Classification of Open Government Data Solutions’ Help: A Novel Taxonomy and Cluster Analysis

Jonathan Crusoe, Antoine Clarinval

Résultats de recherche: Contribution dans un livre/un catalogue/un rapport/dans les actes d'une conférenceArticle dans les actes d'une conférence/un colloque


Open Government Data (OGD) pose that public organisations should freely share data for anyone to reuse without restrictions. However, the rawness of this data proves to be a challenge for data or information seekers. OGD-based solutions, such as interactive maps and dashboards, could help seekers overcome this difficulty and use OGD to satisfy needs, helping them to work effectively, solve problems, or pursue hobbies. However, there are several challenges that need to be considered when designing solutions, such as seekers wanting to solve problems rather than consuming information and aiming for quick wins over quality. Previous research has classified OGD solutions, focusing on general concepts. The next step is to reveal helpful patterns in OGD solutions, helping seekers. This paper presents a taxonomy with 24 criteria to classify these patterns. It was tested on 40 OGD solutions, and the resulting classifications were grouped in a cluster analysis, identifying 16 key criteria and 6 clusters. The clusters are (1) simple-personalised, (2) proactive multi-visual, (3) lightly-facilitated exploration, (4) facilitated data-management, (5) facilitated information exploration, and (6) horizon solutions. One unexpected finding is that helpful patterns do not cluster following themes, types, or purposes of solutions. Another finding is that the importance of key criteria varies between the clusters.

langue originaleAnglais
titreElectronic Government - 22nd IFIP WG 8.5 International Conference, EGOV 2023, Proceedings
rédacteurs en chefIda Lindgren, Csaba Csáki, Evangelos Kalampokis, Efthimios Tambouris, Marijn Janssen, Anneke Zuiderwijk, Gabriela Viale Pereira, Shefali Virkar
EditeurSpringer Science and Business Media Deutschland GmbH
Nombre de pages16
ISBN (imprimé)9783031411373
Les DOIs
Etat de la publicationPublié - 2023
Evénement22nd IFIP WG 8.5 International Conference on Electronic Government, EGOV 2023 - Budapest, Hongrie
Durée: 5 sept. 20237 sept. 2023

Série de publications

NomLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14130 LNCS
ISSN (imprimé)0302-9743
ISSN (Electronique)1611-3349

Une conférence

Une conférence22nd IFIP WG 8.5 International Conference on Electronic Government, EGOV 2023
La villeBudapest

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