TAPAS: A Pattern-Based Approach to Assessing Government Transparency

TL;DR

This paper tackles the challenge of assessing government transparency by shifting focus from external proxies to the actual day-to-day information-management practices that underlie transparency. It introduces TAPAS, a design-science, pattern-based artifact that identifies transparency-impeding anti-patterns in electronic document management and uses data-driven indicators and rules to monitor these behaviors continuously. The study contributes an eight-anti-pattern catalog organized into four impact categories, demonstrates feasibility through a large-scale implementation at a Dutch ministry using two decades of EDMS data, and shows how TAPAS yields actionable, low-cost insights via ongoing monitoring. The approach provides a practical, technology-agnostic toolkit for governments seeking to improve transparency through better information-management practices, with explicit guidance on evaluation, dashboard deployment, and future research directions that connect anti-pattern metrics to traditional transparency indices.

Abstract

Government transparency, widely recognized as a cornerstone of open government, depends on robust information management practices. Yet effective assessment of information management remains challenging, as existing methods fail to consider the actual working behavior of civil servants and are resource-intensive. Using a design science research approach, we present the Transparency Anti-Pattern Assessment System (TAPAS) -- a novel, data-driven methodology designed to evaluate government transparency through the identification of behavioral patterns that impede transparency. We demonstrate TAPAS's real-world applicability at a Dutch ministry, analyzing their electronic document management system data from the past two decades. We identify eight transparency anti-patterns grouped into four categories: Incomplete Documentation, Limited Accessibility, Unclear Information, and Delayed Documentation. We show that TAPAS enables continuous monitoring and provides actionable insights without requiring significant resource investments.

Figures (3)

• Figure 1: Overview of the TAPAS methodology
• Figure 2: Indicators and detection occurrences averaged over the whole organization
• Figure 3: Detection of Batch Documentation yearly (left) and monthly (right) per organizational unit