ODECO paper on Analysing User Involvement in Open Government Data Initiatives

With Initiating findings from their respective studies, ESR2 Dagoberto Herrera and ESR8 Abdul Aziz presented their work at the International Conference on Theory and Practice of Digital Libraries (TPDL 2022) from September 20-23 in Padua Italy. The title of the paper is ” Analysing User Involvement in Open Government Data Initiatives” in coauthor-ship with Javier Nogueras-Iso , and Francisco J. Lopez-Pellicer.  The proceedings may be found at https://link.springer.com/book/10.1007/978-3-031-16802-4, which is part of the Lecture Notes in Computer Science (LNCS) Springer Series.

This study proposes a technique for measuring user involvement in Open Data portals by an analysis of Twitter activity in an effort to deduce the connection between social network activity and the primary characteristics that define the size, quality, and maturity of Open Data portals.


Over the last decade, many Open Data initiatives have been launched by public administrations to promote transparency and reuse of data. However, it is not easy to assess the impact of data availability from the perspective of user communities. Although some Open Data portals provide mechanisms for user feedback through dedicated discussion forums, web forms, and some of the user experiences are listed as use cases in their portals, there is no consistent way to compare user feedback in different data initiatives. To overcome the difficulty of assessing user impact, this paper examines the activity generated by Open Data initiatives through the social network Twitter: a forum used by all types of stakeholders and publicly available for consistent analysis. We propose a methodology to compile a set of variables that describe both the main characteristics of Open Data initiatives and the associated Twitter activity. The collected data is then analysed using factor analysis and clustering techniques to derive possible relationships between the variables. Finally, the initiatives are classified according to their activity on social networks and the values that characterise some of their features. The methodology was evaluated by analysing 27 European Open Government Data portals and their activity on Twitter in 2021.