Categorizing Open Government Data Users by Exploring their Challenges and Proficiency

BSTRACT Developing user personas has been a crucial aspect of human-centered system design for decades as it helps in understanding and segregating users based on their prominent characteristics. However, such a technique has not been applied in developing and improving systems for supporting open government data (OGD) users. Therefore, this paper explores OGD users’ characteristics and creates relevant personas for them. Open coding-based content analysis and k-means clustering were performed on posts of an online community managed by a U.S. local-level OGD portal, where users’ characteristics such as purposes, challenges, and proficiency in civic data domain knowledge and computational skills were used as features for clustering. Through manually analyzing the output clusters, we identified three personas with their distinct behavior patterns based on their proficiency. The proposed personas can facilitate in personalizing informational and technological support for OGD forum users.