quarterly,2018

3. A systematic review of open government data initiatives;Government Information Quarterly,2015

4. Developing maturity models for IT management;Business & Information Systems Engineering,2009

5. A maturity model for public administration as open translation data providers;ArXiv Preprint ArXiv:1607.01990,2016

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