TY - GEN
T1 - Classification of Open Government Data Solutions’ Help
T2 - 22nd IFIP WG 8.5 International Conference on Electronic Government, EGOV 2023
AU - Crusoe, Jonathan
AU - Clarinval, Antoine
N1 - Publisher Copyright:
© 2023, IFIP International Federation for Information Processing.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - classification
KW - cluster analysis
KW - information behaviour
KW - Open Government Data
KW - solution
KW - taxonomy
UR - http://www.scopus.com/inward/record.url?scp=85172033461&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-41138-0_15
DO - 10.1007/978-3-031-41138-0_15
M3 - Conference contribution
AN - SCOPUS:85172033461
SN - 9783031411373
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 230
EP - 245
BT - Electronic Government - 22nd IFIP WG 8.5 International Conference, EGOV 2023, Proceedings
A2 - Lindgren, Ida
A2 - Csáki, Csaba
A2 - Kalampokis, Evangelos
A2 - Tambouris, Efthimios
A2 - Janssen, Marijn
A2 - Zuiderwijk, Anneke
A2 - Viale Pereira, Gabriela
A2 - Virkar, Shefali
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 5 September 2023 through 7 September 2023
ER -