ABSTRACT
Parliaments will eventually not evade the digital evolution of every institution to become data-driven organisations. This study examines the Hellenic Optical Character Recognition (OCR) Team, a pioneering crowdsourcing initiative aimed at processing and analysing parliamentary data. Under certain conditions, crowdsourcing, in other words, the power of the people, can be appropriately channelled and exploited to support representative institutions and their societal stakeholders in managing their change processes. Based on survey findings, this research highlights the profiles and motivations of participants, identifies best practices for crowdsourcing in parliamentary contexts, and demonstrates the initiative's impact on improving data accessibility and transparency. The results suggest that the Hellenic OCR Team significantly contributes to the digital evolution of parliamentary functions and promotes greater public involvement in the legislative process.
Acknowledgements
Open Access funding provided by the Qatar National Library.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
Fotios Fitsilis
Dr. Fotios Fitsilis is a parliamentary researcher with over 20 years of experience in scientific roles across both private and public sectors. Since 2009, he has served as the Head of the Department for Scientific Documentation and Supervision at the Hellenic Parliament. His global contributions span telecommunications, management, and governance, with a focus on artificial intelligence and parliamentary oversight. In 2017, he co-founded the Hellenic OCR Team.
George Mikros
George Mikros is currently a Professor and Coordinator of the MA Program of Digital Humanities and Societies at the Hamad Bin Khalifa University in Qatar. Since 2013, he has also been Adj. Professor at the University of Massachusetts, Boston, USA. In 2017, he co-founded the Hellenic OCR Team. Prof. Mikros has authored 5 monographs and over 100 papers published in peer-reviewed journals, conference proceedings, and edited volumes. His main research interests are Large Language Models, Computational and Forensic Linguistics.