Data donation, an emerging user-centric data collection method for public sector research, faces a gap between participant willingness and actual donation. This suggests a design absence in practice: while promoted as "donor-centered" with technical and regulational advances, a design perspective on how data choices are presented and intervene on individual behaviors remain underexplored. In this paper, we focus on pre-donation data exploration, a key stage for adequately and meaningful informed participation. Through a real-world data donation study (N=24), we evaluated three data exploration interventions (self-focused, social comparison, collective-only). Findings show choice framing impacts donation participation. The "social comparison" design (87.5%) outperformed the "self-focused view" (62.5%) while a "collective-only" frame (37.5%) backfired, causing "perspective confusion" and privacy concerns. This study demonstrates how strategic data framing addresses data donation as a behavioral challenge, revealing design's critical yet underexplored role in data donation for participatory public sector innovation.

翻译：摘要：数据捐赠作为一种新兴的以用户为中心的公部门研究数据收集方法，正面临参与者意愿与实际捐赠行为之间的鸿沟。这揭示了实践中的设计缺失：尽管在技术与监管层面已取得进展并被推广为"以捐赠者为中心"，但有关数据选择如何呈现并干预个体行为的设计视角仍未得到充分探索。本文聚焦于数据捐赠前的探索阶段——这是实现充分且有意义知情参与的关键环节。通过一项真实数据捐赠研究（N=24），我们评估了三种数据探索干预方式（自我聚焦、社会比较、集体性呈现）。结果表明选择框架对捐赠参与度产生影响。"社会比较"设计（87.5%）优于"自我聚焦视图"（62.5%），而"集体性呈现"框架（37.5%）引发"视角混淆"与隐私担忧，产生反效果。本研究揭示了策略性数据框架如何将数据捐赠转化为行为挑战，论证了设计在参与式公部门创新数据捐赠中关键且未被充分探索的作用。