RESUMO
We introduce "Natural" differential privacy (NDP)-which utilizes features of existing hardware architecture to implement differentially private computations. We show that NDP both guarantees strong bounds on privacy loss and constitutes a practical exception to no-free-lunch theorems on privacy. We describe how NDP can be efficiently implemented and how it aligns with recognized privacy principles and frameworks. We discuss the importance of formal protection guarantees and the relationship between formal and substantive protections.
RESUMO
The scholarly knowledge ecosystem presents an outstanding exemplar of the challenges of understanding, improving, and governing information ecosystems at scale. This article draws upon significant reports on aspects of the ecosystem to characterize the most important research challenges and promising potential approaches. The focus of this review article is the fundamental scientific research challenges related to developing a better understanding of the scholarly knowledge ecosystem. Across a range of disciplines, we identify reports that are conceived broadly, published recently, and written collectively. We extract the critical research questions, summarize these using quantitative text analysis, and use this quantitative analysis to inform a qualitative synthesis. Three broad themes emerge from this analysis: the need for multi-sectoral cooperation and coordination, for mixed methods analysis at multiple levels, and interdisciplinary collaboration. Further, we draw attention to an emerging consensus that scientific research in this area should by a set of core human values.
