Measuring User Engagement in Open Data Platforms

Abstract

Existing research on open data engagement has predominantly focused on the supply-side indicators or on the subjective demand-side evaluations, while objective-based analysis of the demand-side engagement remains underexplored. Drawing on the platform ecosystem perspective, this paper takes a different approach by examining open data platform engagement as an indicator of value creation through observable behavioral interactions, thereby positioning our study on the demand-side and within an objective-based evaluation. Through interviews with 15 open data platform stakeholders, we identify opportunities to measure engagement using behavioral indicators derived from platform use. Building on these findings, we develop a multi-layer framework of behavioral indicators to measure engagement with open data platforms. The framework consists of four layers which includes: system-level indicators, behavioral metrics, interactive signals, and contextual factors. We present a proof-of-concept implementation that operationalizes the proposed framework using platform logs, providing guidance for open data platform designers and policymakers to evaluate engagement. The paper contributes to the open data evaluation literature by reconceptualizing engagement as an observable, value-creating behavior in open data platforms. In this way, the demand-side is taken into account, and the actual behavior is measured, which data can complement the subjective data. Overall, the study demonstrates how integrating objective measures with subjective evaluation can support a more comprehensive and value-oriented engagement measurement of open data platforms.