The next generation of open data platform (ODP+): use case of Qatar

Abstract

Purpose

This study aims to look at challenges that hinder small- and medium-sized enterprises (SMEs) from using open data (OD). The research gaps identified are then used to propose a next generation of OD platform (ODP+).

Design/methodology/approach

This study proposes a more effective platform for SMEs called ODP+. A proof of concept was implemented by using modern techniques and technologies, with a pilot conducted among selected SMEs and government employees to test the approach’s viability.

Findings

The findings identify current OD platforms generally, and in Gulf Cooperation Council (GCC) countries, they encounter several difficulties, including that the data sets are complex to understand and determine their potential for reuse. The application of big data analytics in mitigating the identified challenges is demonstrated through the artefacts that have been developed.

Research limitations/implications

This paper discusses several challenges that must be addressed to ensure that OD is accessible, helpful and of high quality in the future when planning and implementing OD initiatives.

Practical implications

The proposed ODP+ integrates social network data, SME data sets and government databases. It will give SMEs a platform for combining data from government agencies, third parties and social networks to carry out complex analytical scenarios or build the needed application using artificial intelligence.

Social implications

The findings promote the potential future utilisation of OD and suggest ways to give users access to knowledge and features.

Originality/value

To the best of the authors’ knowledge, no study provides extensive research about OD in Qatar or GCC. Further, the proposed ODP+ is a new platform that allows SMEs to run natural language data analytics queries.

Citation

Albinali, A.A., Lock, R. and Phillips, I. (2023), "The next generation of open data platform (ODP+): use case of Qatar", Transforming Government: People, Process and Policy, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/TG-04-2023-0042